In 2025, using an AI chat for lead generation isn’t just smart.

It’s how the most effective teams are scaling conversations, qualifying prospects faster, and driving pipeline on autopilot. 

Whether embedded on your website or connected to your outbound workflows, AI chats are turning passive traffic into warm leads 24/7.

But here’s the catch: not all AI chats are created equal. 

The real magic happens when you combine instant responsiveness with deep context, such as who the visitor is, what they’ve done before, and what they actually care about.

In this guide, I’ll break down exactly how to use an AI chat for lead generation in 2025: from strategy and setup to real-world use cases and the tools that are changing the game. 

If you’re looking to engage the right prospects at the right time without blowing up your SDR team’s calendar, you’re in the right place.

Let’s dive into how to make AI chat work for your GTM motion!

How do AI chatbots work for sales?

AI chatbots for sales aren’t just digital receptionists. It’s more accurate to think of them as frontline revenue agents. 

What does this mean?

At a high level, AI chatbots use natural language processing (NLP), behavioral data, and CRM integrations to engage site visitors, qualify intent, and route leads in real time. 

But what makes them truly valuable in 2025 is how they fit into your go-to-market motion.

Here’s how it works: someone lands on your site, maybe after clicking a LinkedIn ad or searching for a solution. 

Instead of offering a static form, an AI chat jumps in with a human-sounding question tailored to that visitor’s context, i.e., who they are, what page they’re on, and how they got there. 

From there, the chat does three things almost instantly:

1. Starts a warm conversation - It opens with context-aware prompts (“Looking for help with X?”), building trust right away.
2. Qualifies intent without friction - Through smart, dynamic questions, it captures buying signals, firmographic data, and need-level without ever feeling like a survey.
3. Routes hot leads to your team - Based on responses and behavioral cues, it can book a meeting, notify an SDR, or push the lead into your CRM with tags, scores, and notes automatically.

Unlike traditional live chat (which relies on having someone online), AI chats work 24/7 and scale with your traffic. 

And because they’re integrated with tools like your CRM or outreach platforms, every conversation becomes part of a larger, orchestrated funnel, and not a one-off interaction.

The result? Faster handoffs. Cleaner pipeline. More qualified leads, less SDR burnout.

How to use an AI chat for lead generation - 8 high-impact use cases 

So, what does AI chat actually look like in action?

Below are eight real-world use cases that show how AI chat can drive serious impact across the entire buyer journey, from the moment someone lands on your site to the point they book a meeting (and beyond). 

Some are foundational. Others are advanced. But together, they make AI chat a core part of a modern revenue engine.

1. Lead qualification and scoring

Traditional lead qualification usually depends on two things: static forms and manual follow-up. 

A visitor lands on your site, fills in a form (if you're lucky), and a rep reaches out later to ask discovery questions. 

It’s slow, it’s impersonal, and it often leads to ghosting - or worse, wasted time on unqualified leads.

AI chat flips that model on its head.

Instead of making prospects wait or fill out rigid forms, AI chat starts a conversation the moment someone lands on your site. 

And it uses contextual cues like what page they’re viewing or how they arrived, to open with questions that feel natural and relevant. 

From there, it gathers the information your team needs to assess fit: goals, timeline, role, company size, and urgency.

And it does all of this in real-time, without forcing the visitor into a one-size-fits-all funnel.

With Warmly, this process goes beyond the conversation itself. 

The platform actively monitors both on-site and off-site intent signals, such as: 

• Which pages a visitor browses.
• How often they return?
• Whether they’ve already engaged with outbound campaigns.
• If they’re already in your CRM from a previous deal cycle.
• Whether they’ve already researched your competitors, etc.

The AI chat then uses these signals in real-time to help qualify and score leads more accurately. 

This means that Warmly’s AI Chat doesn’t just score someone based on what they say - it scores them based on what they do. 

A visitor checking your pricing page for the third time? That’s a high-intent signal. 

A returning lead from a closed-lost opportunity? That’s context worth acting on.

Combined with how the lead interacts during the chat, these behavioral signals give your team a far more complete - and actionable - picture of each prospect’s potential, without a rep needing to dig for it.

2. Reactivating closed-lost accounts

Closed-lost doesn’t always mean “never.” 

Sometimes the timing was off. Sometimes priorities shifted. And sometimes the deal just quietly faded out.

But what happens when that same lead returns to your site months later, ready to re-engage?

Most teams wouldn’t even notice.

That’s where AI chat steps in as your always-on, second-chance catcher. 

Instead of relying on reps to comb through CRM records or guess who’s who, your AI chat recognizes closed-lost accounts the moment they land. 

It can trigger a personalized message based on previous deal history, welcoming them back, referencing past conversations, or offering help with next steps.

With Warmly, this becomes a fully automated play. 

Here’s an example of a workflow that automatically adds Sales Leaders visiting our site to Outreach campaigns ⤵️

The platform syncs directly with your CRM (like HubSpot or Salesforce) and monitors for visits from known closed-lost leads. 

When one appears, it not only tailors the chat greeting but also alerts the original rep via Slack, giving them a heads-up to jump in live or follow up with perfect timing.

Instead of losing these leads all over again, AI chat turns quiet re-visits into a reactivated pipeline with no form fill or manual tracking required.

3. Warming up leads through contextual, on-brand conversations

High-intent leads don’t want to be “captured.” They want to be understood.

And yet, most companies still rely on rigid forms or generic chatbots that ignore who’s actually on the page. 

Same fields. Same questions. No context. No personality.

AI chat changes that experience completely.

Instead of pushing a cold form, it starts a warm, brand-aligned conversation. 

The chat adjusts in real-time to each visitor’s journey, whether they’re exploring features for the first time, coming back after a few weeks, or navigating your pricing page. 

It picks up on those signals and responds in a way that feels helpful, not pushy.

Warmly lets you train its AI Chat to speak your language, tone, voice, product positioning, and the whole package. 

That means every interaction sounds like it’s coming from your team, not some third-party script. 

And because it feels more human, leads are far more likely to open up, share real intent, and stick around.

This creates the ideal setup for warming up cold or curious visitors, turning casual browsing into engaged dialogue. 

And when you pair this with Warmly’s website visitor identification and intent enrichment, your reps don’t just see a name and title. They see buying signals, past activity, and what the lead actually cares about.

It’s trust-building at scale. And it makes every follow-up easier, more relevant, and way more likely to convert.

4. Booking meetings

Every sales team wants more meetings, but the handoff from chat to calendar is where a lot of intent slips through the cracks.

Think about the typical flow: a visitor is interested, the chatbot offers help, and… they’re told to “expect a follow-up soon.” 

That’s a recipe for no-shows and lost momentum.

AI chat solves that by making scheduling instant and frictionless.

Once a lead is qualified or shows intent, whether through their responses or their behavior on-site, the chat can offer available meeting times right then and there. 

No back-and-forth. No separate email thread. 

Just “Let’s get something on the calendar,” followed by real-time options pulled from your reps’ calendars.

With Warmly, this experience is smooth and tailored. 

The AI knows when someone is demo-ready based on intent signals and can offer the meeting prompt at the right moment in the conversation. 

It even works after hours, turning late-night visits into booked calls your reps will wake up to.

More meetings. Less drop-off. No gatekeeping.

5. Instant routing to sales reps

AI chat is powerful, but sometimes, what a lead really needs is a real person.

That’s why the best chat experiences don’t stop at automation, allowing collaboration, too. 

When a high-intent prospect is ready to talk, AI chat should know when to step back and loop in a rep immediately.

Instead of letting that interest cool off with a “we’ll be in touch,” instant routing brings a human into the conversation right then and there, when the lead is most engaged.

With Warmly, this handoff happens seamlessly. 

The AI Copilot monitors live chat sessions, detects high-value signals, and pings the right rep via Slack or email. 

That rep can jump in directly, continuing the chat in real-time, or following up minutes later with full context already in place.

Moreover, Warmly also enables reps to smoothly transition to video calls straight from the platform, allowing them to engage extra valuable leads in a more impactful and personal way.

6. Product recommendations and guided selling

Not every visitor knows exactly what they’re looking for, and that’s where AI chat can become a true sales assistant.

By analyzing on-site behavior and responses in the conversation, AI chat can suggest the right solution, feature, or content in real-time. 

It can guide visitors toward the best-fit product based on their role, goals, or stage in the buying journey without making them dig through menus or wait for a rep.

Think of it as guided selling, but scalable. 

Instead of showing everyone the same path, each visitor gets a tailored experience that feels consultative and not salesy.

This is especially valuable for teams with multiple offerings, pricing tiers, or complex products. 

Whether it’s pointing someone to a relevant use case, recommending a plan, or offering a targeted demo based on their answers, AI chat makes it easy for prospects to discover the right next step without the friction.

Since you can train it on the same content you’ve used to train your reps, Warmly’s AI Chat can tackle this for you as well.

The chatbot can provide contextual and relevant help and suggestions, ranging from explaining your pricing model to offering a case study or playbook, depending on the lead’s intent level, previous interactions, questions, etc.

The result? Faster decisions, better product-fit conversations, and more confident buyers.

7. Handling FAQs and reducing drop-off

Before a lead is ready to book a meeting, they often have a few simple questions:

“Do you integrate with Salesforce?”

“How does pricing work?”

“Is there a free trial?”

If they can’t find an answer fast, most will bounce - or worse, go looking elsewhere.

AI chat solves this by instantly handling FAQs in the flow of conversation. 

Because it can be trained on your data, the chatbot will deliver clear, accurate answers right when they’re needed, instead of sending visitors to a help centre or waiting for a rep to respond.

That keeps the momentum going and reduces the chances of losing a good lead over something minor.

And when a question is too specific or signals higher intent, the chat can escalate to a rep or offer to schedule time, so there are no dead ends.

8. Cart assistance and conversion nudges

Even the most interested buyers get cold feet.

They browse your product, click into pricing, maybe even add something to their cart, and then leave. 

It’s not always because they’re not interested. Sometimes they just need a little reassurance, a quick answer, or a timely nudge to keep going.

That’s where AI chat shines.

For SaaS teams, this could mean nudging a visitor who’s lingering on the pricing page with a helpful breakdown or inviting them to book a demo. 

For e-commerce brands, it could mean recognizing cart abandonment patterns, offering a limited-time promo, or suggesting the right product variant based on browsing behavior.

AI chat detects these micro-moments - like exit intent, extended idle time, or return visits - and responds instantly with relevant, on-brand messages. 

It might offer help, remind someone about their cart, answer a lingering question, or showcase a customer testimonial that reinforces trust.

These nudges don’t feel pushy because they’re contextual. They meet the user where they are, with just enough information to reduce hesitation and drive action.

Whether you're selling a subscription or a physical product, these small, well-timed interactions add up to more conversions and fewer missed opportunities.

How to build & deploy a lead generation AI chatbot that will work for you

A good AI chatbot is not supposed to just sit on your site looking fancy.

It should work with your entire GTM motion, making it better and more efficient.

If you want to build one that’s perfectly tailored to your organization and actually drives leads (instead of annoying visitors), here’s a clear, no-fluff roadmap to get it right:

1. Start with your goal, not the tool

Before jumping into setup, get specific:

Are you trying to qualify leads? Book demos? Re-engage lost deals?

Your objective will shape the tone, flow, and integrations you’ll need from your chatbot, so define it upfront.

2. Choose a chatbot that fits your stack and workflow

Whether you're using a no-code builder or a more advanced AI platform, pick a solution that plays nicely with your CRM, scheduling tools, and outbound systems. 

Seamless integrations are key, especially for routing leads, syncing data, and triggering follow-ups without manual steps.

Pro tip: If your team is using Warmly, this means you’ll get deep integrations with HubSpot, Salesforce, Slack, etc., from day one, with no extra dev work required.

3. Train it to speak your language

Generic chatbots don’t convert. Ones that sound like your team does.

Upload your key messaging, tone of voice, and positioning assets so your AI can reflect your brand in every conversation. 

This includes how you describe your product, how you respond to common objections, and how you ask qualifying questions.

Warmly lets you fine-tune the AI with rep-level prompts, so each flow feels like a real, on-brand interaction, not a script.

4. Build your core flows based on intent

Structure your conversation flows around different levels of buyer intent.

• High-intent: Offer demos, book meetings, or loop in a rep
• Mid-intent: Share relevant content, case studies, or product recommendations
• Low-intent: Guide to resources or encourage newsletter sign-ups

Map out these paths before launch. 

Remember, you’re not just building a chat - you’re building mini lead funnels.

5. Connect it to real-time signals

The real power of AI chat is personalization. 

That means pulling in behavior signals, such as page visits, traffic source, ad campaign IDs, CRM data, and using them to adapt the chat experience on the fly.

Warmly, for example, uses Warm Intent Signals to recognize returning visitors, match them to ICP criteria, or spot when a closed-lost lead is back on your site, so the chatbot can respond with laser-focused messaging.

6. Test small, then scale

Don’t launch site-wide on day one. 

Start with key pages like your homepage, pricing, or demo landing page, and then monitor engagement, drop-off, and conversion rates.

Use A/B tests to optimize tone, prompts, CTAs, and chat flow length. 

Look at what drives booked meetings, not just conversations.

7. Set up real-time alerts and handoffs

Make sure high-value leads don’t get stuck in automation. 

Configure routing rules, Slack alerts, and live rep handoffs so your team can jump in when it matters most.

Even the best AI chats perform better when they work with your team - not in a silo.

8. Monitor performance and optimize

Track metrics like:

• Engagement rate.
• Qualified leads generated.
• Meetings booked.
• Drop-off points.

Refine your flows over time based on what’s working. 

AI chat isn’t set-and-forget; it’s a living part of your GTM motion, which changes and evolves over time.

AI chat x lead generation case study

Kandji, a fast-growing Apple device management platform, needed a way to engage high-intent website visitors without overwhelming its sales team. 

The solution? AI chat built for speed, context, and instant handoffs.

Just weeks after rolling out Warmly, Kandji’s reps booked two qualified meetings in under 8 minutes, all through live sessions triggered by AI.

Here’s how it worked:

1. A prospect landed on their site, and Warmly’s AI chat greeted them with a personalized message based on company and intent signals.
2. When the visitor responded, reps were instantly alerted via Slack.
3. Two separate sales reps jumped in, continued the conversation in real-time, and seamlessly booked meetings with qualified leads.

Because the AI was trained to reflect Kandji’s voice and messaging - and backed by real-time visitor data - it was able to start warm, relevant conversations that didn’t just gather info, but built trust.

This wasn’t just sales automation for the sake of it.

It was a fully integrated AI-human handoff that created real pipeline, fast.

Two booked meetings. Eight minutes. Zero manual chasing. That’s what AI chat can do when it’s working for your sales team.

FAQ

What is an AI chat?

An AI chat is a conversational tool powered by artificial intelligence that engages website visitors in real-time. 

It can answer questions, qualify leads, and guide users toward the next step, like booking a demo or talking to sales.

It’s different from traditional chatbots because of its ability to better understand context and learn from past interactions and your data.

What are the benefits of using an AI chat for lead generation?

AI chat helps qualify leads faster, reduces friction, and engages prospects 24/7. 

It also drives personalized conversations at scale, turning anonymous traffic into pipeline without needing a live rep on standby.

#3 What are the challenges of using an AI chat for lead generation?

Poorly configured AI chats can feel robotic or irrelevant if not aligned with your brand and GTM motion. 

Success depends on training the AI with the right messaging, setting up smart flows, and connecting it to real-time signals and sales tools.

Next steps: Turn traffic into qualified pipeline on autopilot

AI chat isn’t just another tool on your site.

It’s a frontline teammate that works 24/7, qualifies leads in real time, and helps your reps close faster with less manual effort. 

And when it’s built right, it doesn’t just improve conversion rates - it transforms how your entire GTM team operates.

The best part? You don’t need to start from scratch.

Warmly’s AI chat is built to plug into your existing motion, tuned to your brand, and designed to surface high-intent leads when it matters most. 

Whether you want to book more meetings, re-engage lost deals, or simply stop letting good traffic go to waste, it’s all doable with the right chat, built the right way.

Book a demo with our team to see how Warmly’s AI Chat can start driving pipeline from day one.

Read more

• AI Lead Generation: How to Use AI to Get More Leads in 2024 - Discover how to use AI to attract, qualify, and convert more leads without adding headcount.
• 10 Best AI Marketing Tools for B2B Teams [2025] - Explore the top AI tools helping B2B marketers drive smarter campaigns and better pipeline in 2025.
• AI Lead Scoring: What Is It & How To Do It Right In 2025? - Learn how to automate lead qualification with AI and focus your team on the prospects that actually convert.
• 10 Best AI Prospecting Tools & Software in 2025 [Reviewed] - A curated list of the most effective AI tools to streamline outbound and fill your pipeline faster.
• AI for Sales: Best Tools & Tips [2025] - See how modern sales teams are using AI to close deals faster, from chat to forecasting.
• How To Use AI In Account-Based Marketing [2025] - A practical guide to using AI to personalize, prioritize, and scale your ABM strategy.

AI for outbound sales is quietly transforming how teams fill their pipeline and book more meetings.

Instead of cold lists, random outreach, and endless guessing, reps now have smarter tools that tell them who to reach out to, when to do it, and what to say.

Simply put, using AI for outbound sales means you're not flying blind anymore. 

You’re using real data, smart predictions, and automation to do what used to take hours in mere minutes. 

But to get real results, you need to understand how AI fits into your outbound motion, what tools actually work, and what best practices will set you up for success.

That’s exactly what I’ll cover in this guide, keeping it simple, clear, and actionable.

Let’s begin!

How is AI used for outbound sales in 2025?

Salespeople are using AI to completely change how outbound sales work in 2025. 

Instead of spending hours building lists, guessing who to contact, or manually writing emails, AI is helping teams focus on what moves deals forward.

AI doesn’t replace the human side of sales. What it actually does is take care of all the heavy lifting behind the scenes. 

It analyzes massive amounts of data to spot patterns humans would easily miss and helps reps:

• Identify better prospects.
• Find the right timing.
• Craft stronger messaging.
• Automate repetitive tasks that slow them down.

As a result, you get more time spent on real conversations with qualified leads, and less time wasted on research, admin, or sending emails into the void.

By using AI this way, outbound sales teams can scale their efforts faster, personalize outreach at levels that were impossible before, and consistently fill their pipeline with higher-quality opportunities. 

What are the benefits of using AI in outbound sales?

The benefits of using AI in outbound sales are huge, primarily because it makes your salespeople far more effective and leaves them more time to focus on strategic tasks and converting hot leads. 

Here are some of the major advantages teams are seeing in 2025:

1. Smarter prospecting - AI analyzes huge data sets to help reps find the right accounts, contacts, and buying signals, so there are no more spray-and-pray lists.
2. Better timing - AI spots patterns that suggest when a lead is most likely to engage, so reps reach out at exactly the right moment.
3. Personalization at scale - Instead of generic emails, AI helps tailor outreach based on real insights, like job changes, company news, or recent activity.
4. Faster research - AI pulls in firmographic, technographic, and intent data automatically, so reps don’t waste hours on manual research.
5. Consistent follow-up - AI-powered sequences ensure leads don’t fall through the cracks, even when humans get busy.
6. Continuous optimization - AI learns from past performance to recommend what’s working and where to improve, making the entire outbound motion more efficient over time.

8 ways you can use AI for outbound sales

By now, it’s clear that AI isn’t just automating outbound sales. Instead, it’s completely changing how teams approach it, and for the better.

From finding better leads to personalizing outreach and staying on top of every opportunity, AI is reshaping each step of the process. 

Here are 8 specific ways teams are using AI right now to make outbound sales more efficient, targeted, and effective.

1. AI-powered ICP identification

First things first - outbound sales only work when you’re aiming at the right targets. 

And that starts with defining your ICP, which sounds simple, but is often where most teams get stuck.

In the past, building an ICP usually meant looking at basic firmographic data: company size, industry, and location. 

But AI takes this way further. 

Instead of just checking a few boxes, it analyzes real data from your existing customer base, which includes things like:

1. What technologies they’re using.
2. Their recent hiring trends.
3. Funding rounds and growth signals.
4. Website activity and intent signals.
5. Buying behaviors and sales cycle patterns.
6. Common job titles involved in deals.
7. And dozens of other data points you probably wouldn’t catch manually.

AI connects the dots between all these factors to uncover patterns that define who your best customers actually are, not just who you think they are. 

And once you have that data-backed ICP, you can train AI models to go out and find more companies that match those same characteristics.

That’s exactly where platforms like Warmly come in. 

Warmly’s AI-powered ICP identification uses machine learning to go far deeper than basic firmographics. 

It analyzes your current customers and closed deals, surfaces the hidden traits that drive success, and automatically builds highly-targeted prospect lists that mirror your top performers. 

This way, instead of building lists manually or guessing who fits, your outbound motion starts with laser focus, aimed directly at companies most likely to convert.

When you nail your ICP at this level, everything downstream, including prospecting, messaging, and outreach, becomes dramatically more effective. 

You’re not wasting time on bad-fit accounts. You’re starting conversations with companies that already look like your best wins.

2. Smarter prospecting and segmentation

Once you know exactly who your ideal customers are, the next challenge is finding them, and sorting them into the right buckets. 

This is where most outbound teams end up drowning in spreadsheets, enrichment tools, and endless list-building.

AI changes that completely. 

Instead of manually researching every account, AI scans massive amounts of real-time data to continuously surface new leads that match your ICP. 

But it doesn’t stop at just finding names. It evaluates dozens of live data signals to automatically score, rank, and segment prospects based on:

• Fit (how well they match your ICP).
• Intent (how likely they are to be in-market right now based on the signals they’re showing across web visits, ad engagement, social activity, etc.).
• Engagement (how they’re interacting with your brand or reps).

As a result, you’re not looking at one giant list anymore. 

You’re looking at a dynamic, prioritized pipeline where the hottest, highest-fit leads naturally float to the top. 

And this allows reps to understand exactly who to contact, in what order, and when.

This is one of Warmly’s biggest strengths. 

Warmly’s AI agents combine your ICP data with live real-time signals, including first-party, second-party, and third-party ones, to automatically build hyper-targeted lead segments. 

These segments update constantly as new signals come in, so your outbound lists are always fresh, focused, and prioritized.

No more static lists that go stale after a few weeks. No more reps spending hours cleaning spreadsheets. 

With AI-powered prospecting and segmentation, your outbound machine stays sharp and always aimed at the right targets, without the manual busywork.

3. Personalized outreach that actually resonates

Outbound sales lives or dies on how relevant your message feels to the person receiving it. 

But true personalization is hard. 

Most teams end up doing surface-level tweaks, like inserting a name or job title, and calling it “personalized.”

The reality? Buyers see right through that.

AI takes personalization to a completely different level. 

Instead of relying on generic templates, AI can pull from dozens of real data sources to build context for each prospect. 

These are things like:

1. Recent company news or funding announcements.
2. Product launches or hiring trends.
3. Social media activity or thought leadership posts.
4. Website visits and page views.
5. Shared connections or partnerships.
6. Competitor activity and market shifts, etc.

AI can process all of this in seconds - far faster than any rep could research manually - and generate personalized messaging that actually speaks to what’s happening in that account right now.

That’s where Warmly’s Orchestrator feature comes in. 

As prospects engage by visiting your site, clicking on ads, or showing other intent signals (e.g., comment on your LinkedIn posts, etc.) Warmly automatically sends hyper-personalized messages across email and LinkedIn. 

With it, you can also orchestrate follow-up and nurturing.

Namely, once a prospect enters a sequence, Warmly keeps monitoring engagement signals in real-time and adjusts the messaging and timing automatically. 

As contacts move through different stages of interest, Warmly keeps the conversation going at the right pace, ensuring no lead gets forgotten or ignored.

For example:

• If a prospect opens but doesn’t reply, Warmly can automatically schedule a softer second touch (e.g., include them in a retargeting ad campaign with a personalized offer).
• If someone clicks a link or visits your pricing page, it can trigger a more targeted follow-up right away (send a contextual chatbot message offering an interactive demo or other resources).
• If a lead stays cold for a while, it can pause outreach and re-engage them later when new signals show interest again.

Most importantly, Warmly considers at all times which contacts are already being sequenced, avoids duplicates, and ensures the right stakeholders get the right message at the right moment. 

This helps outbound teams scale highly-personalised outreach while still keeping every touchpoint relevant and well-timed.

4. Hyper-targeted ads powered by intent signals

Outbound doesn’t always start with an email or a call. 

Sometimes the best way to warm up cold prospects is to get in front of them before any direct outreach even happens, and this is where AI-powered ads come in.

Instead of blasting broad audiences with generic ads, AI uses real-time data to build highly targeted ad segments, looking into all kinds of signals, from keyword research to technographic and other relevant data.

These signals allow you to serve ads directly to prospects who are showing real signs of buying intent, even if they haven’t raised their hand yet. 

By the time your outbound email or call lands, they’ve already seen your messaging and brand, making cold outreach feel much warmer.

That’s exactly what Warmly enables with its Demand Gen Agent that tackles ad targeting. 

As leads engage with your site or show intent across the web, Warmly automatically builds lead segments and syncs them with your ad platforms. 

This allows you to run hyper-targeted campaigns across channels like LinkedIn or Google Ads, focusing spend only on accounts that are already showing buying signals.

5. Account multi-threading (finding all stakeholders)

In most B2B sales, there’s rarely just one decision-maker. 

Deals involve multiple people across different roles, from champions and blockers to legal, finance, and executive sponsors. 

The more people you can engage inside an account, the stronger your position becomes. 

But finding and reaching all those stakeholders manually? That’s time-consuming, and honestly, pretty painful.

AI solves this by automatically mapping accounts and identifying all relevant stakeholders based on:

1. Org charts and job titles.
2. Department structures.
3. Past deal patterns.
4. Public data and enrichment databases.
5. CRM data and buying committee behaviors.

Instead of reps having to dig through LinkedIn or cross-reference multiple databases, AI continuously scans and updates account maps as new contacts surface.

Warmly helps automate this exact process. 

Warmly connects to data sources like Apollo, Demandbase, ZoomInfo, or Warmly’s own database to automatically surface all key decision makers within high-intent accounts. 

As new signals appear, like a stakeholder changing roles or a new hire joining, Warmly updates your outreach lists and makes sure you're multithreading into every angle of the deal.

This way, you’re no longer relying on one person to carry the conversation forward. 

You’re building momentum across the entire buying team, increasing deal velocity and reducing the risk of stalls.

6. AI-powered social selling 

Outbound isn’t limited to inboxes anymore. 

A huge part of modern prospecting happens on social platforms like LinkedIn, where buyers share insights, engage with content, and leave valuable clues about what matters to them. 

The challenge? It takes a ton of manual time for reps to monitor posts, comment thoughtfully, and stay consistently visible.

AI helps automate and scale social selling without losing the personal touch. 

Instead of reps spending hours scrolling feeds, AI monitors your target accounts and contacts for activity, such as new posts, competitor mentions, industry conversations, or job changes, and flags the best opportunities to engage.

It can also suggest relevant, context-aware comments reps can leave, helping them participate in conversations naturally and build credibility before any outreach happens. 

Over time, this keeps your team visible, builds familiarity with your prospects, and warms up relationships long before the first cold email or call ever lands.

Warmly can help with this, too, as it tracks LinkedIn activity in real-time, including posts, likes, comments, and keyword mentions related to your industry. 

It automatically surfaces the right conversations to join, helps you build lead lists from real engagement, and can even trigger personalized email or LinkedIn outreach based on social activity, turning social engagement into warm outbound pipeline.

7. Guided selling and next-best-action recommendations

One of the hardest parts of outbound sales is knowing what to do next. 

Do you send another email? Try a LinkedIn message? Loop in a different stakeholder? 

Without clear signals, reps often fall back on gut feeling, and that’s where deals can stall.

AI helps remove the guesswork by analyzing all the data from previous outreach, engagement history, deal progress, and similar accounts, and then suggesting the next best action for each prospect. 

For example, AI can:

• Recommend which channel to use (email, LinkedIn, call, etc.).
• Suggest new stakeholders to involve.
• Propose message variations based on what’s worked with similar accounts.
• Identify the right time to follow up or pause.

This way, instead of every rep having to figure it out on their own, AI guides them through the process, helping keep deals moving and preventing leads from falling through the cracks.

Warmly’s Copilot agent is the perfect example of how AI can turn every rep into a top performer.

The AI assistant tells your team who to reach out to, why they’re showing interest, and even suggests what to say, eliminating the usual manual research and guesswork. 

The result is more relevant outreach, stronger engagement, and a lot less time wasted trying to figure out what comes next.

8. AI-enhanced cold calling

If you thought cold calling is dead, you’d be far from the truth.

Not only is cold calling alive and kicking, it’s also undergoing the transformation of a lifetime, with AI completely changing how teams approach it. 

Traditionally, reps had to dial blindly, rely on outdated lists, and manually track every conversation. 

The result? Low connect rates, inconsistent conversations, and a lot of wasted time.

AI makes cold calling far smarter and more efficient. 

Before the call even happens, AI can help build better call lists by analyzing real-time intent signals, job changes, and account activity, so reps are calling people who are actually far more likely to be open to a conversation.

Once the call starts, AI-powered tools can listen in real-time, analyzing speech patterns, objections, and tone of voice. 

Based on this, AI can suggest on-the-fly coaching tips, like which objection handling technique to use or when to ask a clarifying question, helping reps navigate tough conversations with more confidence.

And it doesn’t end there.

After the call, AI automatically transcribes, summarizes, and scores conversations, highlighting key moments, objections, and next steps. 

This makes it easier for managers to coach reps and helps the entire team learn what’s working and where adjustments are needed.

And this isn’t just theory - some sales teams are already using AI to handle full outbound calls end-to-end. 

In one real example shared on LinkedIn, an AI sales agent dialled 10 cold prospects, fully ran the conversations, and successfully booked a meeting, with the prospect not even realizing they were speaking to AI until halfway through.

As a result, you get much higher connection rates, better conversations, and a cold calling process that feels a lot less like guesswork and a lot more like a well-oiled system.

4 best AI-powered outbound sales tools in 2025

Of course, none of this works without the right tools behind it. 

The good news? There’s now a growing stack of AI-powered platforms built specifically to help sales teams scale outbound smarter, faster, and with a lot less manual work. 

Here are 4 standout tools that are leading the way in 2025.

1. Warmly - All-in-one intent-led outbound stack

Warmly is an end-to-end AI outbound platform built to handle the entire sales motion, from finding the right accounts to sequencing hyper-personalized outreach across email, LinkedIn, and ads. 

Instead of relying on static lists or basic firmographics, Warmly uses real-time signals, deep ICP modelling, and multi-channel engagement to help reps focus only on the leads most likely to convert.

Standout features

• AI-powered ICP identification - Automatically uncovers patterns in top customers and builds precision-targeted prospect lists.
• AI-powered outbound sequencing - Autonomous AI agents run email and LinkedIn outreach based on live activity signals, such as web visits, ad clicks, job changes, and more.
• Automatic stakeholder mapping - Finds and incorporates all decision-makers in target accounts.
• Signal-based ad targeting - Creates ad audiences based on live intent, warming up prospects ahead of outreach.
• Social signal tracking - Monitors LinkedIn posts, mentions, and competitor buzz for timely engagement clues.
• AI Copilot - Smart assistant that suggests exactly who to reach, why, and what to say.
• AI-powered nurture sequences - Adapts follow-up timing and messaging based on individual engagement.
• B2B prospecting database - Holds continuously updated and validated data on 250M+ contacts to improve prospecting efforts and enable better personalized outreach.

Pricing

Warmly offers a free forever plan that allows you to reveal up to 500 monthly visitors, set up ICP filters to quickly identify high-quality leads, and automate basic lead routing.

If you need more, there are three tiers to choose from:

1. Data Only: Starts at $599/mo when billed monthly or $5,000 when billed annually, lets you identify up to 5,000 monthly visitors, first-party intent signals, alerts, and access to Warmly’s B2B prospecting database.
2. Business: Starts at $19,000/year for up to 10,000 visitors or $45,000/year for up to 75,000 visitors, everything in Data Only, plus third and second-party signals, sales orchestration, AI Chat, and lead routing.
3. Enterprise: Custom pricing, custom number of visitors, everything in Business, plus custom signals and warm calling.

2. Chorus - AI-driven call analysis and real-time conversation intelligence

Chorus is part of the ZoomInfo platform.

It records and transcribes every sales call and meeting, then uses AI to analyze the conversation, including tone, objections, competitor mentions, and talk/listen ratios. 

It surfaces key moments and patterns to help sales teams understand what’s working, improve coaching, and close more deals over time 

Standout features

• Real-time transcription and recording - Automatically captures every conversation for review and analysis.
• AI-driven conversation analysis - Identifies call peaks, objections, and critical buyer signals.
• Coaching scorecards & snippet sharing - Enables managers to share winning call segments and provide targeted feedback.

Pricing

Just like with the rest of its products, ZoomInfo doesn’t disclose the actual price for Chorus.

You’ll have to contact its team for a quote.

3. Outreach.io - AI-powered multi-channel sequencing and workflow optimization

Outreach uses AI to power multi-channel sequences that adapt in real-time based on prospect engagement. 

It helps sales teams optimize cadences, recommend next steps, and deliver consistent outreach playbooks across email, phone, and social channels.

Standout features

• AI prospecting agent - This agent identifies potential leads, qualifies them based on predefined criteria, and reaches out to best-fit prospects through personalized messages. 
• Embedded call coaching - Offers suggestions during conversations to handle objections or shift tactics.
• Smart deal assist - Outreach predicts whether a deal will close with high accuracy rates and recommends actions to keep it on track.

Pricing

Outreach has five different product packages:

1. Engage: Includes email assistant, automations, CRM sync, templates, etc.
2. Call: Includes sales dialer, live sales monitoring, AI-powered call summary, etc.
3. Meet: Includes real-time call recording and transcription, AI-powered meeting assistant, automated summary and action items, etc.
4. Deal: Includes AI-powered deal assistant, deal health score, deal overview with activity history, etc.
5. Forecast: Includes AI projection, scenario planning, detailed dashboards, etc.

However, the platform doesn’t publish prices for any of its packages, so you’ll have to contact its sales team.

Moreover, each package has distinct pricing, meaning the costs can easily add up if you want to use several of Outreach’s products.

4. Apollo - AI-powered lead discovery and contact enrichment

Apollo combines AI-powered lead discovery, enrichment, and outbound automation in one platform. 

It helps sales teams find new ICP-fit leads, launch optimized outreach sequences, and automate follow-ups based on real-time engagement data.

Standout features

• AI-powered contact discovery - Finds new leads fitting your ICP using firmographic and intent signal data, leveraging its massive B2B database.
• Multichannel outreach - Lets you build automated outbound sequences across email and phone, using engagement signals and CRM data to personalize messaging and optimize sequence timing.
• Lead scoring and prioritization - Uses AI to score leads in real-time based on fit and intent signals, helping reps focus their outreach on the prospects most likely to turn into deals.

Pricing

Apollo has a free forever plan that includes 100 email and mobile phone finder credits, basic filters and prospecting, and two sequences.

If you need more, you can upgrade to one of three paid plans:

1. Basic: $59 per user per month.
2. Professional: $99 per user per month.
3. Organization: $149 per user per month.

Best AI-powered outbound sales tools comparison table

AI x outbound sales case study

And now, let’s look at a real-world example of how AI can boost outbound sales strategies.

D2D Experts, a sales consultancy, used Warmly to completely transform how their outbound team works. 

Before, reps were relying on cold lists, had limited data on who was visiting their site, and often reached out too late, if at all.

With Warmly’s AI-powered outbound features, they were able to completely flip that:

• Real-time website visitor tracking identified who was showing interest, allowing reps to instantly target leads that were already warm.
• Slack notifications and lead routing alerted reps the moment high-intent prospects landed on the site, triggering immediate outbound calls while the lead was still active.
• AI-powered email sequences replaced standard outbound cadences, booking ~20 meetings per month while sending 10x fewer emails.
• AI-driven lead insights and prioritization gave reps context before reaching out, making cold calls far more relevant and effective.

The result?

Outbound call answer rates jumped from 5–10% to 30–40% simply by calling at the right time, based on real-time signals.

In just 12 days, this outbound-focused approach generated $80,000 in revenue, fueled by speed, data-driven targeting, and AI-personalized outreach at exactly the right moment.

FAQ

Can I use AI to personalize my message for outbound sales?

Yes, you can use AI to personalize your message for outbound sales! AI can pull data from multiple sources like job changes, company news, and buying signals to personalize your outreach at scale. 

It helps you tailor messages to each prospect’s situation without spending hours on manual research.

How can I measure the effectiveness of AI in my outbound sales?

Track key metrics like reply rates, meetings booked, conversion rates, and sales cycle length. 

If AI is working, you should see better targeting, faster responses, and more qualified conversations.

What are the things that AI still cannot do in outbound sales?

AI can’t fully replace human relationship-building, handle complex negotiations, or read emotional nuance during live conversations. 

It’s a powerful assistant, but your reps still need to drive real connections and close deals.

Next steps: Let AI do the heavy lifting in your outbound sales

AI isn’t here to replace sales reps - it’s here to finally make outbound sales work the way it should. 

From smarter prospecting and real-time signals to personalized outreach and better timing, AI takes the guesswork out of outbound and helps your team focus on having better conversations with the right people at the right time.

If you're ready to see how AI can transform your own outbound sales motion, Warmly gives you everything you need - ICP targeting, intent signals, multi-channel sequencing, and real-time lead engagement - all in one platform.

Want to see it in action?

Book a demo and let our team show you how Warmly can scale and optimize your outbound sales in no time.

Read more

• What is Warm Outbound? Definition, Benefits & Best Practices - Learn how warm outbound works, why it outperforms traditional cold outreach, and how to build an effective warm outbound system for your sales team.
• 10 Real-World AI In Sales Examples In 2025 [Reviewed] - See how real companies are using AI right now to drive pipeline, improve sales productivity, and close more deals in 2025.
• Outbound Sales Automation: Use Cases, Best Practices & Software - Discover how sales teams automate outbound with AI, from prospecting to follow-ups, and the best tools that power it all.
• AI for Sales: Best Tools & Tips [2025] - Explore the top AI-powered sales tools and actionable tips for using them to boost conversions and sales efficiency this year.
• 10 Best AI Sales Calls Tools & Software in 2025 [Reviewed] - A detailed look at the top AI-powered sales call tools helping reps handle objections, improve call performance, and win more conversations.
• 10 Best AI SDR Agents to Win More Deals in 2025 - Meet the top AI SDR agents that handle prospecting, outreach, and lead qualification, so your team can focus on closing deals.

AI for marketing is transforming how teams attract, engage, and convert customers in 2025.

Instead of relying on gut instinct or outdated playbooks, marketers now use AI to analyze data, personalize campaigns, predict buyer behavior, and optimize performance - all in real-time.

The challenge? The AI landscape is crowded, and not every tool delivers meaningful results.

That’s where this guide comes in to save the day.

In it, I’ll break down exactly how AI for marketing works, the best practices driving real outcomes, and the top AI marketing software to consider, so you can run smarter campaigns, maximize ROI, and stay ahead of the curve.

How is AI used for marketing in 2025?

Marketers are using AI for marketing to transform how campaigns are planned, executed, and optimized across the full customer journey.

Instead of relying on manual processes or educated guesses, AI uses real-time data, predictive insights, and agentic automation to help teams make better decisions at every stage.

Today, AI for marketing powers everything from audience targeting and content creation to personalized messaging, pricing adjustments, and real-time campaign optimization. 

As a result, it allows teams to anticipate customer behavior, identify high-intent leads, and coordinate campaigns across multiple channels with much greater precision.

But AI isn’t just about saving time on repetitive tasks. 

It’s already becoming a vital partner in shaping strategy, improving execution, and driving real results - whether that’s getting more leads, keeping customers engaged, or growing revenue.

What are the benefits of using AI in marketing?

The benefits of using AI in marketing are numerous, and they are transforming how teams operate, make decisions, and drive growth from the ground up. 

Here are some of the things AI brings to the table:

• Smarter targeting - AI analyzes huge datasets to segment audiences based on real behaviors, preferences, and intent, which goes far beyond traditional demographics.
• Hyper-personalization at scale - AI dynamically tailors content, offers, and messaging for each prospect or customer based on their actions and profile.
• Real-time decision making - Instead of waiting for reports after something has already happened, AI continuously monitors performance and optimizes campaigns on the fly.
• Increased efficiency and automation - Repetitive tasks like lead scoring, email sequencing, and ad placement can run automatically, freeing teams to focus on strategy.
• Predictive insights - AI models help forecast customer behavior, identify churn risks, and surface high-intent leads early.
• Improved ROI and budget allocation - AI helps allocate spend to the highest-performing channels and tactics based on live performance data.
• Better creative output - AI assists with copywriting, visual design, A/B testing variations, and creative optimization, allowing teams to test faster and produce more.

10 ways that you can use AI for marketing

We’ve already seen how AI is reshaping how marketers plan, optimize, and run campaigns, but what does that actually look like in practice?

Namely, AI for marketing isn’t one single tool or feature. 

It’s a growing set of capabilities that help teams target the right audiences, personalize outreach, optimize performance, and drive better results at every stage of the funnel.

Here’s a closer look at how AI is being applied across the marketing funnel, powering everything from smarter targeting to real-time personalization and more efficient pipeline growth.

1. AI-powered ICP building 

One of the most important - and most overlooked - areas where AI is changing marketing is how companies define who they’re actually selling to.

Traditionally, building an ICP meant pulling basic firmographic data like company size, industry, and location. 

But that often leaves out the real buying signals: what technologies they use, how fast they’re growing, what their recent hiring trends are, or how closely they actually resemble your best customers.

AI-powered ICP building goes much deeper than that. 

Instead of just checking off surface-level attributes, AI analyzes dozens of data points, such as intent signals, enrichment data, CRM history, job postings, funding rounds, and website behavior to create a far more complete profile of your true best-fit customers.

This level of depth helps marketers:

• Focus their targeting on accounts most likely to convert from the get-go.
• Build much more relevant ad audiences and outreach lists.
• Eliminate wasted spend on poor-fit accounts.
• Align sales and marketing around the same high-potential opportunities.

This is where tools like Warmly step in. 

Warmly’s AI Marketing Ops agent comes with a sophisticated ICP engine that pulls together firmographic, technographic, behavioral, and intent-based signals to automatically define your ideal profile, adjusting it on the fly as relevant factors change.

But it doesn’t stop at that. 

Once the profile is built, Warmly’s AI agent continuously identifies new prospects that match those exact characteristics, so you’re always feeding your pipeline with the right accounts.

2. Intent-based lead scoring and qualification

Finding the right accounts is only step one.

Next, you need to know when they’re ready to engage. And that’s where intent-based lead scoring comes in.

Instead of treating every lead the same, AI looks at real-time behavior signals, such as: 

• Website visits.
• Pricing page views.
• Content downloads.
• Ad interactions.
• Social engagement.
• And dozens of other micro-signals that indicate where a prospect is in their buying journey.

AI continuously monitors and analyzes all these signals, scoring leads dynamically as new data comes in. 

The result? Marketing and sales teams can prioritize leads showing the strongest intent, and not just the ones that filled out a form.

With intent-based scoring, teams can:

• Surface hot leads in real-time.
• Trigger the right initial outreach and follow-up sequences automatically.
• Shorten sales cycles by catching buyers while interest is high.
• Reduce time wasted on low-intent or unqualified prospects.

This is where Warmly makes a real impact. 

By combining CRM data, data from 10+ data enrichment providers, and live buyer signals, Warmly builds continuously updated lead scores that reflect true buyer readiness. 

Hot leads are automatically routed to sales with Slack alerts and automatic CRM syncs, allowing your team to engage at exactly the right moment.

Instead of playing catch-up, you’re now one step ahead of your buyers, which is exactly where you want to be.

3. Hyper-personalized offers - in real-time

Even the best targeting and lead scoring won’t move the needle if your message feels generic. 

That’s why personalization is where AI becomes a true differentiator.

Real-time personalization means adjusting your messaging, offers, and website experience on the fly based on who’s visiting, where they came from, and what they’re doing right now. 

AI processes behavioral signals, traffic sources, firmographic data, and persona insights to tailor the experience in milliseconds.

With real-time personalization, teams can:

• Show custom offers to different audience segments.
• Adjust messaging based on traffic source or referral partner.
• Personalize CTAs for returning vs. first-time visitors.
• Serve dynamic content depending on the buying stage or intent level.

Warmly’s Demand Gen agent brings this capability to life. 

As soon as a visitor hits your site, Warmly identifies their persona, buying intent, and traffic source and then serves personalized offers, messages, or CTAs that match that visitor’s likelihood to convert. 

Whether it’s a special incentive for a high-intent lead or a softer educational CTA for an early-stage visitor, every interaction is tailored in real-time.

As a result, you get more engagement, higher conversion rates, and a far more relevant buyer experience without the need for complex manual segmentation.

4. Signal-based ad targeting

Ad targeting used to be mostly guesswork: pick some firmographic filters, add a few interests, and hope your ads land in front of the right people. 

AI has changed that landscape completely.

Signal-based ad targeting taps into real-time behavioral and intent signals to build highly dynamic, hyper-relevant ad audiences. 

So, instead of relying only on static lists, AI continuously updates audience segments based on who’s showing buying signals right now - whether that’s:

1. Recent site visits - especially visits to high-intent pages like pricing.
2. Content engagement.
3. Social media activity (e.g., engagement with your or competitors’ posts).

With signal-based targeting, teams can:

• Build dynamic retargeting lists that refresh automatically.
• Focus ad spend on accounts actively showing interest.
• Minimize wasted impressions on low-intent or out-of-market prospects.

Warmly makes this fully operational by automatically syncing onsite and offsite behavioral signals to your ad platforms. 

As prospects engage across your channels, Warmly builds continuously updated lead segments and pushes them directly to ad networks like LinkedIn, Facebook, and Google. 

This way, your ads are always aimed at the highest-intent prospects, and not outdated static lists, leading to better ad performance, higher CTRs, and much more efficient ad spend.

5. AI-powered lead workflows and nurture sequences

Even with the right leads and targeting, timing is everything. 

Not every buyer is ready to convert the moment they engage, and that’s where AI-powered workflows step in.

Instead of forcing leads into rigid nurture tracks, AI monitors behavior in real-time and dynamically adapts each lead’s journey based on their level of intent, recent activity, and engagement patterns. 

As a result, every prospect receives the right touchpoint at the right time, be that email, ads, chat, or a live rep.

Warmly’s AI-powered Orchestrator handles this entire process end-to-end. 

As leads interact with your content, site, and ads, Warmly detects their intent level and routes them into tailored email and/or LinkedIn campaigns. 

Each message or connection request the Orchestrator sends will be perfectly tailored to every lead’s journey stage, previous interactions, and behavioral signals, making your messaging more relevant and personalized across levels.

This keeps your pipeline constantly moving, ensuring no opportunity gets lost, and every lead is always being guided toward conversion.

6. Content creation

Creating high-quality content has always been one of the biggest resource drains for marketing teams. 

Blog posts, ad copy, landing pages, email sequences - it all adds up fast. 

Generative AI is now taking a massive load off by helping teams produce content faster, at scale, without sacrificing quality.

Generative AI models can draft everything from long-form articles to email subject lines, product descriptions, and social media posts, all based on your inputs, audience data, and desired tone. 

Instead of starting from scratch, marketers get strong first drafts that can be reviewed, edited, and optimized by humans, allowing teams to:

• Dramatically speed up content production cycles.
• Generate multiple variations for A/B testing.
• Personalize messaging for different segments or personas.

Many teams now use AI writing assistants like Jasper, Copy.ai, or ChatGPT to support their content engines. 

And while cannot AI fully replace human creativity, it acts as a force multiplier, helping teams keep up with the growing demand for high-volume, high-quality content across every channel.

7. Chatbots and conversational AI

AI-powered chat is no longer limited to simple, scripted bots that frustrate users with dead-end answers. 

Conversational AI has already become a key part of marketing, turning your website into a fully functioning, always-on sales assistant that can engage, qualify, and convert visitors in real-time.

Namely, modern AI chat systems go beyond just answering FAQs. 

They can now analyze visitor behavior, adapt to each conversation, personalize responses, and then guide prospects to the right next step, such as booking a meeting, accessing content, or speaking with sales.

This is where Warmly’s AI Chat takes things even further.

Unlike generic chatbots, Warmly’s AI chat is trained on your brand’s unique messaging and product positioning - the same content you’d use to train your sales team. 

Moreover, it recognizes high-intent visitors based on intent signals and personalizes conversations accordingly. 

For example:

• If an ICP lead lands on your site, Warmly can immediately surface a demo offer.
• If a previously lost opportunity returns, the chat greets them with a “welcome back” sequence.
• If a decision-maker changes jobs and visits your site, Warmly triggers outreach automatically.

The result? Smarter conversations, better visitor experiences, and more meetings booked, all while keeping your messaging fully on-brand and aligned with your GTM strategy.

9. Dynamic pricing

Pricing has always been one of the trickiest levers in marketing.

Set it too high, and you lose deals. Go too low, and you leave revenue on the table. 

AI-powered dynamic pricing helps companies strike the right balance by continuously analyzing supply, demand, competition, customer segments, and external market signals to adjust prices in real-time.

Dynamic pricing allows businesses to:

• Adjust pricing based on customer segment or buying behavior.
• Respond quickly to competitor price changes or market shifts.
• Maximize revenue during periods of high demand.
• Offer personalized pricing models to different customer tiers.

While dynamic pricing has been widely adopted in industries like airlines, e-commerce, and ride-sharing, it’s becoming increasingly relevant for SaaS, subscription businesses, and enterprise sales as well. 

AI models factor in historical deal sizes, customer budgets, product usage patterns, and seasonality to recommend optimized pricing strategies.

For B2B marketers, dynamic pricing powered by AI can open new doors for packaging flexibility, mid-funnel conversion optimization, and even upsell or renewal strategies, helping companies stay competitive while protecting margins.

10. Improved marketing strategy and research

Most AI for marketing conversations focus on campaign execution, such as targeting, personalization, and lead scoring. 

But one of the most powerful (and still underutilized) applications of AI sits much earlier: marketing strategy and research.

AI can analyze massive amounts of qualitative and unstructured data - the kinds of inputs that marketers traditionally have to dig through manually for weeks, such as:

• Past sales conversations and call transcripts.
• Customer support chats.
• CRM notes and pipeline activity.
• Internal Slack discussions and deal reviews.
• Product documentation and training materials.
• Marketing collateral and website copy.

By processing these diverse data sources, AI surfaces patterns that help refine ICP definitions, sharpen positioning, uncover customer pain points, and even guide hyper-targeted keyword research.

One marketer shared on LinkedIn that they’re using a custom GPT-powered “business brain” that ingests real customer conversations, internal strategy sessions, and product materials, allowing them to refine ICPs, validate messaging, and build GTM strategies that are tightly grounded in what customers actually say and need.

The result? Smarter positioning, faster research cycles, and GTM strategies built directly from live customer data instead of assumptions.

4 best AI-powered marketing tools in 2025

So, we covered how AI is transforming nearly every part of marketing - from targeting and personalization to content creation and research. 

But pulling it off requires the right tools. 

Here are some of the best AI-powered tools helping teams put these strategies into action in 2025.

1. Warmly - Full-funnel AI orchestration 

Warmly is an AI-powered marketing platform built for modern GTM teams. 

It helps marketing and sales identify ICP-fit prospects, track real-time intent signals, and automatically trigger the right outreach, ads, or offers based on each buyer’s behavior, turning engagement data into pipeline, without the manual busywork.

Standout features

• AI marketing agents - AI agents that autonomously coordinate lead qualification, segmentation, and personalized outreach
• Real-time ICP matching - Continuously identifies and surfaces new prospects that fit your evolving ICP.
• Seamless Slack/CRM alerts - Instantly routes hot leads to sales with automated real-time notifications.
• Signal-based ad audience sync - Builds and updates ad audiences dynamically based on live buyer signals.
• AI Chat - Automatically engages, qualifies, and pushes leads further down the funnel, ensuring that each interaction is personalized, contextual, relevant, and on-brand.

Pricing

Warmly offers a free forever plan that allows you to reveal up to 500 monthly visitors, set up ICP filters to quickly identify high-quality leads, and automate basic lead routing.

If you need more, there are three tiers to choose from:

1. Data Only: Starts at $599/mo when billed monthly or $5,000 when billed annually, lets you identify up to 5,000 monthly visitors, first-party intent signals, alerts, and access to Warmly’s B2B prospecting database.
2. Business: Starts at $19,000/year for up to 10,000 visitors or $45,000/year for up to 75,000 visitors, everything in Data Only, plus third and second-party signals, sales orchestration, AI Chat, and lead routing.
3. Enterprise: Custom pricing, custom number of visitors, everything in Business, plus custom signals and warm calling.

2. Writesonic - Flexible content creation & SEO integration

Writesonic is an AI-driven content and SEO platform that supports everything from blog posts and ad copy to landing pages and social content. 

With multi-model support (GPT-4, Claude), brand voice settings, and real-time SERP intelligence via Surfer SEO integration, it lets you create more strategic and efficient content workflows.

Standout features

• AI SEO agent integration - Analyzes SERP data from Ahrefs and Search Console to shape content strategy.
• Brand voice memory - Learns and applies tone settings across all outputs.
• Content repurposing & editing tools - Resizes blog posts into tweets, emails, video scripts, or paraphrased versions.

Pricing

Writesonic has as many as six different pricing tiers:

1. Basic: $20/month, includes one user, one project, AI article writer, 10 AI Agent generations/month, 5 articles/month, etc.
2. Lite: $49/month, includes everything in Basic but with higher usage limits.
3. Standard: $99/month, includes everything in Lite with higher usage limits, plus brand presence tracking, automatic fixes using AI in site audit, etc.
4. Professional: $249/month, includes everything in Standard with higher usage limits, plus API access, access to ChatGPT 4, etc.
5. Advanced: $499/month, includes everything in Professional with higher usage limits, plus user management, project scaling, etc.
6. Enterprise: Starting from $1,499/mo, annual plan only, includes everything in Advanced with higher usage limits, plus advanced Generative Engine Optimization (GEO), SSO & enterprise-grade security, custom training, etc.

3. Anyword - Data-driven copy optimization across channels

Anyword is a marketing platform that uses AI to generate and optimize copy for ads, emails, landing pages, and social posts. 

It analyzes performance data to score variations, predict conversion impact, and continuously improve messaging across campaigns, helping marketing teams nail each copy and content strategy.

Standout features

• Predictive performance scoring - Rates copy effectiveness before launch.
• Audience-specific language generation - Tailors tone and messaging to target personas.
• Built-in A/B testing support - Quickly creates multiple versions for testing and iteration.

Pricing

Anyword has 4 pricing plans:

• Starter: $49/month, for individual users, includes 1 seat, 1 brand voice.
• Data-Driven: $99/mo, for smaller teams, includes 3 seats.
• Business: $499/mo, for teams looking for more customization and personalization options, also includes 3 seats.
• Enterprise: Custom pricing is available for teams that need custom-built AI tailored to their specific needs, with superior security options.

Each plan - except for Enterprise - offers a 7-day free trial.

4. Omneky - Automated ad creative generation & omnichannel campaign management

Omneky combines AI design generation with machine learning optimization to automate ad creation across multiple channels. 

It adapts creative assets in real time based on campaign data, audience engagement, and performance trends, boosting conversion rates and reducing wasted spend.

Standout features

• On-brand creative generation - AI-generated ad visuals designed to match your brand’s aesthetic.
• Omnichannel campaign launcher - Simultaneously manages ad campaigns across Meta, LinkedIn, Google, and TikTok.
• Creative optimization engine - Updates assets dynamically based on CTR, conversions, and platform performance.

Pricing

Omneky has three pricing plans:

1. Creative Generation Pro: $99/mo, includes AI product image and video generation, brand voice consistency with brand LLM, AI campaign brief, AI brand rules, etc.
2. Creative Generation Pro + Insights: $398/mo, includes everything in Creative Generation Pro, plus insights-powered automated ads, AI creative insights and recommendations (Meta only), insight-enhanced campaign briefs, etc.
3. Enterprise: Custom pricing, includes everything in Creative Generation Pro + Insights, plus omnichannel budget recommendations, omnichannel predictive analytics, custom fine-tuning of AI models based on 1P data, etc.

The first two plans come with a 7-day free trial.

AI x Marketing Case Study

To see how AI for marketing works in the real world, let’s look at how Kandji, a leading device management platform for Apple devices, is using Warmly’s AI capabilities to generate pipeline in real-time.

Kandji’s sales team leverages Warmly’s AI-powered chat to engage website visitors instantly. 

As prospects land on the site, Warmly’s AI identifies the visitor’s company, generates personalized opening messages based on firmographic data, and kicks off intelligent conversations, much before a rep gets involved.

In multiple instances, Kandji’s AI chat engaged visitors, collected context (such as device needs and pricing questions), and automatically notified the sales team via Slack when a conversation was ready for human handoff. 

From there, Kandji’s reps jumped into live chats directly from Slack, answered additional questions, and booked qualified meetings, often within minutes of initial engagement.

What’s especially important is that these wins happened just weeks after Kandji implemented Warmly, with minimal ramp-up time, allowing its team to get very tangible results from the get-go.

For Kandji, AI didn’t just save time. It added real, qualified pipeline by combining intelligent automation with real-time buyer signals.

What have AI’s challenges been in marketing?

AI’s challenges in marketing have been less about the technology itself and more about what it takes to apply it effectively. 

As teams adopt AI to drive targeting, personalization, and content, many are running into real-world issues around data quality, trust, privacy, and execution. 

Here’s where the friction tends to show up and what marketers need to solve as AI becomes core to how we operate.

1. Data quality, bias, and transparency

AI is only as good as the data you feed it. 

If the data is messy, outdated, or incomplete, you end up with bad predictions, off-target messaging, or audience segments that don’t make sense. 

Plus, a lot of AI models work like black boxes, meaning that they make decisions, but it’s not always clear how or why. 

That makes it harder for marketers to trust the outputs or adjust things when something feels off.

2. Privacy and regulations

As mentioned above, AI depends on data, and that creates big questions around privacy. 

Marketers need to carefully navigate strict privacy laws (like the EU’s AI Act and U.S. state rules) that control how personal information is collected and used. 

If companies mishandle data - even accidentally - it can lead to legal trouble and damage trust with customers.

3. Ethics and AI hype

As AI becomes more common, so does the pressure to use it responsibly. 

Some companies overpromise what their AI can actually do (aka "AI washing"), while others push out content or campaigns that cross ethical lines, like undisclosed AI-generated influencers or deepfakes. 

At the end of the day, audiences want honesty, transparency, and content that respects their trust.

4. Complexity and skill gaps

AI tools aren’t always simple to set up. 

They often require specialized knowledge, from managing data to connecting systems and fine-tuning models. 

Many marketing teams don’t have in-house AI experts, which can make implementation slow or frustrating, especially when older systems don’t easily connect with newer AI-powered tools.

5. Trusting AI’s decisions

Even when AI works well, people can be hesitant to fully rely on its recommendations, especially for sensitive things like pricing or targeting. 

Marketers still want some level of control and explanation behind why certain decisions are made. 

That’s why combining AI with human oversight tends to work best.

6. Company-wide buy-in

Rolling out AI isn’t just about buying a tool - it’s about getting everyone on board. 

Teams need to agree on goals, processes, and how success will be measured. 

Without clear leadership and alignment, many AI projects never move past the pilot phase.

How marketers can overcome these challenges

Next steps: Turn AI into your unfair advantage

AI isn’t a side project anymore, as it’s quickly becoming the backbone of how modern marketing actually gets done. 

From targeting and personalization to content, strategy, and pipeline generation, the teams that figure out how to use AI the right way aren’t just working faster - they’re building a real competitive advantage.

And the key isn’t chasing every shiny tool.

Real success is about putting the right systems in place that combine smart automation with human judgment, so your team can focus on the conversations and deals that actually move the needle.

Ready to see how AI can help your team generate pipeline, engage the right accounts, and scale smarter?

Book a demo with Warmly and see what’s possible today!

Read more

• Agentic AI For Marketing: Best Use Cases & Software In 2025 - Discover how agentic AI is reshaping marketing workflows, driving smarter personalization, and unlocking new levels of automation.
• AI in B2B Marketing: How To Use It? [2025] - See how B2B teams are using AI to target the right buyers, personalize outreach, and build pipeline with more precision.
• AI Marketing Strategy: Top Use Cases and Tools - Breakdown of the most effective ways to use AI in your marketing strategy, plus the tools leading the way in 2025.
• 8 Examples of AI Marketing Automation in 2025 - Explore real-world AI marketing automation examples that show exactly how teams are scaling smarter across channels.
• AI Marketing Agents: Use Cases and Top Tools for 2025 - Learn how AI agents are taking over repetitive tasks, optimizing campaigns, and helping marketing teams focus on what moves pipeline.
• How To Use AI In Account-Based Marketing [2025] - See how AI is powering smarter ABM, from dynamic targeting to real-time personalization and account orchestration.
• 10 Real-World AI In Sales Examples In 2025 [Reviewed] - Dive into 10 concrete examples of how AI is transforming sales motions and driving more closed deals in 2025.
• 10 Best AI Tools for Advertising in 2025 [Reviewed] - Get the full breakdown of the best AI-powered ad tools helping teams optimize targeting, creative, and spend across platforms.

Account-based marketing (aka ABM) has always been about precision: right account, right message, right moment. 

But today, “right” isn’t good enough unless it’s also real-time, scalable, and smart. 

That’s where AI flips the game.

AI-powered ABM doesn’t just automate tasks. 

It helps sales and marketing teams zero in on high-value accounts, surface buying signals, personalize at scale, and adapt outreach based on live behavior, all without overburdening your team.

In this guide, I’ll break down exactly how to use AI in ABM to drive better engagement, more pipeline, and tighter sales-marketing alignment. 

From intent-driven targeting to full-funnel orchestration, this isn’t theory - it’s real-world execution. 

Let’s get into it!

How is AI being used in account-based marketing in 2025?

In 2025, AI has become the engine behind the most effective plays in ABM.

Namely, AI is helping GTM teams move from static lists and one-size-fits-all messaging to dynamic, data-driven account engagement. 

It’s not just about who to target, but when, how, and why. 

AI systems are analyzing intent signals, website behavior, CRM data, and social engagement to help teams spot opportunities earlier and tailor their moves in real time.

Instead of relying on gut feel or manual research, companies are now using AI to prioritize accounts, predict deal potential, personalize outreach at scale, and align marketing and sales around shared signals.

And while the tech might sound complex, the impact is simple: faster workflows, sharper focus, and better results.

Next, let’s look at why this shift matters, and the real benefits AI brings to modern ABM.

What are the benefits of using AI for ABM?

AI supercharges what ABM was always meant to do: engage the right accounts with the right message at exactly the right time.

But it does more than just enhance ABM. It also fixes the parts that often fall flat in traditional ABM strategies.

Here’s how:

1. Smarter account targeting

AI analyzes thousands of data points, such as firmographics, technographics, buyer intent, engagement signals, etc., to help you zero in on the accounts that are actually in-market. 

As a result, instead of static ICP lists, you get a dynamic view of who’s ready to buy, and when to engage.

2. Personalization at scale

Creating custom messaging for every account used to take hours, or you were doomed to generic “Hey {first name}” attempts at genuine personalization. 

With AI, you can auto-generate relevant, persona-specific emails, social content, and talking points based on account data and live signals without sacrificing quality or human tone.

3. Real-time prioritization

AI continuously monitors account behavior (email opens, site visits, social actions, CRM activity) to surface the warmest, most engaged accounts. 

This way, your team knows exactly who to focus on, meaning there’s no more chasing cold leads or missing active buyers.

4. Tighter sales and marketing alignment

AI breaks down silos by giving both teams a shared source of truth. 

Everyone works off the same signals, knows where an account stands, and can coordinate actions accordingly - from outbound messaging to deal support.

5. Increased efficiency and shorter sales cycles

AI eliminates manual busywork and accelerates everything from list building to campaign sequencing. 

As a result, reps spend more time on high-leverage actions, allowing deals to move through the funnel faster with fewer blockers.

Top 8 ways you can use AI for account-based marketing

Exploring the benefits of integrating AI into ABM strategies showed us clearly that the synergy between these two can revolutionize how businesses engage with high-value accounts. 

And now, it’s time to delve into eight practical applications of AI in ABM, ranging from more precise account prioritization to hyper-personalized outreach sequences and beyond.

1. Dynamic ICP discovery

At the heart of every successful ABM strategy lies a clear, accurate Ideal Customer Profile. 

Your ICP defines who you’re targeting, that is, companies with the right size, industry, tech stack, buying behavior, and pain points. 

It’s what keeps your marketing focused and ensures your sales team isn’t wasting cycles chasing poor-fit accounts.

But here’s the problem: most ICPs are built once and then left to collect dust. 

They’re based on surface-level firmographics and assumptions, not real-time buying behavior. 

And in fast-moving B2B markets, that’s not just inefficient - it’s costly.

This is where AI steps in.

AI doesn’t just help you define a more accurate ICP. It continuously refines it. 

By ingesting and analyzing large volumes of data across multiple dimensions (firmographics, technographics, historical conversion data, product usage, site behavior, job changes, etc.), AI can uncover the deeper traits that actually correlate with pipeline velocity and deal closure.

So, instead of targeting “SaaS companies with 50–200 employees,” AI might discover that your best accounts are VC-backed SaaS teams using Snowflake that recently hired a new head of ops and visited your pricing page twice in the last week. 

That’s the difference between a generic ICP and a dynamic, revenue-ready one.

This is exactly where platforms like Warmly shine. 

Its AI-powered ICP engine goes beyond the basics to uncover what truly makes your best customers convert, then finds more accounts just like them. 

It combines live person-level intent signals with enriched firmographic and CRM data to build a living, breathing ICP that updates in real time, helping you pinpoint who’s worth prioritizing right now.

For ABM teams, that means sharper targeting, better personalization, and far less wasted effort on accounts that were never a fit to begin with. 

It’s the foundation that makes every downstream ABM play, such as ads, outreach, and nurture, way more effective.

2. Accurate account prioritization

In ABM, timing is everything. 

You could have the perfect account that fits your ICP and the perfect message, and still get ignored simply because the buyer isn’t ready. 

That’s why intent data has become one of the most valuable tools in modern account-based marketing.

Intent signals help answer a critical question: who’s actively in the market right now?

Instead of relying on manual research or waiting for someone to fill out a form, AI can detect buying intent by tracking a wide range of behavioral signals across digital touchpoints. 

These include:

1. First-party signals like website visits, content downloads, and product usage.
2. Second-party signals, such as job changes or social engagement.
3. Third-party signals like keyword searches and competitor research across the web.

AI’s role here is to bring all that data together, processing thousands of micro-interactions in real-time, and turning it into actionable insight. 

It identifies patterns, scores engagement, and highlights when a specific account (or even an individual) shows signs of buying readiness. 

The result? You easily prioritize the right accounts and reach out when it matters, and not when it’s too early or too late.

Warmly, for example, monitors all these signals at the person level. 

Its platform tracks activity from across channels and enrichment sources (e.g., web behavior, job shifts, ad interactions, LinkedIn engagement, and more), then maps that activity back to individuals and accounts in your total addressable market.

And it’s not just about collecting signals. It’s about making them usable. 

Warmly’s system syncs high-intent leads directly into your CRM, automatically updates segments, and even notifies your team in real-time (via tools like Slack) when an account is heating up. 

That means your reps can take action immediately and with the right context in hand.

For ABM teams, this is a massive unlock. 

Instead of generic nurture tracks or cold outreach, you’re delivering targeted, relevant engagement precisely when buyers are most receptive. 

That’s how deals get accelerated and competitors get left behind.

3. Hyper-personalized content creation

Personalization is at the core of effective ABM. 

When you’re targeting high-value accounts, generic content simply doesn’t cut it. 

Decision-makers expect messaging and experiences that speak directly to their challenges, industry context, and role-specific goals.

AI makes this level of personalization possible at scale, and not just in one-off emails or ads, but across your entire content strategy.

With AI, marketers can generate personalized content for blogs, landing pages, product pages, and case studies based on account-level data and behavioral insights. 

For example, AI can dynamically tailor web copy based on a visitor’s company size or industry. 

A tech prospect from a mid-market SaaS company might see different use cases, testimonials, and CTAs than a healthcare enterprise executive, even though they’re on the same page.

Warmly’s DemandGen agent, for instance, makes sure to show personalized content or special offers to each account, based on their intent level, buyer journey stage, previous social engagement, web research intent, and more.

Blog posts and thought leadership can also be adapted with AI. 

Instead of creating one generic article, teams can spin up multiple tailored versions for different verticals or buyer personas in seconds, each optimized for the priorities and language of the target audience.

Most importantly, AI doesn’t just help with creation - it helps with relevance. 

By analyzing engagement data, AI can continuously test, optimize, and iterate content variations to understand what resonates best with each account.

The result? Content that feels specific, intentional, and valuable because it actually is. 

And in ABM, that’s what builds credibility, nurtures trust, and opens doors with the accounts that matter most.

4. Predictive account targeting

One of the most powerful applications of AI in ABM is its ability to predict which accounts are most likely to convert before they raise their hand.

Unlike intent monitoring, which reacts to observable behaviors (like website visits or ad clicks), predictive prioritization uses machine learning to forecast future actions.

It analyzes historical data, such as closed-won deals, deal speed, and buyer stage, and identifies patterns across firmographics, engagement levels, buying committee structures, and campaign touchpoints.

As a result, it allows ABM teams to get ahead of the curve. 

For example, if AI sees that high-converting accounts from your past share common traits, such as using a specific tech stack, having a head of RevOps, and engaging across multiple channels in a short time frame, it can flag similar accounts in your pipeline even before those behaviors fully emerge.

Instead of waiting for obvious buying signals, you can focus early outreach, personalized content, or sales development on accounts with a high likelihood to engage, giving you a competitive edge.

Predictive scoring also helps sales and marketing stay aligned. 

Everyone knows which accounts deserve attention now, which need nurturing, and which to deprioritize altogether, based not on gut feel, but on actual data-driven forecasts.

In short: while intent tells you who’s active, predictive AI tells you who’s next.

5. Automated lead-nurturing sequences

In ABM, long sales cycles are the norm, especially when you're targeting complex organizations with multiple stakeholders. 

That’s why effective lead nurturing is critical. 

It’s not just about staying top-of-mind. It’s about moving accounts forward with the right message at the right time, for the right person.

But here’s the catch: manually managing personalized nurture across dozens - or hundreds - of target accounts isn’t scalable. 

AI fixes that.

With AI, ABM teams can create intelligent, multi-channel nurture sequences that adjust automatically based on where an account is in the buyer’s journey. 

Instead of using static drip campaigns, AI sequences evolve in real-time, based on actions like email opens, page views, persona engagement, or even inactivity.

This is where Warmly’s AI SDR agents shine. 

They don’t just automate the follow-up - they orchestrate it. 

After a lead visits your site or downloads a resource, Warmly can initiate a tailored sequence via email or LinkedIn DMs, adapt messaging based on the individual’s role or behavior, and even pause or reroute sequences when someone becomes sales-ready.

For example:

1. If a target persona engages multiple times with mid-funnel content, Warmly’s AI SDR agents can escalate that lead to a human rep and alert the team in Slack.
2. If someone ghosts after early engagement, the AI can re-engage them weeks later with a refreshed message without reps having to lift a finger.

The best part? These nurture flows are always on. 

Your outreach doesn’t stop when a rep is busy or asleep, and your best-fit accounts never fall through the cracks.

With AI handling the heavy lifting, your team can focus on strategic conversations and closing, instead of chasing cold leads or repeating the same follow-up steps manually.

6. AI-powered chat engagement

In any kind of marketing - account-based included - first impressions matter, and they often happen on your website. 

When a target account visits a high-intent page like pricing, features, or a demo request, that moment is your best shot at engaging them while interest is high.

But the traditional approach of waiting for them to fill out a form or hoping a rep is online often falls short. 

That’s where AI-powered chatbots come in.

Today’s AI chat tools can recognize when someone from a high-value account is browsing your site and engage them instantly with personalized, relevant conversation starters. 

Unlike generic chatbots that stop at “How can I help you?”, AI-driven systems use real context, like company, role, behavior, and past activity to tailor the experience in real-time.

For example, if a known account visits your pricing page, the AI chat can reference their industry or use case and offer to connect them with a specialist.

If it’s a repeat visitor, it can skip the intro and ask if they’re ready to book time with sales.

Warmly’s AI SDR agents do this exceptionally well. 

They combine person-level de-anonymization with generative AI to create real-time conversations that match each prospect’s intent. 

These AI chatbots can book meetings directly, answer common questions, or route the visitor to the right rep without human intervention unless it’s needed.

This always-on engagement layer is a game-changer for ABM. 

You’re no longer relying on reps to catch leads in the moment. 

AI ensures that when your dream account lands on your site, someone’s always there to engage them intelligently and instantly.

7. Signal-based advertising

Traditional advertising casts a wide net, and in ABM, you want a laser. 

Every impression, click, and dollar should be aimed squarely at high-value accounts that actually matter.

That’s where AI-driven, signal-based advertising comes in.

Instead of building static ad audiences based on job titles or company size alone, AI allows you to create dynamic segments based on real-time behavior and buying signals. 

This means you’re not just targeting accounts that fit your ICP. Instead, you’re targeting those actively showing signs of intent.

For example:

1. If someone from a target account downloads a case study, AI can immediately move them into a custom ad audience that highlights next-step content (like a demo offer).
2. If an account starts researching competitors or engages with your product pages, AI can trigger personalized ad sequences that address their specific interests or pain points.
3. And if an account goes cold, they can be pulled from your ad audiences automatically, saving budget and preventing wasted impressions.

This level of precision is exactly what ABM teams need, and it’s where Warmly’s Demand Gen agent plays a valuable role. 

It combines real-time signal tracking with audience automation, syncing your warmest accounts into ad platforms like LinkedIn or Google Ads. 

That way, you’re always reaching the right people, at the right time, with the most relevant message.

In a market flooded with generic banners and retargeting overload, signal-based advertising cuts through the noise and connects your brand with real buyers, not just browsers.

8. Intelligent lead routing and notifications

Remember how I mentioned earlier that timing is everything in ABM?

Well, in ABM, timing and context aren’t just important for your prospects - they’re essential for your internal teams, too.

Once a high-value account starts engaging, the question becomes: Who on your team should act on this? And how fast can they do it?

AI-driven lead routing solves both problems. 

Instead of using rigid, rules-based systems, AI evaluates each lead in context, considering their persona, level of intent, stage in the journey, and historical behavior, and automatically routes them to the right rep or team, at the right moment.

For example:

1. If a mid-funnel operations lead from a strategic account visits your ROI calculator, AI can flag this as a hot lead and route it directly to a senior AE.
2. If a new visitor from a target account downloads a gated asset, AI might assign them to a BDR for personalized outreach.
3. If multiple stakeholders from the same company engage in a short window, AI can trigger coordinated follow-up across sales and marketing.

This isn't just about faster responses. It’s about smarter handoffs, better alignment, and less lead leakage.

Tools like Warmly enhance this by combining real-time signal monitoring with intelligent Slack, email, and CRM alerts. 

Reps get notified the moment someone from a key account engages, along with the context they need to respond in a relevant, personalized way.

In practice, this means no more “random acts of outreach” or siloed follow-up. 

AI ensures your team is always in sync with what’s happening on the buyer side, making your ABM motion feel cohesive, responsive, and human.

4 best AI-powered ABM tools on the market

With AI now driving the most effective ABM strategies, the right tech stack can make or break your execution. 

Below are four standout AI-powered ABM tools that help B2B teams identify, prioritize, and engage high-value accounts with precision, each bringing unique capabilities to the table.

1. Warmly - Real-time intent tracking and automated multichannel outreach

Warmly is an AI-powered ABM platform that helps B2B teams uncover, prioritize, and engage high-intent accounts through signal-based intelligence and agentic automation. 

It monitors 1st, 2nd, and 3rd-party buying signals at the person level, enabling marketing and sales to act in real time with personalized, channel-aware outreach. 

With a suite of AI agents, covering sales outreach, demand gen, and marketing, Warmly turns intent into action across your pipeline.

Standout features

• AI SDR agents - These automate email and LinkedIn outreach sequences based on signal strength, persona, and behavior.
• Demand Gen agent - Automatically builds audience segments and syncs them to ad platforms based on buying signals for hyper-targeted advertising.
• Dynamic ICP - Leverages AI to identify accounts matching your ICP based on granular insights that go far beyond firmographics, including behavior, intent, etc.
• Company and person-level de-anonymization - Identifies companies and specific individuals visiting your site and maps them to their roles and accounts.
• Signal-based scoring - Uses 1st, 2nd, and 3rd-party data (e.g., website visits, job changes, social activity, competitor research) to score and segment accounts in real time.
• Slack and CRM integration - Instantly alerts sales teams when key accounts engage, complete with context and suggested next steps.
• Intelligent lead routing - Automatically assigns leads to the right rep based on behavior, funnel stage, and fit.

Pricing

Warmly offers a free forever plan that allows you to reveal up to 500 monthly visitors, set up ICP filters to quickly identify high-quality leads, and automate basic lead routing.

If you need more, there are three tiers to choose from:

1. Data Only: Starts at $599/mo when billed monthly or $5,000 when billed annually, lets you identify up to 5,000 monthly visitors, first-party intent signals, alerts, and access to Warmly’s B2B prospecting database.
2. Business: Starts at $19,000/year for up to 10,000 visitors or $45,000/year for up to 75,000 visitors, everything in Data Only, plus third and second-party signals, sales orchestration, AI Chat, and lead routing.
3. Enterprise: Custom pricing, custom number of visitors, everything in Business, plus custom signals and warm calling.

2. 6sense - Predictive analytics and intent-based account prioritization

6sense is an AI-powered revenue platform that helps B2B teams uncover in-market accounts, predict buying behavior, and orchestrate multi-channel engagement. 

By combining intent data, predictive analytics, and account intelligence, it enables sales and marketing to focus on the accounts most likely to convert.

Standout features

• Granular intent data - Aggregates behavioral signals to identify buying intent across accounts.
• Predictive lead scoring - Ranks accounts based on likelihood to engage and convert.
• Intelligent workflows - Lets you automate various sales and marketing operations across channels.

Pricing

6sense has a free plan that provides 50 credits/month, Chrome Extension, list builder, sales alerts, and company and people search.

When it comes to its paid options, there are three to choose from:

1. Sales Intelligence + Data Credits + Predictive AI: The most comprehensive package, includes all of 6Sense’s features, such as predictive AI models, scores, and dashboards, sales Copilot, AI recommendations, company and contact insights, alerts, automated workflows, etc.
2. Sales Intelligence + Data Credits: Includes access to some features related to sales (e.g., sales Copilot, AI writer, etc.) and data (limited company and contact insights).
3. Sales Intelligence + Predictive AI: Also includes access to some features related to sales and some regarding predictive AI modules (e.g., predictive scoring and dashboards).

However, 6sense doesn’t disclose actual prices for any of the packages.

You’ll have to contact their team for a custom quote.

3. Demandbase - Comprehensive ABM orchestration and personalization

Demandbase is an end-to-end ABM platform that uses AI to unify account intelligence, personalize experiences, and drive coordinated engagement across sales and marketing. 

It empowers teams to target high-value accounts with precision by combining firmographic data, real-time behavior tracking, and AI-driven orchestration.

Standout features

• Account identification - Uses AI to discover and prioritize target accounts showing buying signals.
• Website personalization - Customizes web experiences based on account attributes and behaviors.
• ABM analytics - Tracks performance metrics to measure the impact of ABM campaigns.

Pricing

Demandbase doesn’t disclose its prices.

You’ll have to contact its sales to get a custom quote based on your business goals and needs.

4. RollWorks - Scalable ABM for growing B2B companies

RollWorks offers a scalable ABM solution for growing B2B teams, using AI to identify target accounts, activate cross-channel campaigns, and measure engagement. 

It’s designed to help marketers focus on accounts with the highest potential, even with limited resources or headcount.

Standout features

• Account targeting - Combines firmographic and intent data to pinpoint ideal accounts.
• Cross-channel engagement - Runs coordinated campaigns across display ads, social media, and email.
• High precision B2B advertising - RollWorks uses machine learning algorithms to optimize budgets, reach, frequency and engagement on the fly.

Pricing

RollWorks has two pricing tiers:

1. Account-Based Advertising: Includes precision targeting across all digital channels, custom audiences, etc.
2. Account-Based Marketing: Includes predictive buying signals, buyer insights, detailed analytics and key metrics tracking, etc.

   

However, RollWorks doesn’t publish prices for any of the packages, so you’ll have to speak to its team directly.

What are some of the challenges of incorporating AI into your ABM strategy?

While AI can dramatically enhance account-based marketing, integrating it into your strategy isn’t always plug-and-play. 

Many teams encounter roadblocks that can delay adoption or undermine ROI if not addressed early. 

Let’s look at some of the most common challenges:

1. Data readiness and quality

AI is only as good as the data it’s fed. 

If your CRM is messy, intent signals are incomplete, or account data is outdated, your AI models may generate inaccurate insights or poor prioritization. 

Ensuring clean, enriched, and unified data across systems is foundational for AI-driven ABM to work.

2. Complexity and integration

AI tools often need to integrate with CRMs, marketing automation platforms, ad systems, and sales workflows. 

Without tight integration, insights get lost in silos or require manual workarounds, defeating the purpose of automation. 

Teams need to assess whether their current sales and marketing tech stack is flexible and open enough to support real-time orchestration.

3. Over-personalization or “uncanny” messaging

AI can personalize content at scale, but if it goes too far or lacks context, it risks coming off as robotic or intrusive. 

Striking the balance between relevance and authenticity is key, especially in high-touch ABM programs where trust and tone matter, so it’s best to combine AI with human editors.

4. Skills and confidence gaps

Not every team is immediately comfortable using AI tools or trusting their output. 

There’s often a learning curve, and without internal champions or proper onboarding, adoption can stall. 

Training, experimentation, and transparency in how AI makes decisions can help build trust.

5. Budget and resource constraints

While many AI-powered ABM tools offer strong ROI, they can be a stretch for smaller teams or early-stage companies. 

It’s important to assess not just the tool’s capabilities, but whether your team has the resources to implement and manage it effectively.

Next steps: Putting AI-powered ABM into motion

AI isn’t just reshaping ABM - it’s redefining what’s possible. 

From real-time intent monitoring to predictive prioritization and fully automated outreach, AI allows GTM teams to move faster, target smarter, and personalize at a level that was unthinkable just a few years ago.

But tools alone don’t create impact. 

The real wins come when strategy, systems, and AI work together, aligning sales and marketing, focusing on the right accounts, and delivering value at every touchpoint.

If you’re ready to scale your ABM strategy with AI that’s built for real-world execution, not just dashboards, Warmly can help. 

Our AI marketing agents don’t just surface signals. They act on them, helping you turn intent into pipeline with speed and precision.

Book a demo and find out how Warmly can power your next phase of ABM.

Read more

• What is Person-Based Marketing & Why It’s Better Than ABM - Discover how person-based marketing takes ABM a step further by engaging real people and not just accounts with precision and personalization.
• Account Based Marketing vs Demand Generation: How Are They Different? [2024] - Explore the key differences between ABM and demand gen, and when to use each to drive smarter growth.
• 10 Best Account-Based Marketing Software (ABM) in 2024 - Find the top ABM platforms of 2024 that help you target, engage, and convert your highest-value accounts with ease.
• How to Develop An Effective Account Based Marketing Funnel - Learn how to build an ABM funnel that aligns sales and marketing, shortens deal cycles, and lands bigger deals.
• 6 Tangible Benefits of Account-Based Marketing (ABM) - Unpack the real, measurable gains of ABM, from higher ROI to tighter alignment and faster closes.
• AI Lead Generation: How to Use AI to Get More Leads in 2024 - Discover how to supercharge your pipeline with AI tools that find, qualify, and engage leads automatically.
• 10 Best AI Tools for Advertising in 2025 [Reviewed] - Get a breakdown of the smartest AI ad tools that help you launch, test, and optimize campaigns without the manual grind.
• AI Lead Scoring: What Is It & How To Do It Right In 2025? - Unlock the secrets to AI-powered lead scoring that helps your team focus on the leads most likely to convert.
• AI for Sales Prospecting: How to Use It? [2025] - Learn how AI is transforming sales prospecting by automating research, surfacing intent, and starting more conversations.
• AI in B2B Marketing: How To Use It? [2025] - Explore how B2B teams are using AI to personalize campaigns, optimize spend, and scale smarter in 2025.

Agentic automation has already become a full-blown shift in how GTM teams operate.

Instead of building rigid workflows or babysitting sequences, teams are now deploying self-directed AI agents that act, not just react. 

These agents don’t wait for triggers. They know the goal (“book more demos,” “revive ghosted leads,” “qualify inbound”) and take the best route to get there, adapting in real time as things change.

For sales, marketing, and revenue teams tired of duct-taping tools together or manually chasing tasks across channels, agentic automation delivers a smarter, more autonomous way to scale.

In this article, I’ll break down exactly what agentic automation is, how it works, real-world use cases across the GTM funnel, and the top tools powering this new era.

Ready to leave behind brittle workflows? Let’s begin by answering the key question:

What is agentic automation?

Agentic automation is the next evolution of AI-powered workflows, but with one big difference: it doesn’t wait around for instructions.

Instead of triggering actions based on fixed rules or linear workflows, agentic automation uses self-directed AI “agents” that can think, plan, and act on their own to achieve a goal. 

You tell the agent what you want done (e.g., “revive inactive leads” or “book demos from inbound form fills”), and it figures out how to make that happen across tools, channels, and steps.

This isn’t your typical automation that just runs a playbook. 

Agentic AI adapts in real-time. It can change direction mid-task, pull in new information, and even ask clarifying questions when the path forward isn’t clear. 

Think of it less like just another tool and more like hiring a proactive teammate who just gets it done. And that’s exactly why it matters. 

Because today’s GTM teams aren’t struggling with a lack of tools. They’re struggling with too many disconnected tasks, too much noise, and too little time. 

Agentic automation cuts through that by handling high-leverage, multi-step workflows that actually move the needle.

In the next few sections, I’ll cover exactly why this matters (spoiler: it's more than just efficiency), how it’s different from regular automation, and which industries are seeing the biggest wins.

What are the benefits of using agentic automation?

So, why should everyone - and I mean everyone - in the GTM world consider incorporating agentic automation in their operations?

Well, the thing is that agentic automation doesn’t just make things faster.

It makes them smarter, more scalable, and way less manual. 

Here are some of the real benefits you can expect:

1. Handles real work, not just busywork

Traditional automation is great at repeating simple tasks. 

But agentic automation can take on complex, multi-step workflows, like qualifying leads, booking meetings, or reactivating ghosted deals, without needing you to map out every step.

2. Adapts in real-time

Agentic AI can respond to changing inputs on the fly. 

If a lead replies with a new question, if a meeting gets rescheduled, or if more context becomes available, the agent adjusts its plan without breaking the workflow.

3. Connects the dots across your stack

Instead of relying on brittle automations or juggling five different tools, agentic automation can work across systems, pulling info from your CRM, sending outreach via email or LinkedIn, updating calendars, and more. 

The best agents orchestrate all of this behind the scenes, so the workflow actually flows.

4. Frees up your team to focus on higher-leverage tasks

AI agents can handle everything from outreach and follow-up to CRM enrichment and handoffs. 

As a result, your team can spend more time closing deals, crafting strategy, and driving growth.

5. Delivers outcomes, not just actions

You don’t have to pre-program every click. 

You just set the goal (“increase demo bookings from inbound leads”) and the agent figures out the best path to get there, end-to-end.

6. Scales with zero burnout

Agents don’t get tired. 

You can spin up five, ten, or fifty agents to handle different GTM motions from inbound to outbound to post-sale, all working in parallel without adding headcount.

What’s the difference between regular automation and agentic automation?

Let’s be real: most “automations” today are just glorified to-do lists.

You set a trigger → it runs a predefined action → and that’s about it. 

Works great when everything’s predictable. 

But the second something goes off-script, like a lead replying with a curveball question or a data field missing in your CRM, things fall apart.

Agentic automation changes the game entirely.

Here’s a quick overview of how regular and agentic automation stack up:

So, instead of building 47 logic branches for every possible scenario, you just tell the agent the goal, and it figures out the best way to get there.

Think of it like the difference between:

A basic email sequence tool that sends a pre-set drip campaign vs. an AI SDR that knows your ICP, monitors engagement signals, adapts copy, and books meetings autonomously.

One is rule-based. The other is agentic.

And guess which brings better results.

The industries that can best leverage agentic automation

Agentic automation isn’t just changing how we automate. It’s also changing who can benefit.

Now that AI agents can reason, adapt, and execute on high-level goals without hand holding, we’re seeing a wave of adoption across industries where traditional automation used to hit a wall. 

Here’s a look at the industries already seeing results and how agentic automation is helping them unlock new value:

1. B2B sales & marketing

This is where agentic automation is already making serious noise.

GTM teams are using AI agents to:

• Score and qualify inbound leads the moment they hit the website.
• Warm up cold prospects across email and LinkedIn.
• Revive ghosted deals with smart, context-aware follow-ups. 
• Create dynamic, targeted ad audiences fine-tuned to actual intent.

The thing that sets these agents apart from regular automation is that they don’t just run playbooks. 

Instead, they adapt on the fly, score leads based on real-time intent, and trigger outreach or routing without waiting for a rep to jump in. 

The result? More qualified pipeline, fewer dropped balls, and a sales team that can focus on closing instead of chasing.

2. Customer success & revenue operations

Agentic automation isn’t just a sales tool. It’s also a post-sale powerhouse. 

AI agents help CS and RevOps teams manage seamless handoffs, keep tabs on customer health, and surface churn risks before they become problems. 

They can do things like:

• Trigger personalized renewal nudges.
• Coordinate upsell plays.
• Loop in product or support when issues arise, and more. 

It’s like having a proactive, always-on account coordinator that never drops the ball, keeping customers engaged, informed, and more likely to stick around.

3. SaaS & tech

Speed matters in SaaS, and agentic automation gives fast-moving teams the edge. 

AI agents can qualify trial users in real time, trigger onboarding flows based on in-app behavior, and send personalized follow-ups after key product actions, all without human babysitting. 

For PLG teams, it’s a game changer, as you can drive usage-based upsells, renewals, and outreach that feels 1:1 without overwhelming your reps. 

It’s personalization at scale, with zero burnout.

4. Healthcare

In complex, highly regulated environments like healthcare, agentic automation is helping teams cut through administrative friction. 

AI agents can extract insights from unstructured clinical data, coordinate workflows across care teams, and ensure compliance documentation is handled without constant manual input. 

They even support personalized care journeys at scale, adapting to patient history, behavior, and treatment plans in real time. 

The goal is to streamline operations without losing the human touch, and these agents excel in it.

5. Financial services & insurance

In fast-paced, high-stakes industries like finance and insurance, speed and accuracy are everything. 

Agentic automation is being used to triage loan and claim applications, extract and analyze documents, and pre-qualify customers based on real-time data, at a fraction of the time humans would need for the same tasks.

AI agents can even flag fraud patterns on the fly, spotting risks faster than traditional rule-based systems. 

When decisions need to be made at scale without sacrificing precision, agents are the perfect fit.

6. IT

IT teams are no strangers to chaos, as tickets, system requests, data syncs, and endless Slack pings pile up fast. 

Agentic automation acts like a behind-the-scenes engine that keeps everything running smoothly. 

Agents can triage incoming requests, spot workflow inefficiencies, coordinate updates across internal tools, and even monitor systems for outages or anomalies, taking action before alerts hit your inbox. 

And in complex tech environments, it’s like giving your IT team a superpower.

Top 10 real-world use cases of agentic automation

Now that we’ve covered what agentic automation is and where it’s making the biggest impact, let’s look at what it can actually do.

From qualifying leads and running campaigns to analyzing contracts and fixing IT issues, agentic AI is already powering real-world workflows by making decisions, adapting to context, and driving outcomes at scale.

Here are 10 powerful, real-world use cases showing how agentic automation is being put to work today:

1. Lead scoring and qualification in real time

In most sales orgs, lead scoring is a fixed formula: assign points for job title, company size, maybe a few clicks on your site, and hope it tells you who’s worth following up with. 

The problem? Buyers don’t move linearly anymore, and static models miss the nuance. 

Timing, intent, behavior, and context all matter, and traditional automation just isn’t built to handle that.

Agentic automation flips this on its head. 

Instead of assigning scores based on rigid rules, AI agents continuously monitor behavior, detect buying signals, and qualify leads dynamically. 

These agents don’t just calculate scores - they understand actual intent. 

If someone’s bouncing between pricing pages, revisiting key blog posts, or engaging across multiple touchpoints, the agent recognizes it’s time to act, even if that lead wouldn’t have passed a traditional threshold.

This is where platforms like Warmly shine.

Warmly’s Marketing Ops Agent tracks dozens of real-time signals - such as website engagement, recency, firmographic match, traffic source, ad interactions, and even de-anonymized visitor data - to determine which leads are warm right now. 

Then, it combines these warm signals with relevant data from over 10+ data providers, creating deep, contextual insight that allows it to spot in-market buyers as soon as they show intent.

Even better, this agent actively improves your ICP over time. 

By analyzing which types of leads actually convert, and not just which ones look good on paper, the system continuously sharpens your targeting criteria and surfaces lookalike prospects who match the behavioral patterns of your best customers.

So instead of your reps wondering who to follow up with, agentic automation ensures they’re always working the right leads, at the right time, with context that goes far deeper than traditional MQL checklists.

2. Personalized outreach that runs 24/7

One of the most time-consuming parts of B2B sales is outbound prospecting, that is, finding the right people, personalizing messages, sending follow-ups, and keeping track of engagement. 

It's manual, repetitive, and doesn’t scale well, which is why most SDRs end up buried in busywork instead of actually starting conversations that lead to pipeline.

Agentic automation changes that.

With AI sales agents, teams can automate outbound efforts from end to end - from identifying high-intent accounts to sending personalized sequences across channels like email and LinkedIn. 

And the best part is that these agents don’t just blast generic messages. 

They understand which accounts are heating up, who the key stakeholders are, and how to engage them in a meaningful, relevant way - automatically.

Warmly’s AI SDRs are built specifically for this.

They act as full-time, always-on sales assistants that prospect, engage, and nurture leads around the clock, without ever needing a break. 

Here’s what they do:

• Monitor intent signals to detect when an account is showing buying behavior.
• Automatically find key stakeholders across the target account.
• Trigger personalized outbound sequences on behalf of reps via email and LinkedIn.
• Engage leads via contextual website chats and directly book meetings without the manual back and forth.

And because they're always running, you can scale outreach volume dramatically without needing to scale headcount.

3. Hyper-targeted advertising based on live signals

Most B2B ad campaigns still rely on broad targeting, using criteria such as job titles, company size, and industries. 

And while that can work, it often wastes spend on the wrong audience or reaches the right people at the wrong time. 

What these campaigns lack is context: who’s actually in-market right now, and what are they reacting to?

Agentic automation fills that gap by connecting real-time intent signals with ad delivery. 

Instead of relying on static lists or outdated firmographics, AI agents monitor on-site and off-site behavior, and then automatically build and sync high-intent segments to your ad platforms. 

That means your campaigns are constantly evolving based on who’s showing interest, what they’re engaging with, and where they are in their buying journey.

Warmly enables exactly this kind of intelligent advertising motion.

Its agentic demand gen engine tracks live buying signals across your site and other digital properties, including:

• Onsite behavior (e.g. pricing page visits, return traffic, time spent).
• Social engagement (e.g., relevant interactions with your LinkedIn posts or participation in discussions on topics related to your product).
• Third-party signals (researching keywords related to your product, visits to competitors’ pages, etc.).
• Relevant B2B & CRM data (like industry, title, and stage).

As Warmly detects interest surges from specific accounts or personas, it dynamically updates target segments and syncs them directly to your ad channels. 

This allows you to run hyper-specific campaigns, like surfacing a custom offer to only mid-market marketing leaders from in-market accounts, without lifting a finger.

Better yet, agents can automatically stop serving ads to leads who have already converted or passed a certain funnel stage, so your spend stays efficient.

Instead of your team constantly rebuilding audiences and guessing when to retarget, agentic AI advertising lets you stay relevant automatically and in real-time.

4. Automated lead follow-up and nurturing

Following up with leads sounds simple until you’re juggling dozens of conversations, multiple channels, and varying levels of interest. 

The truth is, most leads don’t convert on the first touch. 

But keeping track of who to follow up with, when, and how? That’s where most teams drop the ball.

Traditional automation helps, but it’s rigid. 

Set-it-and-forget-it sequences often lack personalization, can’t adapt to behavior changes, and don’t escalate when engagement spikes. 

That’s where agentic automation makes a major difference.

With agentic AI orchestration, follow-up becomes intelligent and responsive. 

These agents don’t just send templated messages on a fixed timeline. 

They monitor each lead’s actions - like revisiting your site, clicking an ad, or engaging with content - and adjust their outreach accordingly. 

Messaging gets smarter, timing gets sharper, and high-intent leads get fast-tracked.

Warmly’s SDR agents handle this in the background 24/7.

Once a lead enters the funnel, whether through chat, form fill, or signal detection, Warmly’s agents automatically:

• Determine the right follow-up path based on intent and behavior.
• Launch personalized email and LinkedIn sequences (avoiding duplication if reps are already engaged).
• Monitor responses and engagement patterns.
• Escalate qualified leads to your reps at exactly the right moment.

5. Contextual customer support 

Support teams are often overwhelmed by volume, from basic questions (“Where’s my order?”) to more complex issues that need routing or escalation. 

Traditional chatbots help with the basics, but they’re limited by rigid scripts and can’t adapt when conversations go off course.

Agentic automation unlocks a more flexible, intelligent approach.

Instead of just responding to predefined questions, agentic AI support agents can:

• Understand context.
• Ask clarifying questions.
• Pull relevant data from multiple systems.
• Execute multi-step actions to resolve an issue.
• Escalate to a human when needed, with full context included.

And because these agents operate around the clock, they reduce wait times, increase resolution speed, and free up human agents to focus on higher-complexity requests.

This kind of hands-off support is especially valuable for fast-growing SaaS companies, e-commerce platforms, and service-based businesses - anywhere customer expectations are high and team capacity is limited.

The result? Better experiences, lower support costs, and faster response times, all powered by agents that never sleep and never burn out.

6. Predictive maintenance in manufacturing

In manufacturing, downtime is expensive, whether it's a single machine going offline or an entire line coming to a halt. 

Traditional maintenance strategies rely on fixed schedules or reactive repairs, which either waste resources or result in costly interruptions.

Predictive maintenance, powered by agentic automation, offers a smarter alternative.

These agents monitor real-time data from IoT sensors embedded in equipment, such as vibration, temperature, or energy consumption, and use AI to detect subtle patterns that indicate potential failure. 

But unlike traditional monitoring tools that only alert humans, agentic agents can go a step further: they assess the risk, determine the best course of action, and trigger maintenance workflows autonomously.

In highly automated factories, this level of self-directed decision-making leads to:

• Higher operational uptime.
• Lower maintenance overhead.
• Faster response to emerging issues.
• Reducing downtime by 40%.

This type of automation gives manufacturing teams an intelligent layer of defence that adapts to real-world conditions without constant oversight.

7. Personalized customer experiences on-site

When a high-intent visitor lands on your website, timing and relevance make all the difference. 

But most sites still treat every visitor the same with static content, generic CTAs, and one-size-fits-all experiences. 

That’s a wasted opportunity, especially when you're dealing with accounts that are actively researching your product.

Agentic automation lets you tailor the on-site experience in real-time, based on who the visitor is, where they came from, and how engaged they are. 

These agents don’t just personalize headlines. They can adjust offers, trigger live chat, recommend next steps, and adapt content dynamically as the visitor browses.

Warmly uses agentic AI to do exactly that.

Its system identifies anonymous traffic and enriches it with firmographic and behavioral data. 

And then, based on persona, traffic source, and intent level, agents can:

• Display personalized offers or CTAs (“Ready for a demo?” vs “See how it works”).
• Trigger intelligent chatbot conversations.
• Suggest relevant case studies, feature pages, or pricing content.
• Route high-value visitors directly to live reps or AI chat.

This way, instead of just optimizing for form fills, agentic on-site experiences guide leads through their own journey. 

The result? Higher conversion rates, more qualified conversations, and better first impressions without requiring your team to lift a finger.

8. Legal and contract analysis at scale

Legal work is often seen as too complex or nuanced to automate, and in many cases, that’s true. 

But much of the day-to-day legal load, especially contract review, is repetitive and rules-based: finding key clauses, identifying risks, checking compliance, and flagging inconsistencies.

And that’s where AI agents step in.

Unlike basic document scanning tools, agentic AI can process legal documents with contextual understanding. 

They can analyze NDAs, vendor agreements, terms of service, and more, surfacing missing terms, suggesting revisions, and routing specific risks to the right legal stakeholders.

For in-house legal teams and firms dealing with high volumes of contracts, this leads to:

• Faster turnaround times.
• Reduced human error.
• More consistent compliance.
• Better allocation of legal talent to complex, high-value matters.

It’s a prime example of agentic automation replacing process friction with smart, autonomous execution, even in industries known for caution and complexity.

9. IT operations and incident resolution

Modern IT environments are increasingly complex, with hybrid infrastructure, dozens of monitoring tools, and constant pressure to keep systems up and running. 

And when something breaks, every minute counts. But traditional incident response often looks like this: 

Wait for an alert → check a dashboard →  escalate to the right person →  hope it gets resolved fast.

Agentic automation turns this reactive model into a proactive, autonomous one.

Instead of relying on static thresholds and manual triage, agentic AI can:

• Monitor system health continuously across environments.
• Detect anomalies using historical patterns and real-time data.
• Diagnose root causes.
• Trigger automated remediation steps (restart services, reroute traffic, apply patches).
• Escalate only when human input is truly needed.

This isn’t just “automation” in the ticketing sense. 

These are AI agents that reason, act, and improve, learning from past incidents and outcomes to respond faster and smarter over time.

10. HR and recruitment workflows

Hiring great people is critical, but it’s also one of the most time-consuming and resource-intensive functions in any company. 

Between reviewing resumes, scheduling interviews, sending assessments, updating candidate pipelines, and keeping everyone aligned, it’s no wonder recruiters are overwhelmed.

Agentic automation is changing the game for talent teams by handling many of these workflows autonomously and intelligently.

These agents can do far more than just parse resumes. They:

• Analyze job descriptions and candidate profiles to assess fit.
• Rank applicants based on customizable hiring criteria.
• Send personalized outreach and interview requests.
• Coordinate scheduling based on availability across calendars.
• Provide real-time status updates to hiring managers.
• Flag potential red flags (like job-hopping or skill mismatches) and escalate for review.

What sets agentic systems apart is their ability to adapt. 

For example, if a candidate suddenly becomes inactive, the agent can adjust the outreach cadence or route the lead to a talent pool for future roles. 

If a hiring manager leaves feedback, the agent updates its ranking logic for the next batch of applicants, learning as it goes.

The result?

Shorter time-to-hire, reduced admin burden on recruiters, and more consistent candidate experience across departments.

4 best agentic automation tools on the market

Not all AI tools are truly agentic. 

Many still rely on rigid rules or simple workflow builders. 

But a new wave of platforms is giving teams access to actual autonomous agents that can reason, adapt, and execute across complex tasks with minimal input.

Here are four of the best agentic automation tools on the market today.

1. Warmly

Best for: B2B revenue teams that want to scale outreach, qualification, and lead follow-up with AI SDR agents.

Warmly brings agentic automation to sales and marketing with AI SDRs, Demand Gen, and Marketing Ops agents that can orchestrate your entire funnel from top to bottom. 

It's purpose-built for GTM teams, replacing manual prospecting, nurturing, and follow-up with autonomous workflows that actually drive pipeline.

Standout features

• AI SDRs that prospect, sequence, and multi-thread - Automatically identify high-intent accounts and contacts, then launch multi-step outbound campaigns across email and LinkedIn, just like a human rep would.
• Real-time lead qualification - Continuously scores and prioritizes leads using dozens of live intent signals, CRM data, and engagement history to surface the hottest opportunities.
• Dynamic ICP creation - Combines live intent signals and historical data to continuously update your ICP, ensuring your campaigns are relevant and perfectly targeted every single time.
• Adaptive ad targeting agents - Automatically syncs high-intent lead segments to your ad platforms, so only the right audiences see your campaigns, at the right time.

Pricing

Warmly offers a free forever plan that allows you to reveal up to 500 monthly visitors, set up ICP filters to quickly identify high-quality leads, and automate basic lead routing.

If you need more, there are three tiers to choose from:

1. Data Only: Starts at $599/mo when billed monthly or $5,000 when billed annually, lets you identify up to 5,000 monthly visitors, first-party intent signals, alerts, and access to Warmly’s B2B prospecting database.
2. Business: Starts at $19,000/year for up to 10,000 visitors or $45,000/year for up to 75,000 visitors, everything in Data Only, plus third and second-party signals, sales orchestration, AI Chat, and lead routing.
3. Enterprise: Custom pricing, custom number of visitors, everything in Business, plus custom signals and warm calling.

2. UiPath

Best for: Enterprise IT and operations teams looking to integrate agentic AI with RPA and existing automation stacks.

UiPath is extending its legacy in robotic process automation with AI agents that can reason, plan, and take independent action. 

It's ideal for enterprises managing complex systems that span across departments.

Standout features

• Agent Builder for autonomous workflows - Lets teams design and deploy agents that interact with apps, systems, and users to complete multi-step processes.
• LLM-powered engines - Empowers agents to process natural language, extract context, and make on-the-fly decisions based on current state and data inputs.
• Process orchestration for hybrid teams - Coordinates humans, agents, and bots within a unified workflow, ensuring smooth handoffs and goal alignment.

Pricing

UiPath has three pricing plans:

1. Basic: Starting at $25 per month, includes basic automation builder, EU hosting, etc.
2. Standard: N/A, includes everything in Basic, plus advanced automation builder, enhanced governance controls, agents, robots, and people orchestration, etc.
3. Enterprise: N/A, includes everything in Standard, plus self-healing UI automation builder, dashboards for monitoring, optimizing, and simulating live business processes, automatic optimizations of your own Robot infrastructures, etc.

Since UiPath doesn’t disclose prices for its Standard and Enterprise plans, you’ll have to contact its sales team for more details.

3. Paradox

Best for: Talent acquisition teams seeking to automate candidate screening, outreach, and scheduling.

Paradox automates repetitive hiring tasks with a conversational AI agent that acts like a recruiting assistant.

It tackles everything from screening candidates and booking interviews to providing real-time updates without HR intervention.

Standout features

• Conversational AI assistant ("Olivia") - Engages candidates through chat to qualify them, answer questions, and guide them through the hiring process automatically.
• Behavior-adaptive workflows - Adjusts follow-up timing and messaging based on candidate responsiveness and past interactions, improving engagement rates.
• Integrated interview coordination - Connects with hiring managers’ calendars and books interviews without needing recruiters to manually intervene.

Pricing

Paradox doesn’t publish prices.

You’ll have to contact its sales team for more information.

4. BigPanda

Best for: IT operations teams aiming to automate incident detection, response, and resolution.

BigPanda applies agentic AI to IT operations by enabling AI agents to detect, diagnose, and resolve incidents autonomously. 

It integrates with observability tools to create a self-healing environment that reduces alert fatigue and downtime.

Standout features

• Autonomous incident correlation - Groups related alerts together using AI, so teams aren’t overwhelmed with noise and can focus on root causes.
• Root cause analysis agents - Analyzes logs and metrics in real time to pinpoint why issues are happening and suggests (or initiate) fixes automatically.
• Self-learning optimization - Continuously refines detection and resolution logic based on historical incident data and resolution outcomes.

Pricing 

BigPanda doesn’t publish any information regarding its packages or their exact prices.

You can book a demo to learn more.

What are some of the challenges associated with incorporating agentic automation into your sales strategy?

Finally, while agentic automation has the power to transform sales, it’s important to understand that adopting it efficiently isn’t without its challenges. 

It’s not just about installing a tool and flipping a switch. It requires a thoughtful shift in how your team works, how your data flows, and how you measure success.

Here are some of the most common challenges to watch for:

1. Data readiness and hygiene

Agentic AI relies on accurate, real-time data to make decisions. 

If your CRM is a mess, your enrichment sources are outdated, or your lead activity isn’t being tracked consistently, agents will struggle to operate effectively - or worse, make poor decisions. 

Before deploying agents, teams need to invest in cleaning up data pipelines and ensuring core GTM systems are properly integrated.

2. Over-automation without context

Just because agents can automate something doesn’t mean they should. 

Without clear guardrails, agentic workflows can lead to robotic outreach, misrouted leads, or impersonal customer experiences. 

Sales leaders need to set clear goals, define when humans should stay in the loop, and ensure agents are enhancing, not replacing, meaningful interactions.

3. Integration complexity

Agentic automations often need to work across multiple platforms, including CRM, email, LinkedIn, ad platforms, chat, calendar, and more. 

If your systems are fragmented or lack API support, you may hit serious friction. 

Successful implementation often requires coordination between sales, marketing, ops, and IT to create a connected, automation-friendly environment.

4. Rep adaptation and process change

Reps may be sceptical, or even resistant, when they hear “AI SDR.” 

And that’s fair. 

If not rolled out properly, agentic tools can feel like a black box or a threat to their role. 

Teams need to invest in onboarding, education, and transparency, positioning agents as assistants that free reps up to focus on higher-leverage work, not tools that replace them.

5. Monitoring, optimization, and oversight

Unlike static workflows, agentic automation evolves over time. 

That’s powerful, but it also means you need systems in place to monitor performance, review outputs, and tune behavior. 

Who owns this? Sales ops? RevOps? Marketing automation reps? 

Clear ownership is critical to keep things on track and aligned with strategy.

6. Measuring success beyond vanity metrics

It’s tempting to measure success based on volume, such as more sequences launched, more contacts reached. 

But agentic automation should be evaluated based on real outcomes: higher conversion rates, more qualified meetings, smoother handoffs, and less manual work. 

Teams need to align on the right KPIs before scaling automation.

Next steps: Agentic automation is already here - the only question is how you’ll use it

The way sales teams operate is changing, and fast. 

Agentic automation isn’t some future-state vision. 

It’s already booking meetings, qualifying leads, running follow-ups, and moving pipeline forward in real time. 

The teams that win in this new era won’t be the ones with the most tools. They’ll be the ones who know how to orchestrate outcomes, and not just send more generic messages.

That’s where agentic AI shines. It doesn’t just follow rules. It understands context. It adapts. It acts. 

And when used right, it frees your team to focus on the parts of selling that actually require a human, such as building trust, closing deals, and thinking strategically.

Curious how it all works in action?

Warmly’s AI agents are helping revenue teams like yours scale without the spam, book more qualified meetings, and stay top-of-mind with the right leads, all day, every day.

Book a demo and see what agentic automation looks like in real life.

Read more

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In 2025, sales teams don’t win with more data. They win with smarter data.

That’s where AI data enrichment comes in. 

Instead of relying on static lists or partial profiles, enrichment tools powered by AI can automatically fill in the blanks, validate details, and surface critical insights, all in real-time.

Whether it’s identifying decision-makers, uncovering buying signals, or syncing firmographic data across your stack, enriched data means your team spends less time guessing and more time closing.

In this article, I’ll break down what AI data enrichment really is, how it works, why it matters for modern GTM teams, and how to implement it right, plus the top tools to consider as a bonus.

Let’s dive into the tech that turns raw contacts into ready-to-convert leads!

What is AI data enrichment, and how does it work?

AI data enrichment is the process of enhancing raw or incomplete data by automatically adding relevant, real-time information using artificial intelligence. 

Instead of relying on manual research or third-party lists that go stale quickly, AI enrichment tools connect to multiple data sources (like public databases, proprietary datasets, CRM records, and third-party APIs) to fill in the blanks accurately and at scale.

Here’s how it typically works:

1. AI models ingest your existing records, such as lead lists, contact info, or firmographic data.
2. They cross-reference these entries against real-time sources to verify, supplement, or correct missing information (like job titles, buying signals, industry, tech stack, recent funding, etc.).
3. Machine learning ensures the enrichment becomes smarter over time, prioritizing high-confidence matches and eliminating duplicates or bad data automatically.

The result? 

A living, breathing database that’s always up-to-date and immediately actionable without hours of manual effort. 

And because the enrichment happens automatically, your sales and marketing teams stay focused on engaging the right people, not cleaning up endless rows of spreadsheets.

Next, let’s look at why this matters and how AI takes enrichment to the next level.

What are the benefits of using AI for data enrichment?

AI data enrichment isn’t just about speed. 

It’s about turning scattered, outdated, or incomplete data into revenue-ready sales intelligence that helps GTM teams move faster, personalize smarter, and close more deals. 

Here's what that unlocks:

1. Real-time precision and data freshness

AI enrichment tools continuously sync your data with live external sources, pulling in updates on titles, funding rounds, tech stack changes, and more. 

This means your team is always working with the most accurate and up-to-date information available, not lists that went stale three months ago.

2. Hyper-targeted segmentation and personalization

With richer data, such as technographics, job roles, or recent buying intent, you can segment leads far more effectively and personalize your messaging at scale. 

AI makes it possible to go beyond surface-level traits and speak to what actually matters to each account or buyer.

3. Automation that reduces manual effort

Traditionally, enrichment meant hours of spreadsheet work or chasing leads on LinkedIn. 

With AI, that legwork is automated. 

New leads are enriched as they enter your system, and existing records are continuously updated, freeing up time for reps to focus on outreach and deal progression.

4. Better conversions across the funnel

When you’re reaching out to the right people, with relevant context, at the right moment, responses naturally go up. 

AI-enriched data directly impacts conversion rates by powering smarter targeting and reducing the guesswork in your GTM motion.

5. Improved CRM hygiene and data confidence

Bad data costs you, resulting in lost deals, wasted outreach, and reporting errors. 

AI helps keep your systems clean by deduplicating records, flagging inconsistencies, and enriching missing fields in real-time. 

This means there’s no more bloated CRMs full of half-complete or outdated profiles.

6. Competitive edge at every touchpoint

Teams that adopt AI enrichment don’t just move faster - they move smarter. 

With richer signals and deeper context behind every lead, your GTM strategy becomes more predictive, more personalized, and ultimately more effective than those still relying on static, manual data.

What are the different types of data enrichment?

There are several different kinds of data enrichment, each serving a distinct purpose and playing its role in your marketing strategy.

Here are the key types you’ll see, which are often combined in modern enrichment platforms:

1. Firmographic enrichment - Adds business-level data like industry, company size, revenue, location, and growth stage. This is essential for B2B segmentation and ideal customer profiling.
2. Technographic enrichment - Surfaces what tools or platforms a company is using, like CRM, cloud infrastructure, ad tech, or sales software. This is useful for competitive targeting, integrations, and outbound personalization.
3. Demographic enrichment - Fills in individual-level details like job title, seniority, department, and social profiles, so you’re not just targeting “a company,” but the right person inside it.
4. Behavioral and intent enrichment - Brings in real-time buying signals, such as recent site visits, content downloads, hiring trends, or spikes in keyword research. This is where AI really shines, surfacing leads that are actually in-market.
5. Contact enrichment - Adds missing details like email addresses, phone numbers, or LinkedIn profiles for outreach-ready records, often with confidence scoring and automatic syncing to your CRM or sales tools.

Together, these enrichment types give you a 360-degree view of who your leads are, what they’re doing, and how best to engage them without chasing static lists or scraping the internet manually.

What are the different AI data enrichment techniques?

AI data enrichment is not just about appending missing fields. 

It's about transforming raw data into actionable intelligence through a variety of sophisticated techniques. 

Here's a quick overview of the most impactful methods:

1. External data integration

This technique means adding useful information to your existing customer or lead data by pulling data from outside sources.

For example, AI can look at public records, social media, company websites, or quickly sift through databases like Coldly to find extra details, like someone’s job title, the size of their company, or what tools they use.

By combining this external data with what you already have, you get a more complete picture of who your buyers are and how to reach them more effectively.

2. Data cleansing and deduplication

This technique helps clean up messy or incorrect data in your CRM or other lead databases. 

AI looks for things like typos, missing fields, outdated info, or records that show up more than once.

For example, if the same lead is entered twice in your CRM with slightly different names or email addresses, AI can spot it and fix it automatically.

As a result, you get clean, accurate, and reliable data that your team can actually trust.

3. Semantic enrichment

This technique is all about giving your data more meaning. 

AI looks at what’s already in your database and connects it to related topics or categories using public knowledge sources.

For example, if a contact’s job title is “VP of Growth,” semantic enrichment might also tag them as part of the marketing department or leadership team.

This helps your team understand context and improves targeting, allowing you to spot key stakeholders and related accounts more easily.

4. Geospatial enrichment

This technique adds location data, like the exact coordinates or region a person or company is based in.

So instead of just knowing someone is in “New York,” AI might add their zip code or nearby landmarks.

This is especially useful for planning local mail campaigns, assigning territories, or optimizing deliveries.

5. Sentiment analysis

AI reads through text like social media posts, reviews, or survey answers, and figures out the tone.

Is someone happy, frustrated, or excited?

Sentiment analysis helps companies understand how people feel about their brand, product, or service without having to read through every single comment.

6. Multimedia content analysis

Multimedia content analysis helps you understand and organize large volumes of visual content, such as images and videos, without manual review.

AI can scan a photo or video and figure out what’s in it, such as objects, people, logos, or even emotions.

It also pulls out useful details (like location tags or timestamps), helping companies organize and understand their visual content more easily.

This way, if your brand is mentioned in a product unboxing video or someone posts a photo with your logo, AI can detect that automatically. 

It’s essential for brand monitoring, content moderation, and making smarter use of user-generated content.

7. Predictive analytics

AI looks at past behavior and trends to guess what might happen next.

For example, if a lead has visited your pricing page three times and opened your last two emails, predictive analytics might flag them as likely to buy soon.

This helps you prioritize outreach and take action at the right time.

8. Behavioral data enrichment

This technique tracks how people interact with your website, emails, or product, and then adds those insights to their profile.

This includes things like: which pages they visited, how long they stayed, and what they clicked on.

It gives you a clearer view of what someone is interested in right now, so you can follow up in a smarter, more relevant way.

Platforms like Warmly excel in this, leveraging sophisticated AI models to screen for and identify intent signals in real-time, combining internal data (interactions with your website) with external data from 10+ data enrichment providers.

As a result, you can:

1. Identify high-intent leads while their interest is at its peak.
2. Create detailed lead segments and target audiences.
3. Craft hyper-personalized outreach strategies leveraging the data you have on each lead.

How can you incorporate AI data enrichment into your sales process?

When it comes to incorporating AI data enrichment, the good news is that you don’t need to reinvent your sales process to benefit from it.

You just need to plug it into the right places.

Here’s how to make it work, step by step:

Step #1: Start with your CRM or lead source

Before you do anything else, connect your AI data enrichment tool to wherever your leads first enter the system, which is usually your CRM (like HubSpot, Salesforce, or Pipedrive) or your lead capture forms (like website forms, demo requests, or webinar signups).

Once connected, the AI can automatically enrich each new contact as they come in, adding details like job title, company size, LinkedIn profile, industry, and more. 

Say someone fills out your demo request form and only gives you their name and work email. 

Without enrichment, your team has very little to go on. 

But with AI data enrichment connected to your CRM:

1. The system identifies that the person is Julia Wong, Head of Product at a Series B fintech company using Salesforce and Stripe.
2. It automatically adds her LinkedIn profile, company headcount, funding stage, and a few recent company updates.

As a result, your rep now knows who she is, what her company does, and can tailor the pitch accordingly.

Step #2: Clean and enrich existing records

Your CRM might already be packed with leads, but if that data is old, incomplete, or duplicated, it’s holding your team back. 

This step is about using AI to automatically:

• Fill in missing fields (like job titles or industries).
• Update stale info (like a contact who changed roles or companies).
• Merge duplicates so you’re not contacting the same person twice.

It’s the fastest way to turn your database into a useful, up-to-date sales asset.

For example, imagine your rep is about to follow up with Sophie D., but her CRM record hasn’t been touched in over a year. 

With AI enrichment:

1. You discover she’s no longer at her old company - she’s now VP of Marketing at a startup that just raised a Series A.
2. The AI updates her profile, syncs her new LinkedIn, and tags her new company with relevant firmographics.

Now your rep knows Sophie’s a high-value target and not a dead-end lead.

Step #3: Use enriched data to segment smarter

Once your data is enriched, you can go far beyond basic filtering. 

Instead of blasting generic messages to everyone in your CRM, AI-enriched fields let you create precise, dynamic segments based on:

• Company size.
• Industry.
• Funding stage.
• Tech stack.
• Buying signals.
• Job seniority, and more.

For instance, Warmly’s Marketing Ops agents work 24/7 on building targeted audience segments, unearthing granular insights and traits that go beyond just firmographics.

This way, you get more accurate, always updated ICP and dynamic, well-targeted audiences.

The outcome?

Smarter segments = more relevant messaging = better results.

Step #4: Prioritize leads based on real signals

Not all leads are created equal, and AI enrichment helps you spot the ones most likely to convert.

By layering in signals like job changes, recent funding, hiring spikes, or product research behavior, AI can help you automatically score and prioritize leads based on who’s showing real buying intent.

This means your reps stop wasting time on cold or low-fit prospects and focus on the ones that are actually worth it.

For example, if you’ve got 300 leads sitting in your CRM, AI enrichment can highlight that:

1. 5 of them work at companies that just raised a Series B,
2. 2 have just installed a competitive tool your product integrates with,
3. And 1 rep just switched into a new buying role last week.

And voila - that’s your shortlist! That’s who your team should talk to today.

Step #5: Personalize your outreach at scale

Enriched data turns generic outreach into relevant, high-converting messages without making your team write everything from scratch.

With details like job title, industry, tools used, recent activity, or even company news, your reps (or your AI assistant) can personalize emails, InMails, and call openers automatically.

You still get the scale, but now it feels like 1:1 communication.

This means that instead of sending:

“Hi Jamie, I’d love to connect and share what we’re building.”

You send:

“Hi Jamie, I saw you recently joined Acme as Head of GTM. Since you’re using HubSpot + Gong, I thought I’d share how we help RevOps teams using that same stack increase pipeline coverage.”

With tools like Warmly, you can put the entire outreach process on autopilot:

1. The platform identifies high-intent leads and enriches them with in-depth B2B and intent data.
2. Its AI SDR agents automatically pick up those leads and include them in email or LinkedIn sequences, using the info they have on each lead to tailor messaging accordingly.

The result?

Higher open, reply, and conversion rates across channels.

Step #6: Sync across your stack

It’s not enough to enrich your data. You need to make sure everyone in your GTM motion is seeing and using it.

That means syncing enriched profiles across your CRM, email tool, sales engagement platform, and analytics dashboards. 

When done right, every system pulls from the same up-to-date, enriched source of truth and your reps, marketers, and ops folks stay aligned.

Step #7: Review and refine regularly

AI data enrichment isn’t a “set it and forget it” solution. 

To get the best results, you’ll want to monitor performance, audit your data health, and adjust your enrichment strategy as your sales process evolves.

Look at which enriched fields actually help your team convert.

Is the funding stage more useful than the tech stack? Are job titles getting messy again?

Refining over time keeps your data - and your strategy - sharp.

For example, if you notice your reps rarely use the “industry” field but rely heavily on job seniority and recent hiring signals, that’s your cue to update your scoring model and prioritize the fields that actually drive results.

What are some of the challenges in using AI for data enrichment?

While AI data enrichment can certainly transform your sales process, like any powerful tool, it comes with its own set of challenges. 

Let’s look at some of the most common issues teams face (and how to overcome them):

1. Data quality in, data quality out

AI can enrich your data, but it can’t work miracles if your starting point is garbage. 

If your CRM is full of outdated, mislabelled, or inconsistent records, enrichment tools may struggle to match or append the right information.

💡Tip: Start with a basic data clean-up before layering in AI. The better your foundation, the better the enrichment results.

2. Integration complexity

Many enrichment tools promise plug-and-play, but syncing them across multiple platforms (CRM, sales engagement, analytics) can get messy, especially if your systems are siloed or custom-configured.

💡Tip: Choose tools with native integrations for your core stack, and work closely with RevOps or your CRM admin to set up clean, bi-directional syncs.

3. Over-enrichment or irrelevant fields

Just because you can add 30 new fields to every contact doesn’t mean you should. 

Too much data clutters your workflows, confuses reps, and can even hurt personalization if the info isn’t actually helpful.

💡Tip: Be selective. Focus on enriching fields your team will use, such as job role, seniority, and buying signals, not vanity metrics.

4. Privacy and compliance risks

Pulling in external data, especially personal or behavioral data, can introduce privacy issues. 

You’ll need to make sure you’re compliant with GDPR, CCPA, and other local regulations around data usage and transparency.

💡Tip: Use enrichment providers who are transparent about their data sources and have strong privacy practices in place. Always give users a way to opt out if required.

5. AI blind spots or mismatches

No system, including AI, is perfect. 

Sometimes enrichment tools misidentify people, attach the wrong company data, or pull in outdated information. 

If you rely too heavily on enrichment without validation, your reps may act on bad signals.

💡Tip: Set confidence thresholds for enriched fields. Some tools let you prioritize “high certainty” matches or even flag data for manual review before syncing to your CRM.

Next steps: Get smarter data to do sharper outreach with Warmly

In today’s sales landscape, it’s not about how much data you have.

It’s about how accurate, timely, and actionable that data is, and that’s where AI-powered enrichment makes all the difference.

By automating enrichment, syncing it across your tools, and embedding it into your workflows, you can unlock faster research, better segmentation, and truly personalized outreach at scale. 

But the key isn’t just adding data - it’s knowing what to do with it.

Warmly helps GTM teams not only enrich leads with real-time firmographic and behavioral signals, but also act on them, automatically surfacing the hottest accounts, adapting outreach, and helping reps prioritize with confidence.

Want to see it in action? Book a demo with Warmly and discover how smarter data can fuel more efficient selling.

Read more

• The 12 Top Lead Enrichment Tools for GTM Teams in 2025 - Discover the best lead enrichment tools that modern GTM teams are using to turn raw contact data into revenue-ready insights.
• 9 Best Data Enrichment Tools in 2024 - Explore the top platforms helping B2B teams clean, complete, and supercharge their databases with smarter, more actionable data.
• AI Lead Scoring: What Is It & How To Do It Right In 2025? - Learn how AI is changing lead scoring forever and how to use it to prioritize the right prospects at the right time.
• AI for Sales Prospecting: How to Use It? [2025] - Find out how AI is helping sales teams prospect faster, better, and with less manual effort in 2025.
• AI GTM: Top Use Cases, Software, & Examples [2025] - See how AI is transforming every stage of the go-to-market motion with real-world tools and workflows that actually deliver.
• How to Evaluate B2B Data Providers: The Warmly Decision Framework - Use this proven framework to confidently choose the right data partner for your sales and marketing needs without the guesswork.
• How to Use AI in Your Sales and Marketing Tech Stack - Unlock practical tips for integrating AI into your GTM stack to boost performance, automation, and revenue impact.
• AI-Powered Sales Automation: Use Cases, Examples & Software - Explore how AI is automating everything from outreach to pipeline progression—and which tools are leading the way.

Account-based marketing (ABM) is a highly specific strategy that completely transforms how B2B teams approach growth. 

Instead of casting a wide net, ABM aligns marketing and sales to go deep on high-value accounts, using personalization, timing, and intent signals to drive real results.

And in 2025, ABM is smarter, more automated, and more connected than ever.

But let’s be honest: generic templates and surface-level tactics won’t cut it. 

If you want your ABM strategy to actually move pipeline, you need ideas rooted in reality.

In this article, we’re breaking down 8 of the most inspiring, creative, and effective ABM examples, from hyper-personalized outreach to multi-channel plays that actually convert.

These will help you think bigger, test smarter, and sell more effectively, regardless of whether you’re refining your current ABM motion or building one from scratch.

What are some of the best practices of ABM in 2025?

ABM in 2025 is more intelligent, integrated, and intent-driven than ever. 

As teams lean into AI, better data, and tighter sales-marketing collaboration, ABM has shifted from being a niche strategy to a foundational B2B motion. 

But getting it right still requires more than just tech - it takes focus, coordination, and experimentation. 

Here are the best practices leading teams are using today:

1. Hyper-personalization at scale

Today, ABM isn’t just about personalization - it’s about relevance at scale. 

Leading teams are using AI and real-time intent data to create content and outreach that feels handcrafted, even when it’s automated. 

That might mean referencing a prospect’s latest funding round, tailoring ads to industry-specific challenges, or adapting messaging based on where an account sits in the buying cycle. 

The key isn’t just adding a name, it’s showing you understand the actual context and each individual lead’s current buying stage and other relevant circumstances. 

According to Salesforce, 73% of B2B buyers expect vendors to personalize their engagement to their needs, and that number is probably going to increase, so keep that in mind.

Tools like Warmly make this kind of personalization scalable. 

With AI SDRs that trigger automated, context-aware sequences across email and LinkedIn based on live engagement signals and website behavior, teams can deliver the right message to the right stakeholder at the right time. 

Whether it’s finding key contacts or orchestrating follow-ups, Warmly helps revenue teams build 1:1 relationships across hundreds of accounts without adding headcount.

2. Using AI and predictive insights to guide targeting

With so much data available, the best ABM programs use AI to filter noise from signals. 

Predictive models surface which accounts are warming up, which are showing in-market signals, and which should be deprioritized. 

Instead of relying on guesswork, teams are scoring accounts in real time using a mix of firmographics, CRM activity, website behavior, and buying signals, so reps can strike when interest is peaking.

This is where platforms like Warmly give teams a serious edge. 

Warmly monitors first, second, and third-party signals at the person level, not just the account level, pulling in everything from product usage and web behavior to social activity and job changes. 

As a result, teams can build intelligent segments based on real-time signals and launch precise, personalized sequences or ad campaigns the moment actual intent is detected. 

It’s ABM targeting driven by live buyer context, not assumptions.

3. Aligning marketing and sales around shared account goals

In 2025, ABM is no longer a marketing-led initiative - it’s a go-to-market strategy. 

That means sales and marketing don’t just "collaborate".

Instead, they plan together, build together, and measure success using shared KPIs. 

Teams that win with ABM often have unified account plans, regular alignment meetings, and tools that sync campaigns across functions. 

When both teams are working off the same playbook, outreach feels cohesive, and deal cycles speed up.

4. Going multi-channel, but staying coordinated

No single channel wins deals. 

The most effective ABM programs engage accounts across email, LinkedIn, targeted ads, virtual events, landing pages, and more, but with one consistent narrative. 

The key thing that sets high-performing teams apart is their orchestration - using tools that sequence touches across platforms while ensuring every stakeholder sees a story that makes sense. 

Done right, this builds familiarity, increases trust, and helps accounts self-navigate deeper into the funnel.

That’s the exact role of Warmly’s AI SDRs, which can engage accounts on all channels that matter, including:

• Your website via a smart AI Chatbot that engages and qualifies leads and books meetings.
• LinkedIn through personalized DMs and connection requests to engage surging accounts while they’re still interested.
• Email drip campaigns that nurture accounts and lead them down the ABM funnel.

5. Measuring what matters (and refining fast)

Modern ABM isn’t set-it-and-forget-it. 

The best programs track not just clicks and opens, but pipeline influence, sales velocity, and account engagement over time. 

Leading teams today are using account-based dashboards to identify what’s working and where things stall, then refining campaigns accordingly. 

It’s not about proving ROI with vanity metrics; it’s about building a funnel that continuously learns and improves. 

Think of it as agile marketing, but account-first.

What does a best-in-class ABM strategy look like in 2025?

In 2025, a best-in-class ABM strategy is more than just a campaign - it’s become an entire system that covers all the essential parts of the funnel. 

This means that the strongest B2B teams aren’t just “running ABM”. 

They’ve built always-on, cross-functional growth engines that embed account-based thinking across their entire revenue strategy.

Here’s what I mean by this:

1. ABM is embedded into the full go-to-market motion

At leading companies, ABM isn’t a side project - it’s a core growth strategy. 

From demand gen to outbound, sales enablement to customer marketing, every team is aligned around a unified list of high-value accounts. 

Rather than splitting resources between lead gen and ABM, the entire GTM org is structured to win and expand within a focused TAM. 

Metrics, headcount, and budget follow suit for optimal results.

2. Segmentation is intelligent, dynamic, and real-time

Top teams aren’t relying on quarterly account refreshes or static firmographic filters. 

Their segmentation engines are fluid, driven by real-time data, behavioral signals, and evolving buying committee dynamics. 

For example, if a VP of Ops at a target account visits your pricing page and a second stakeholder starts a product chat the next day, that account automatically gets promoted into a new play.

This is where Warmly shines: it lets teams track intent signals and web activity at the individual level, across 1st, 2nd, and 3rd party sources. 

With that visibility, you can create dynamic audiences that update automatically and trigger personalized sequences or outbound plays without delay using the Orchestrator or agentic AI SDRs.

3. Personalization is programmatic, but human

Best-in-class ABM doesn’t mean handcrafted messages for every touch. It means building systems that feel personalized without being slow. 

Teams use AI to generate context-aware outreach at scale, but pair that with human insight where it matters (e.g., for high-tier accounts or C-level personas). 

The result is outreach that respects the buyer’s context while protecting your team’s bandwidth.

Tools like Warmly’s AI SDRs help strike this balance by automating thoughtful messages based on live activity and contact-level behavior, so reps can focus on strategic conversations instead of manual follow-ups.

4. Revenue teams operate as one account team

The old marketing-to-sales handoff doesn’t exist in a best-in-class ABM motion. 

Instead, everyone touching the account, such as BDRs, AEs, CSMs, marketers, etc. works from a shared source of truth. 

They know who’s engaged, who’s cold, and what’s been tried. 

Tools are integrated. Roles are clearly defined. And there’s total clarity on ownership across every stage of the account lifecycle.

5. Orchestration is proactive, not reactive

Instead of reacting to inbound interest or waiting for MQLs to convert, top ABM teams proactively orchestrate sequences, ads, meetings, and outreach based on buying stage and stakeholder activity. 

This orchestration happens across multiple touchpoints, including email, LinkedIn, chat, and events and unfolds in a way that feels cohesive and timely.

Warmly’s Orchestrator makes this possible at scale, automatically triggering next-best actions - such as adding accounts to targeted LinkedIn ads campaigns, or firing personalized LinkedIn and email sequences - based on behavior, contact role, or engagement score. 

So instead of having reps babysit sequences, the system works behind the scenes to keep momentum going.

8 account-based marketing examples that you can learn from

So what does all of this look like when it’s put into action?

Now that we’ve unpacked what makes a best-in-class ABM strategy tick in 2025, let’s shift from theory to practice. 

The following examples showcase real-world ABM campaigns, each with its own unique playbook, from hyper-personalized outreach to orchestrated multi-channel engagement. 

These aren’t just flashy stunts. They’re strategic, measurable efforts that drove pipeline, created real momentum, and sparked deals with high-value accounts.

Whether you're looking for creative inspiration, tactical ideas, or proof that ABM really works, these campaigns offer a front-row seat to what’s possible.

Let’s break them down.

1. Turning anonymous website traffic into pipeline: How Arc used Warmly to boost funnel conversion and 3x ROI

Challenge: Arc, a modern banking platform for venture-backed startups, operates in a fiercely competitive space where attention is scarce and timing is everything. 

For Basile Senesi, Arc’s CRO, the go-to-market strategy hinges on identifying high-intent buyers fast and engaging them before competitors do.

But like many early-stage teams, Arc faced a visibility gap. 

Thousands of weekly site visitors were flowing through their funnel, but sales had no idea who they were, what they were looking at, or when to reach out. 

Attribution was fuzzy. Outreach was reactive. And reps were losing valuable time chasing the wrong leads.

Solution: That changed when Arc implemented Warmly.

In under 30 days, Arc used Warmly to:

• Identify site visitors in real-time.
• Drop insights directly into Salesforce, Outreach, and Slack (where SDRs already lived).
• Automatically add high-fit visitors to personalized sequences.
• Alert reps the moment a key account hits a pricing page or demo request form.

Results:

1. Arc unlocked a 10–15% lift in funnel conversion.
2. Accelerated sales cycles.
3. Added 1-3 extra customers per month without expanding headcount. 
4. Got a 200% return on investment within 6 months, with a projected 3–5X ROI by year’s end.

This is a prime example of ABM done right: high-intent targeting, signal-based outreach, and operational efficiency that scales with the team, not against it.

2. Skipping the funnel: How StraightIn used ABM strategies to fast-track high-value accounts and close $10K in 2 weeks

Challenge: For LinkedIn marketing agency StraightIn, ABM was a necessity. 

With thousands of monthly site visitors coming in from paid and organic campaigns, the challenge wasn’t generating traffic. 

It was figuring out which accounts were worth pursuing and how to engage them in a relevant, timely way.

Their traditional demand gen approach relied on top-of-funnel marketing and broad outreach. 

But like many B2B teams, they realized that ABM was a smarter path: identifying high-fit accounts early, tailoring outreach, and orchestrating touchpoints across channels. 

Solution: That’s where Warmly came in.

Using Warmly’s AI Orchestrator, StraightIn turned anonymous website traffic into real-time account insights. 

They could now:

• Identify key stakeholders from in-market accounts the moment they hit their site.
• Segment visitors by job title, company size, and behavior, such as time on pricing pages or industry-specific blog posts.
• Trigger personalized outreach across LinkedIn and email tailored to each account’s interest and buying stage.

With these ABM workflows in place, they skipped the spray-and-pray and went straight to engagement. 

Leads from Warmly were automatically dropped into Salesloft and Salesflow campaigns, giving reps a warm context for follow-up and significantly increasing email open, click, and reply rates.

Even better, the team used Warmly’s first-party intent data to cut LinkedIn Ad spend while improving performance by building retargeting audiences based solely on high-fit, already-engaged accounts.

Results:

Within two weeks, StraightIn closed two deals totalling $10K, proving that an ABM motion, when powered by real-time engagement signals and automated outreach, doesn’t need months to start delivering ROI.

3. From anonymous clicks to high-intent conversations: How Caddis Systems drove a 500% conversion lift in 7 days

Challenge: For Caddis Systems, a niche manufacturing software provider with a lean, 3-person sales team, converting website visitors into pipeline wasn’t just a priority - it was a pain point. 

Despite running AdWords campaigns and cold outreach through an agency, their inbound motion lacked one crucial piece: visibility into which accounts were actually showing intent.

In short, their ABM motion was stalled before it even started.

Solution: Caddis Systems decided to implement Warmly.

In just one week, Caddis used Warmly to turn previously anonymous site traffic into targeted, real-time engagement with their ideal accounts, driving a 5x increase in website conversions and proving that even small teams can win big with smart ABM execution.

Here’s how it worked:

• Account identification - Warmly deanonymized site traffic and surfaced contact- and company-level insights in real-time, instantly showing Caddis which visitors matched their ICP.
• Live, high-intent engagement - Reps received Slack alerts when key accounts landed on high-value pages (like pricing or product docs), and jumped into conversations right then and there using Warmly’s Live Video Chat.
• Segmentation and prioritization - With AI Orchestrator, Caddis built dynamic segments to filter and route visitors based on source (e.g. ad campaigns) and behavioral signals, automating outreach only to high-fit accounts.
• Multi-channel orchestration - Leads from ads, email, and chat were nurtured across multiple touchpoints, creating a fluid, ABM-style journey personalized to each account’s engagement level and activity.

This way, instead of waiting for prospects to fill out a form or show blatant intent, Caddis built a proactive ABM system that met accounts where they were, based on real-time behavior, not guesswork.

Results:

1. 500% increase in website conversions.
2. Multiple qualified meetings from live chat.
3. 4-5x ROI in under 7 days.

Warmly didn’t just improve lead gen, it gave Caddis an actual account-based infrastructure, enabling their small team to behave like a much larger org. 

Their ABM playbook became automated, precise, and fast, just how modern GTM teams need it in 2025.

4. Connecting campaigns to pipeline: How Premikati uses Warmly’s Orchestrator and chatbot to scale ABM with precision

Challenge: When Premikati - a procurement and finance operations consulting company - launched multi-channel campaigns across LinkedIn and paid search, they saw promising traffic numbers but no clear insight into who was engaging or whether it was leading to pipeline.

That made it nearly impossible to prove ROI, prioritize spend, or follow up with high-intent accounts.

In short: Premikati was doing everything right, but couldn’t connect the dots.

Solution: By layering Warmly’s Orchestrator and AI chatbot into their go-to-market motion, Premikati transformed those disconnected clicks into a fully orchestrated ABM system - one where visitor identification, lead scoring, segmentation, and follow-up happen automatically.

Here’s what made it work:

• Real-time UTM tracking and deanonymization helped its team identify which campaigns were actually driving the right traffic, and from which channels.
• Warmly’s Orchestrator segmented site visitors by campaign, behavior, and buying stage, automatically enrolling them into relevant LinkedIn and email sequences.
• Instead of stopping at one contact, Warmly surfaced other key stakeholders from the same account, allowing Premikati to multi-thread and personalize follow-up based on roles and activity.
• Warmly’s AI chatbot handled initial engagement, qualifying inbound leads, and even booking meetings autonomously - something their previous chat tools never managed.

The result is an ABM strategy that proactively moves accounts through the funnel, using real-time signals and intent data to determine who to engage, how to follow up, and when to loop in reps.

And it’s working.

Warmly gave Premikati a clear view of ROI per channel, automated the middle of the funnel, and empowered reps to have more relevant, better-timed conversations. 

Results: 

1. More booked meetings.
2. More efficient workflows.
3. A marketing team that can now scale with confidence.

That’s a prime example of modern ABM: tightly orchestrated, dynamically segmented, and built to scale. 

5. Voice-led ABM at scale: How Connectteam used AI SDRs to increase engagement 5x and cut no-shows by 73%

Connectteam, a fast-scaling employee management platform serving frontline-heavy industries like construction, retail, and healthcare, had one core ABM challenge: how to personalize outreach across multiple verticals without overextending their SDR team.

With 120,000 phone calls handled monthly, a lean SDR org, and rising lead volumes, Connecteam’s ops leaders knew they needed to evolve their approach. 

Email and SMS weren’t cutting it, and cold outreach lacked the contextual relevance required for meaningful engagement. 

Plus, a 75% meeting no-show rate was throttling pipeline momentum.

Solution: Deploying Julian, an AI-powered SDR from 11x built to handle voice-based outreach at ABM scale.

Here’s how Connecteam brought ABM into the voice channel and made it work:

• Segmented, vertical-specific outreach - 11x embedded with Connecteam to tailor Julian’s outreach by industry, aligning messaging for retail, healthcare, and construction personas without requiring manual SDR input.
• Intent-based follow-ups - Julian reached out to leads based on behavior and funnel stage, reactivating old or cold opportunities that the sales team didn’t have bandwidth to pursue.
• Meeting scheduling and confirmation - Julian didn’t just call. He booked meetings, handled confirmations, and ran proactive follow-up sequences, slashing no-show rates by over 70%.

Results:

1. $450K+ saved annually on SDR salaries.
2. 73% drop in no-shows.
3. $30K monthly revenue lift per SDR.

For ABM teams looking to scale intelligently, Connecteam’s approach shows what’s possible when you blend vertical-specific messaging, AI-led orchestration, and real-time follow-up without growing headcount. 

It’s a bold reminder that ABM isn’t just about who you target - but how fast and personal you engage once intent is shown.

6. Scaling smart: How Everstage 2.5x’d sales engagement and doubled ABM match rates 

Challenge: Despite investing in multi-channel paid campaigns across LinkedIn and Google, Everstage - a sales commission platform- couldn’t track which accounts were engaging, what content was driving interest, or whether they were targeting the right prospects at the right time. 

Its tech stack, spread across Google Analytics, HubSpot, and spreadsheets, offered fragmented insights and poor account match rates. 

And when outreach did happen, it often lacked the precision needed to drive meaningful engagement.

Solution: The company rebuilt its ABM engine with Factors.ai at the center, and everything changed.

Here’s how Everstage transformed its account-based strategy:

• Centralized attribution and funnel analytics - With a unified view of their marketing funnel, Everstage could now see exactly which campaigns, pages, and segments were underperforming and fix them fast.
• Intent-powered segmentation - By layering in behavioral signals from G2, CRM, LinkedIn, and web data, Everstage was able to score and prioritize ABM accounts based on fit and buying intent.
• Outbound-ready insights - Sales and BDR teams gained account-level timelines that showed who engaged, when, and where, making personalized, timely outreach both easier and more effective.

Results:

• 2.5x increase in sales email engagement.
• Higher ROI per campaign.
• More efficient outbound workflows.
• Smarter targeting with reduced waste.

This is modern ABM in action: clean attribution, targeted engagement, and sales-marketing collaboration built around shared data.

7. From inefficient targeting to 40% pipeline growth: How Coalfire rebuilt its ABM engine from the ground up

Challenge: Coalfire, a cybersecurity advisory firm, had the fundamentals of account-based marketing in place but struggled with execution. 

Their campaigns were reaching the wrong accounts, lead quality was inconsistent, and fragmented attribution made it nearly impossible to connect effort with outcome.

In short, their ABM investments weren’t translating into revenue.

Solution: To fix that, Coalfire turned to Demandbase, using its AI-driven platform to unify targeting, improve account scoring, and drive smarter, data-backed decisions across the funnel. 

Here’s how they did it:

• Precision targeting powered by intent data - With real-time insights and predictive analytics, Coalfire redefined its ICP and focused outreach only on accounts showing relevant behavior, eliminating wasted ad spend and improving account engagement by 30%.
• Smarter segmentation and prioritization - Coalfire could now rank and route accounts based on interest, fit, and stage, so sales teams only pursued prospects that were both qualified and ready.
• Clear attribution - With campaign-level visibility, Coalfire could see exactly which programs were driving results, and which weren’t, enabling continuous optimization.

What followed was a complete transformation of Coalfire’s ABM motion, delivering measurable gains in pipeline, engagement, and sales alignment.

Results:

1. 40% increase in marketing-generated pipeline.
2. 25% higher lead-to-opportunity conversion rates.
3. 12% shorter sales cycle.
4. 45% lift in conversions for targeted campaigns.

8. Precision over volume: How PitchBook cut CPC by 38% and boosted deal size with targeted ABM ads

Challenge: PitchBook, a leading financial data and research firm, knew that traditional digital campaigns weren’t enough to move the needle with high-value accounts. 

It needed a way to drive demand, accelerate deal velocity, and better support their sales and customer success teams without wasting spend on low-fit prospects.

That’s where account-based advertising (ABA) came into play.

Solution: By partnering with RollWorks, PitchBook refined their ABM strategy from broad outreach to precision targeting, focusing their efforts on the highest-fit A and B-tier accounts across their funnel. 

Here’s what worked:

• Hyper-personalized advertising - Instead of generic display ads, PitchBook launched ads tailored by account name, product relevance, and lifecycle stage, creating relevance from the very first impression.
• Smart account prioritization - They streamlined from 10,000+ accounts to a tightly focused list of high-fit targets, cutting cost per click by 38% in just two weeks (from $29 to $18).
• Ad-informed sales timing - Marketing delayed sales handoff for cold accounts, ensuring reps reached out only after a full 30-day engagement window. This built brand familiarity and improved response rates.

Results:

1. 14.9% faster sales cycle.
2. 24.3% higher win rate on influenced deals.
3. 36.9% higher average deal size.
4. 31.8% of closed-won pipeline influenced by ads.

This campaign proves what effective ABM looks like in 2025: fewer accounts, deeper personalization, smarter handoffs, and tighter marketing-sales alignment. 

It’s not about more leads - it’s about the right accounts, engaged the right way.

What does the future look like for ABM?

ABM of the future will be more than just hyper-personalized.

It will also be predictive, autonomous, and orchestrated across every step of the buyer’s journey.

As GTM teams face pressure to do more with less, AI is becoming the engine behind next-gen ABM strategies. 

Instead of just identifying who to target, AI can now help decide when, where, and how to engage, and in many cases, it can execute that engagement autonomously.

I’m not just talking about scoring leads or generating insights. 

AI in ABM is now being used to:

1. Auto-prioritize accounts based on real-time intent signals from websites, email, chat, and third-party research intent.
2. Segment audiences dynamically based on fit and behavior, not static ICP rules.
3. Generate personalized messaging across email, LinkedIn, SMS, and ads at scale.
4. Automate outreach through AI SDRs, especially for warm but mid-priority leads that humans often can’t reach quickly enough.
5. Trigger full-funnel workflows, like warming up accounts with ad impressions, chatbot touches, and follow-up sequences, all without manual handoffs.

This is the foundation of what we call ABM 2.0 at Warmly.

Let’s say a VP of Operations at a target account visits your pricing page, interacts with your chatbot, and opens an email.

Well, Warmly picks that up in real-time. 

Instead of waiting for a rep to manually follow up, that contact is routed into a tailored AI SDR campaign powered by our integration with 11x. 

From there, autonomous AI SDR agents launch a personalized outreach sequence across email, LinkedIn, or even SMS, while your human reps focus on the highest-intent conversations.

In practice, that means:

• Warm leads get AI-powered outreach immediately, without adding SDR headcount.
• High-intent leads get flagged for human follow-up, with full context at their fingertips.
• Your pipeline grows passively, even when your team is offline.

This kind of AI-led orchestration flips the traditional ABM model on its head. 

Instead of running rigid campaigns in quarterly bursts, you're now operating a 24/7, signal-based system that adapts in real time and meets buyers wherever they are in their journey.

Looking ahead, we’ll see even more intelligent use of AI in ABM:

• Fully autonomous research agents that enrich leads and accounts before any contact is made.
• AI-generated playbooks that build dynamic and personalized cadences based on buyer behavior patterns.
• Predictive engagement timing, where AI not only suggests who to reach out to, but when they’re most likely to respond, etc.

The bottom line? 

The future of ABM is no longer limited to identifying high-value accounts. It’s about orchestrating the entire buyer experience, powered by data and executed (in part) by intelligent automation.

And if that sounds complex, it doesn’t have to be. 

With platforms like Warmly, AI isn't replacing your team. 

It’s amplifying their reach, optimizing their time, and making sure no opportunity slips through the cracks.

Next steps: From inspiration to execution

Account-based marketing in 2025 isn’t about doing more - it’s about doing smarter.

As these examples show, the most successful ABM strategies aren’t necessarily the flashiest.  They’re simply the most intentional. 

They combine real-time data, smart segmentation, and personalized engagement to connect with the right people, in the right way, at the right time.

And increasingly, they’re powered by AI, from autonomous SDRs running outreach in the background to signal-based lead scoring that ensures reps never miss a high-intent opportunity.

Whether you’re refining an existing ABM motion or building one from the ground up, the takeaway is the same: ABM today is about orchestration, not just outreach. 

And that orchestration starts with the right tools.

If you’re ready to turn anonymous web traffic into warm pipeline, run personalized outreach at scale, and build a truly adaptive ABM system, Warmly can help.

Book a demo today to see how Warmly’s signal-based platform can help you identify, prioritize, and engage the accounts that actually convert.

Read more

• Account-Based Marketing vs Demand Generation: How Are They Different? [2024] - Unpacks the key differences between ABM and demand gen, including audiences, goals, tactics, and when to use each.
• 6 Tangible Benefits of Account-Based Marketing (ABM) - A breakdown of six clear, measurable advantages of using ABM to drive pipeline and boost revenue efficiency.
• What is Person-Based Marketing & Why It’s Better Than ABM - Explore how person-based marketing goes beyond account-level targeting to drive deeper, 1:1 engagement.
• Agentic AI For Marketing: Best Use Cases & Software In 2025 - Discover how autonomous AI agents are transforming marketing workflows from campaign ops to content and beyond.
• 10 Best AI Agents for Digital Marketing in 2025 [Reviewed] - A curated list of top AI agents helping digital marketers automate, personalize, and scale their efforts in 2025.
• AI Marketing Strategy: Top Use Cases and Tools - An outline of proven AI marketing strategies, with examples and tools that drive results across the full funnel.
• 10 Best Account-Based Marketing Software (ABM) in 2024 - A side-by-side review of the leading ABM platforms, comparing features, pricing, and best-fit use cases.

Finding good data is critical for any GTM organization. As the data landscape becomes increasingly complex, selecting the right B2B data providers is crucial for achieving business success. 

According to one survey, 66% of B2B and B2B2C marketers say improving data quality is a key part of their go-to-market (GTM) strategy. Additionally, data quality is crucial when developing AI tools, such as custom chatbots or AI-powered sales agents. 

As a signal-based orchestration platform, Warmly integrates with over 25 leading data providers, and our team rigorously assesses approximately 20 new providers monthly.

To hone and refine our process, we interviewed 20 Demand Generation leaders who have purchased data from hundreds of B2B data providers in their careers, developing our Data Vendor Decision Framework within our Data Team.

TLDR: You should consider more than just the quality of data when choosing a data vendor. Our Decision Framework highlights six essential factors that contribute to the overall quality of a B2B data provider: data quality, data quantity, ease of use and implementation, partnerships, legality and compliance, and data cleanliness. 

For each factor, we’ve provided clear, actionable steps, including pre-work, evaluation methods, and key red flags to be aware of.  

By evaluating all six factors for each vendor you’re considering, you’ll gain a complete picture of quality and reliability.

Six Factors to Consider When Choosing a B2B Data Provider

1. Quality of data
2. Quantity of data
3. Ease of Use & Implementation
4. Partnership Meter
5. Legality & Compliance
6. Cleanliness & Data Integrity

Resources

Email us at [email protected] for a sample CSV of Test Data for testing company-level matching for Website Identification.

Email us at [email protected] for a sample CSV of Test Data for testing person-level enrichment for Outreach.

1. Quality of Data

The quality of data has a direct impact on business decisions, making it a key consideration for organizations.  

Pre-work

Prepare test data, including examples from current vendors and internal sources. Include ideal customer matches and some incorrect data as a control test.

• Ensure that the test data represents your industry, target audience, and business use case.
• Consider including data from multiple sources to compare accuracy across different providers.

Evaluate

What percentage of your Ideal Customer Profile (ICP) data does the provider match? Ensure they do not validate incorrect data.

• Request sample reports and conduct manual spot checks on key data points.
• Assess whether the provider offers validation mechanisms to minimise inaccuracies.

Why It Matters

No data source is perfect. A provider that correctly identifies 60% of your ICP is performing well. Unrealistically high match rates can indicate low-quality data (they are truly guessing to achieve high results).

• High match rates may indicate that the vendor employs unreliable data aggregation techniques.
• False positives can be more damaging than missing out on some matches. Imagine sending a sales rep to work hundreds of false positive leads that never convert; that’s a massive waste of time.

Red Flags

If a provider claims matches on obviously incorrect data, it's a major warning sign. 

• Look for transparency in their data sourcing and cleansing methodologies.
• Avoid vendors who do not disclose their data verification processes.

2. Quantity of Data

When assessing data volume, consider:

Pre-work

Generate a large sample set (10k+ leads or IPs) for enrichment.

• Ensure the sample includes a diverse range of potential customers.
• Include identifiers like company names, domains, and other referenced data.

Evaluate

How much of your sample set does the provider match?

• Assess both absolute match rates and coverage within your target market.
• Compare results across multiple vendors to benchmark performance.

Why It Matters

Higher match rates indicate a broader reach, even if some leads fall outside your ICP.

• Some vendors specialize in niche datasets, while others offer broader but less precise data.
• A good vendor provides balanced depth and breadth of data.

Red Flags

A provider offering only one match per lead lacks depth. The best vendors provide multiple options ranked by confidence level.

• Ensure the vendor ranks and segments the data appropriately.
• Look for metadata that indicates data freshness and reliability (for example, a timestamp of the last time that data point was validated).

3. Ease of Use & Implementation

Even high-quality data is ineffective if it is challenging to implement.

Pre-work

Review technical documentation and plan a testing timeline. 

• Refer to the API documentation for clear integration instructions.
• Look at case studies or testimonials about implementation experiences.

Evaluate

Do they offer flexible APIs, real-time updates, and timely flat-file deliveries?

• Assess data refresh frequency and latency.
• Verify if they support standard data formats (e.g., CSV, JSON, XML).
• Observe how quickly they communicate with you during the testing phase.

Why It Matters

Quick, seamless integration indicates vendor maturity and minimizes operational delays. 

• A well-structured API or easy import process reduces engineering effort.
• Smooth onboarding is a sign of a strong customer support team.

Red Flags

A lack of clear service-level agreements (SLAs), low uptime commitments, or slow response times can signal potential future problems. Any vendor that has been around for less than three years.

• Ensure the vendor commits to 99.9% uptime for API reliability. 
• Confirm their response times for technical support inquiries.

4. Partnership Meter

Even the best B2B data providers can struggle to build strong relationships with their customers. However, partnership quality can be a significant factor in your overall experience with a data vendor. 

Pre-work

Conduct reference checks.

• Speak with current or former customers about their experience. 
• Research vendor reputation on platforms like G2 or Capterra.

Evaluate

Are they invested in long-term success, or do they prioritize short-term profits? 

• Look for signs of continued innovation in their roadmap.
• Assess whether they provide strategic support beyond just selling data.
• Quiz them on their strengths and weaknesses. Are they honest about their shortcomings?
• Will they work with you to get started (pay-as-you-go) and understand volume-based usage, and help you stabilize known costs in the long run (e.g., switch to an unlimited data model once you know usage)?

Why It Matters

Trust and alignment are crucial. The best vendors are partners, not opportunists.

A good vendor should offer flexibility, training, and collaborative problem-solving. Avoid companies that rely on opaque pricing or aggressive upselling.

Red Flags

Extremely low pricing often indicates high customer churn and a lack of commitment.

• Include a mandated 90-day migration window in contracts to protect against sudden service drops.
• Ensure contract terms include exit flexibility without penalties.
• Look for vendors who offer long-term engagement strategies (e.g., multi-year contracts).
• If they cannot confirm contractually, they will never sell your data to others.

5. Legality and Compliance

Data sources must be legally obtained. To verify compliance:

Pre-work

Request and review legal documentation, including Data Processing Agreements (DPAs) and privacy policies.

• Confirm compliance with GDPR, CCPA, and other relevant regulations.
• Ensure vendors provide explicit consent and opt-out mechanisms.

Evaluate

Confirm compliance with GDPR, CCPA, and other regulations. Ensure transparency in data collection. 

• Look for certifications such as ISO 27001 or SOC 2.
• Verify whether they regularly update their compliance processes (e.g., which privacy lawyers do they work with to stay informed about new and upcoming privacy laws).
• Ensure they’re a registered data broker and have them send confirmations of registration for each state for the current calendar year (as of 2025: California, Vermont, Oregon, and Texas).
• Understand their opt-out processes for individuals who wish to have their data removed or hidden.

Why It Matters

Protects your company from legal risks and maintains customer trust.

• Data privacy violations can lead to hefty fines and reputation damage. 
• Transparent vendors provide audit trails and clear accountability.

Red Flags

Vendors unwilling to provide documentation or those with vague sourcing details should be avoided. 

• Avoid companies that lack a dedicated Data Protection Officer (DPO).
• Ensure they disclose data retention and deletion policies.

6. Cleanliness and Integrity

Clean data is essential for accurate insights. To evaluate cleanliness:

Pre-work

Request documentation on data validation, update frequency, and duplicate detection. 

• Verify if they conduct manual review processes in conjunction with automation.
• Verify how frequently their datasets are refreshed.

Evaluate

What processes are in place to maintain data accuracy and integrity?

• Look for machine-learning-driven duplication and validation techniques. 
• Assess whether they offer enrichment tools to improve data quality.

Why It Matters

Outdated or incorrect data can lead to misinformed business decisions and wasted resources. 

• Clean data ensures higher accuracy in targeting and analysis.
• Efficient data hygiene practices reduce manual cleanup efforts.

Red Flags

No clear strategy for removing outdated information or for a lack of regular data quality audits. 

• Avoid vendors who cannot articulate their data hygiene process.
• Ensure they provide transparency into error rates and data refresh cycles.

Evaluating B2B Data Providers

The best data vendor isn't necessarily the cheapest or the one with the most data; it's the one that aligns best with your needs and prioritizes a long-term partnership. 

Leaders should focus on quality, quantity, ease of use, partnership, legality, and cleanliness to make informed vendor selections. 

If you’re looking for a data vendor that can pass muster, look no further than Warmly. Our dedicated data team has spent years developing our data sets and ensuring we are a great, compliant data provider for you.

How Does Warmly Stack Up Against B2B Data Providers?

1. Quality of data ✅

Warmly’s transparent data commitment means you can test our data quality with our free tier before committing to us as a data provider. Because we aggregate data from 25+ providers and cross-check it using our proprietary waterfall technique, we can validate and verify data on your behalf, ensuring it’s of the highest quality. See more in our overview of data quality.

‎

A great example of this is our Data Quality Slider, a unique feature that lets you maximize data quality (at the expense of data quantity) if you prefer. We can also use AI to help you in scoring leads and filtering data to identify the best warm leads for you.

2. Quantity of data ✅

Warmly’s transparent data commitment means you can test our data quantity with our free tier before committing to us as a data provider. Because we aggregate data from 25+ providers and cross-check it via our waterfall technique, we can validate and verify on your behalf to give the highest quantity of data. See more in our overview of data quality.

A great example of this is our Data Quality Slider, a unique feature that lets you maximize data quantity (at the expense of data quality) if you prefer. Most of our datasets are updated daily, and some are updated weekly to ensure freshness.

Feel free to compare our data quality vectors with those of another industry-leading data aggregator, 6sense.

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3. Ease of Use & Implementation ✅

With Warmly, you have complete control and flexibility over your data as you can:

• Export data via CSV.
• Export data via Webhooks.
• Push the data into your CRM.
• Push the data directly to your preferred outbound/outreach providers via our integrations (e.g., email providers like Outreach, Salesloft, and HubSpot).

We stand behind our customer reviews—see more on our reviews page and compare our Ease of Setup, Admin, and Use vectors with those of other similar services in our space.

‎

4. Partnership Meter ✅

Warmly is a genuine partner. We’re here to offer transparent and communicative offerings that respect your time. 

Our best-in-class customer service organization stems from years of experience in B2B data companies, and our RevOps and GTM experts are here to provide you with GTM consulting and GTM motion architecture, in addition to warm lead data. 

We are committed to driving ROI for you every step of the way, reviewing your data and that of our dozens of data providers to help you make informed decisions about your lead generation strategies.

We ensure that all our data providers are partners and provide us with essential levers, such as migration windows, flexible pay-as-you-scale models, and assurances that they will not sell any data with signed data processing agreements.

We want you to relax while we handle the negotiations and dealings with 1st, 2nd, and 3rd-party data providers.

5. Legality and Compliance ✅

Warmly is compliant with GDPR, CCPA, and SOC 2 security. Learn more at our security portal, our privacy FAQ, or email our privacy team at [email protected].

We conduct randomized privacy audits of our vendors to ensure that all vendors are registered data brokers and comply with all relevant standards.

While not required, Warmly is a registered data broker in all US states where compliance is mandated (our privacy team updates and checks this monthly).

All our data retention and deletion policies are downloadable and transparent from our security portal but from a high-level we can delete your data on demand, respond quickly to individual data deletion requests (see our compliant opt-outs here) as well as if you cease to become a customer we will delete your data within 30 days.

Contact our Data Protection Officer, Uri Steinfeld ([email protected]), with any questions.

6. Cleanliness & Data Integrity ✅

Warmly ensure clean data and data integrity as the cornerstone of how we create, collect, and distribute data. Request an NDA from your Warmly representative to gain access to our Technical Deep Dive and learn how we process data to maximize quantity, quality, and compliance. 

Because we deal with many B2B data providers, we need to merge these datasets appropriately into a clean, simplified, and de-duplicated database of records. Although no data is perfect, our cleansing process is performed daily and ensures that no duplicate data is ever added to your CRM.

Warmly: Comprehensive Data for Signal-Based Selling

The checklist above should serve as your first port of call when evaluating a new data provider. As you can see, Warmly ticks all the boxes in one solution.

Our blend of 1st, 2nd, and 3rd-party data ensures you get accurate, real-time, person-level de-anonymization data to help you identify your warmest leads and reach out to them immediately.

Ready to give Warmly a go?

Sign up for Warmly’s free plan and start exploring how our data can help you identify quality prospects instantly.

Or, book a demo to explore our data in more detail.

Additional Resources

These are our recommendations for continued learning on data vendor evaluation:

• Dataversity - Data management trends and insights.
• TDWI - Research and training in data warehousing.
• Data Quality Campaign - Tools for assessing data quality.
• G2 Data Providers - User reviews on data vendors.
• Capterra Data Providers - Software comparisons and insights.

Read More

• Best B2B Data Providers: Find the optimal B2B data platform for your use case.
• Best Lead Intelligence Software: Find the best platform for gaining critical insight into your leads.
• Best GTM Tools: Optimize your GTM strategy with some of the best GTM software on the market today.
• Warmly vs. ZoomInfo: A direct comparison of Warmly and ZoomInfo.

ZoomInfo vs. 6sense: Find out what the strengths and weaknesses of ZoomInfo and 6sense are in this comparison guide.

AI in sales is not a thing of the future - it’s already here.

From lead qualification and pipeline prioritization to full-blown outbound orchestration, AI is transforming how sales actually gets done, helping teams work smarter, close deals faster, and scale with precision.

But forget vague promises.

In this article, we’ll be diving into real-world AI in sales examples, including the workflows, tools, and strategies modern revenue teams are already using to win more with less effort.

Whether you're exploring AI for the first time or looking to uplevel your current stack, these examples will give you the clarity (and inspiration) you need to make it work.

Let’s get into it.

How is AI used in sales in 2025?

Within just a few years, AI has gone from a futuristic add-on to a core pillar of modern sales operations. 

Today, it’s not just about automating busywork - although that’s still one of its most widespread use cases. Instead, it’s about making sales teams faster, sharper, and more scalable.

Modern AI doesn’t just sit in the background running scripts. 

It actively helps sales reps prioritize the right accounts, personalize outreach at scale, spot buying signals, and even predict which deals are most likely to close. 

It learns from historical patterns, analyzes real-time behavior, and adapts based on context, giving reps the edge they need in competitive markets.

But here’s the real shift: AI is no longer limited to isolated tasks like email writing or call transcription. 

We're seeing the rise of agentic AI, that is, smart systems that can autonomously execute multi-step sales workflows with minimal human input. 

Think of outbound campaigns that launch, learn, and iterate on their own.

In the next section, we’ll look at exactly how sales teams are applying this tech in the wild with real-world examples of AI:

• Driving pipeline.
• Boosting conversions.
• Reshaping how revenue gets built.

Top 7 ways you can use AI in sales

Now that I’ve covered the basics of how AI is reshaping the sales landscape at a high level, let’s get more specific. 

What does this actually look like in action?

The first thing you need to understand is that the most effective sales teams aren’t using AI as just another tool.

Instead, they’re building their workflows around it. 

From intelligent outreach to pipeline forecasting, AI is being embedded directly into daily sales operations in ways that save time, increase precision, and drive results.

Below, I’ll walk you through some of the most impactful ways AI is being used in sales right now - many of which we’ve tested ourselves and have seen make a real difference in how teams operate and drive revenue.

1. Outbound that scales without burning out your team

Outbound prospecting is one of the most resource-intensive parts of sales. 

It takes time, research, coordination, and consistency to do it well. 

But as teams push to hit bigger pipeline goals with the same - or smaller - headcounts, the old way of doing outbound just doesn’t scale.

That’s where AI-powered outbound steps in.

Instead of relying on reps to manually build lists, write outreach, and follow up across dozens (or hundreds) of accounts, AI can take on much of that legwork. 

And not just basic automation. We’re talking about outbound that adapts in real-time to signals, personas, and past interactions.

We’ve put this into play with Warmly’s AI SDR feature, and the difference is immediate. 

The system can:

• Handle prospecting for thousands of accounts simultaneously.
• Tailor messaging based on industry, buyer intent, or job title.
• Adjust sequences on the fly based on engagement (clicks, replies, ghosting).
• Work across multiple channels, not just email.

It’s like giving your team an always-on sales assistant who never forgets to follow up, never sends a generic message, and never gets tired.

This way, instead of deciding who gets your attention, you can start covering more ground, focusing on high-value leads without sacrificing quality or personalization.

2. AI chatbots that actually feel human

Let’s be honest: most chatbots still feel like you’re yelling into the void. 

They follow rigid scripts, fail to understand intent, and often leave prospects more frustrated than informed. 

But recently, AI chat has significantly levelled up, especially when it’s tuned to the right signals.

Today, chatbots are not just about answering simple questions - they’re about starting meaningful conversations that adapt in real-time based on who the visitor is and what they’re trying to do.

That’s exactly what we had in mind when designing Warmly’s AI Chat. 

This AI-powered chatbot doesn’t just sit passively on your website. Instead, it engages visitors proactively based on behavior, past interactions, and buying intent. 

So, if someone’s poking around your pricing page or returning after a missed meeting, it knows how to tailor the message - a “Welcome back” here, a demo offer there, or quick access to key resources if someone’s in research mode.

It also stays completely on-brand. You can train it with the same messaging your reps use, so it reflects your tone, value prop, and positioning perfectly.

This means that when done right, AI chatbots can:

• Qualify leads instantly, without asking them to fill out a form.
• Respond dynamically based on real-time visitor signals.
• Surface high-value offers at just the right moment.
• Book meetings while your team sleeps.

This way, you get conversations that convert, plus a whole new way to engage high-intent leads around the clock without burning out your human reps.

3. Automated lead nurturing

Following up is one of those things everyone knows they should do, but it’s also one of the easiest to let slide. 

A lead books a demo, misses it, never replies... and before you know it, they’ve disappeared from the funnel entirely. 

Multiply that by dozens of leads a week, and the cracks start to show.

And why should you care?

Well, research shows that companies that excel at lead nurturing generate 50% more sales-ready leads at a 33% lower cost per lead. 

That’s where automated lead nurturing powered by AI steps in to save the day.

Instead of relying on manual reminders or hoping your reps remember who to follow up with, AI can automatically track lead behavior and re-engage at the right moment through personalized emails, LinkedIn messages, or even in-site chat prompts.

We’ve seen this in action with Warmly’s nurturing workflows run by the AI SDRs and the Orchestrator, which are designed to keep every lead moving. 

What makes it work is the contextual awareness:

• Each message adapts to where the lead is in their journey.
• Timing is optimized based on engagement signals.
• Sequences can span multiple channels (email + LinkedIn) for higher visibility.
• No lead gets left behind just because your team got busy.

This kind of automation is all about making sure no opportunity slips through the cracks. 

And when your follow-up game is this consistent, it’s only a matter of time before it starts showing up in your conversion rates.

4. Smarter lead scoring that helps reps focus where it counts

Not all leads are created equal, but traditional lead scoring often treats them like they are. 

Someone opens a newsletter? +5 points. Downloads a case study? +10. 

But that kind of static, rules-based approach doesn’t capture real buying intent, and it definitely doesn’t keep up with how buyers behave in 2025.

That’s where AI-driven lead scoring comes in.

It uses machine learning to analyze everything from firmographics to on-site behavior, CRM history, and real-time engagement signals to predict which leads are most likely to convert. 

Instead of just tracking activity volume, AI focuses on conversion patterns, surfacing the leads that actually move the needle.

You can see this firsthand with Warmly’s AI-powered ICP identification and signal monitoring. 

Instead of just scoring leads based on broad criteria, Warmly helps you:

• Define your ICP using deep, AI-driven research, not just basic firmographics.
• Monitor real-time buying signals across site visits, CRM enrichment, and de-anonymized data from 10+ providers.
• Automatically enrich and prioritize lead segments with contextual data.
• Route hot leads to the right rep instantly, with Slack alerts and CRM-ready notifications.

This means you’re not just guessing who to reach out to - you know beforehand who’s most likely to be interested in what you have to offer. 

Your reps will be spending more time in front of qualified leads and less time chasing dead ends.

It’s like having an AI-powered filter on your entire funnel, so what comes through is warmer, faster-moving, and way more likely to close.

5. Real-time pipeline visibility without the guesswork

Forecasting has always been part math, part magic. 

Sales leaders rely on CRM reports, rep gut feel, and last-minute spreadsheet gymnastics to predict what’s coming in. 

But with complex deal cycles, shifting buyer behavior, and distributed teams, it’s no surprise that forecasts are often off the mark.

AI is changing that by turning guesswork into clarity.

In 2025, the best-performing teams are using AI to track pipeline health and predict outcomes with far more accuracy. 

These tools analyze historical deal data, rep activity, buyer engagement, intent signals, and even deal velocity to flag risks early and highlight what’s most likely to close.

As a result, you’ll be able to:

• Understand which deals are moving and which are stalling.
• See intent patterns in real time across entire accounts.
• Make faster decisions on where to focus, without waiting for end-of-quarter reviews.

What’s especially powerful is how early these systems can surface issues:

Before a deal goes cold, before a quarter slips away, and definitely before your team wastes time on pipeline that was never real to begin with.

When AI becomes your co-pilot for forecasting, your sales process becomes a lot less reactive and a lot more predictable.

6. Real-time call intelligence that helps reps close faster

Sales calls are high stakes. 

They’re where you build trust, handle objections, and move deals forward. 

But let’s be real: in the moment, it’s easy to miss buying signals, skip a discovery question, or mishandle a pricing objection. 

And traditional coaching? It usually happens after the fact, when the momentum’s already gone.

That’s why real-time call intelligence has become a must-have.

Tools like Gong, Fireflies, and Chorus now do more than transcribe calls. 

They coach reps in real-time, suggesting relevant talk tracks, surfacing competitor mentions, and even flagging when a deal is at risk mid-conversation. 

For newer reps, it shortens the ramp-up time. For experienced ones, it keeps them sharp.

What’s just as important, though, is what happens before the call starts. That’s where Warmly’s AI Co-Pilots make a big difference.

Before a rep even joins the call, Warmly helps them:

• Identify who’s most worth talking to, based on real-time website behavior and AI-modelled intent signals.
• Personalize their outreach as Copilot breaks down why a lead is interested and even suggests what to say.
• Figure out when to transition to a face-to-face video call, turning website chats into meaningful, human interactions that build trust faster.

This combination of pre-call AI context and in-call intelligence creates a compounding advantage: your reps aren’t just reacting anymore.

Instead, they’re leading conversations with the right people, at the right time, with the right message.

And when every second on a call counts, that edge can make all the difference.

7. Personalization at scale, without the manual grind

We all know personalized outreach works. It gets more replies, builds better rapport, and ultimately converts more leads. 

The problem? Doing it well doesn’t really scale. 

Most reps either spend too much time researching every prospect or settle for generic templates that feel like spam.

AI can successfully bridge that gap.

Namely, AI can instantly generate relevant, contextual, and human-sounding messages based on real data, such as what a prospect cares about, what stage they’re in, and what’s actually going to resonate.

For example, Warmly’s Orchestrator automatically personalizes and sends messages to key stakeholders of surging accounts, using essential B2B data, intent signals, and previous interactions to tailor each message to perfection. 

It’s not just “insert {{first name}} and hope for the best.” It’s real personalization, driven by real context across hundreds or even thousands of leads.

This kind of scalable personalization helps you cut through the noise, increase reply rates, and focus rep time where it matters most - talking to the right people, with the right message, at the right time.

10 real-world AI in sales examples that you can learn from

It’s one thing to talk about what AI can do in sales and another to see it working in the wild because while theory is helpful, execution is where the real learning happens.

In this section, we’re looking at actual companies using AI to improve prospecting, close deals faster, and scale revenue right now. 

From fast-growing startups to established enterprises, these examples show how AI is being applied across different parts of the sales process and what results teams are seeing as a result.

Whether you're building your own AI playbook or just exploring what’s possible, these stories offer practical takeaways, proven strategies, and a few creative ideas worth stealing.

1. How Premikati used AI to turn anonymous traffic into qualified pipeline

Challenge: Like many B2B teams, Premikati was running multi-channel marketing campaigns but struggling to connect the dots between site traffic and real results. 

Despite getting decent volume from PPC and LinkedIn, they lacked the visibility to attribute leads, track ROI, or prioritize high-value prospects.

Solution: Enter Warmly’s AI-powered Orchestrator and AI Chat.

By combining real-time de-anonymization with signal-based segmentation, Warmly gave Premikati’s team deep insight into who was landing on their site, where they came from, and what they were doing once they arrived. 

No more guessing which campaign worked, as AI connected the dots across UTM links, page visits, and research intent.

Once identified, leads were scored and routed into personalized automated outbound sequences through Warmly’s AI Orchestrator, which was fine-tuned to:

• Identify high-intent leads matching Premikati’s ICP.
• Reach out to those leads in highly personalized LinkedIn and email sequences, leveraging the deep insights Warmly has on each lead.

And with Warmly’s AI Chat, Premikati could finally engage and convert inbound visitors instantly with no human intervention needed.

“We booked a qualified meeting from Warmly, which has never happened with our previous chatbots.” - Michael Buczynski, VP of Marketing.

Moreover, reps could now monitor live chat sessions, be looped into conversations with warm leads, or let the bot handle bookings thanks to AI that adapts to visitor signals in real-time.

Results:

• Better visibility into campaign performance.
• More meetings booked from inbound traffic.
• Scaled outreach with fewer manual steps.
• Expanded reach within buying committees.

💡Takeaway:

If you’re running paid campaigns without real-time lead tracking and AI-driven follow-up, you’re flying blind, as all the qualified website traffic will fall through the cracks.

Use AI to segment traffic, personalize engagement, and orchestrate outreach automatically, so every visitor has a path to pipeline.

2. How Kandji used a sophisticated AI-powered chatbot to book 2 qualified meetings in just 8 minutes

Challenge: Kandji, an Apple device management platform, needed a faster and more scalable way to turn website visits into real sales conversations without burdening its sales team with more manual work. 

Like many high-growth companies, they were looking for ways to generate pipeline more efficiently without sacrificing personalization or timing.

Solution: Kandji adopted Warmly’s AI Chat to engage visitors at the exact moment of interest. 

The AI chatbot delivered personalized, company-specific messages based on real-time visitor identification, and it did so without reps needing to monitor the site around the clock.

Just weeks after implementing Warmly, Kandji’s team saw the impact: two qualified meetings were booked within 8 minutes.

Slack notifications alerted their reps the moment a high-intent lead responded to the AI, allowing the team to jump into the chat, continue the conversation as real humans, and guide prospects straight into booked calls. 

It was a seamless handoff from Warmly’s AI to Kandji’s sales team.

Results:

• 2 qualified meetings booked in less than 10 minutes.
• Increased inbound engagement with minimal human effort.
• Personalized experiences delivered at scale.

💡 Takeaway:

Timing matters more than ever. 

With AI-powered chatbots, you don’t need a rep online 24/7. You just need to be ready when it counts. 

Set up real-time alerts, craft smart AI responses, and create seamless handoffs. 

That’s how you turn intent into action at scale.

3. How StraightIn closed $10K in 2 weeks with AI-powered prospecting

Challenge: StraightIn, a LinkedIn marketing agency, had strong website traffic and active email and social campaigns, but struggled to identify who was actually visiting their site and where they were in the buying journey. 

Without clear visibility into intent signals, much of their demand gen effort was flying blind.

Solution:

Using Warmly’s AI Orchestrator and real-time visitor de-anonymization, StraightIn began tracking high-intent leads the moment they hit the site. 

Try it yourself 👇or watch it in action. 

💡Note: You will need to be on one of Warmly’s paid plans to gain access to AI Prospector. For ARC, the ROI was 200% over 6 months. 

Instead of wasting time nurturing cold prospects, the team shifted to targeting only warm visitors - people actively showing buying intent through behaviors like pricing page visits and deep scrolls.

Here’s the workflow StraightIn’s team built with Warmly’s AI Orchestrator:

• The AI feature screened for website visitors ready to buy based on granular firmographic and behavioral data and ICP fit.
• Once identified, high-intent leads were automatically segmented and added to personalized email and LinkedIn sequences.
• Some leads were also added to LinkedIn Ads campaigns, eliminating unnecessary ToFu spend.

Results: 

• Two deals closed from LinkedIn in just two weeks, totalling $10K in new revenue.
• Email engagement shot up: +9% open rate, +6% CTR, and +1% positive replies.
• LinkedIn ad spend dropped significantly while conversion quality improved.

💡 Takeaway:

The fastest way to boost ROI is to stop chasing cold leads. 

Use AI to identify high-intent visitors early, segment them smartly, and automate outreach where it matters. 

You’ll move faster, spend less, and close more, just like StraightIn did.

4. How Connectteam scaled outreach and cut no-shows by 73% using an AI SDR

Challenge: Connectteam, an all-in-one employee management app, was scaling fast, but its SDR team was maxed out. 

Traditional email and SMS campaigns weren’t cutting it, especially for reactivating older leads. 

With no bandwidth to hire more reps, and a painful 75% meeting no-show rate, the team needed a way to personalize outreach and increase capacity without adding headcount.

Their goal was to re-engage cold and closed-lost leads, reduce no-shows and keep demos full, while avoiding scaling costs and operational complexity.

Solution: Connectteam turned to 11x, deploying “Julian,” an AI-powered SDR designed to make personalized phone calls, schedule meetings, and follow up automatically. 

Julian did more than just handle cold calls, though. He monitored intent, followed up with closed-lost leads, and confirmed meetings in real time.

Results:

• Meeting no-shows dropped by 73%.
• Each SDR generated ~$30K more revenue without hiring.
• Outreach tailored by vertical, powered by real-time behavior and signals.
• Missed and stale leads re-engaged with intent-based phone outreach.

And now? 

Warmly has partnered with 11x, meaning teams can bring this same AI SDR power directly into our sales stack alongside Warmly’s existing AI capabilities, lead nurturing, and signal-based outreach capabilities, unlocking a whole new world of opportunity for our customers.

💡 Takeaway:

AI SDRs don’t just replace repetitive work.

They unlock new opportunities by engaging leads you couldn’t reach before. 

Whether it’s booking meetings or reviving cold accounts, adding an AI phone rep can immediately increase revenue without increasing headcount.

5. How InvestNext boosted reply rates by 30% with AI-personalized outreach

Challenge: InvestNext, a real estate investment management platform, had a strong value proposition, but their outbound sales motion was struggling to scale. 

Personalizing each cold email took 15–20 minutes per lead, which wasn’t sustainable for their lean sales team.

With competition growing and inboxes getting noisier, they needed a way to scale outreach without losing personalization and break through in a saturated market,

Solution: InvestNext adopted OneShot.ai, an AI-powered personalization engine designed to create smart, tailored email outreach at scale.

Rather than sending one-size-fits-all messaging or burning rep hours on manual copy-pasting, OneShot.ai automates high-quality personalization, customizing content by persona, company, and context. 

This way, InvestNext got more engagement, more replies, and more deals without hiring more reps.

Results: 

• 30% increase in reply rates (highest in company history).
• 25% lift in open rates.
• 75% reduction in time spent personalizing emails.
• Multiple deals closed from email-only sequences.

💡 Takeaway:

Scaling personalization doesn’t have to mean sacrificing quality. 

With AI, you can send better emails faster and free up your reps to focus on what actually moves the deal forward. 

If you’re still writing every cold email by hand, it might be time to let AI take the first shot.

6. How a BPO scaled outbound calls to 500K+ patients using an AI-powered virtual assistant

Challenge: This Dallas-based BPO was growing fast, but growth brought pressure. 

With call volumes spiking and a lean workforce, the leadership team needed a way to scale without compromising customer experience or blowing up cost per call.

One urgent use case was outreach on behalf of Medicare: informing qualifying members about free COVID-19 test kits and collecting confirmation for fulfilment. 

But there was a catch: the campaign had to go live within one week, and hiring 130 new agents to handle the expected call volume wasn’t realistic.

Solution:

The BPO partnered with Uniphore, deploying the U-Self Serve intelligent virtual assistant (IVA) to automate outbound calls at scale.

Within days, Uniphore’s team integrated the IVA with the BPO’s existing dialer and scripted voice flows using studio-quality voiceovers to replicate a human agent experience. 

The assistant was trained to confirm test kit requests, answer FAQs, and escalate complex cases to live agents with full context, enabling a smooth handoff.

What would have required 130 agents was now handled by a scalable AI layer at a fraction of the cost.

Results:

• 500K+ Medicare members engaged.
• Real-time FAQ handling and confirmation without human reps.
• Rapid go-live in under 1 week.
• ~$2 saved per call in operational costs.

💡 Takeaway:

AI doesn’t just reduce support costs. It unlocks entirely new outreach campaigns that would otherwise be too expensive or resource-heavy to run. 

For lean teams under pressure to scale, virtual assistants offer a fast, flexible path to reach more people, faster.

7. How Whatfix built a more confident sales team with AI-powered knowledge access

Challenge: Sales success isn’t just about product features - it’s about confidence. 

At Whatfix, a digital adoption platform, new reps often struggled to find the right information at the right time. 

The key issue was that salespeople aren't proactive learners by nature. They need knowledge delivered when it's immediately relevant, not weeks in advance.

But with content spread across documents, slides, and sales enablement platforms, knowledge accessibility was a bottleneck. 

The team needed a solution that could surface accurate, context-specific answers instantly and on demand.

Solution: Whatfix turned to Docket, an AI-powered knowledge assistant that gives sales reps real-time answers to product, positioning, and competitive questions with no digging or document-hunting required.

Docket was set up specifically for new hires, embedding itself into their daily workflow. 

Now, instead of pinging managers or wading through folders, reps can simply ask a question and get a short, accurate, and confident response right when they need it.

Results:

• New reps are empowered from day one.
• Product knowledge is more accurate and consistent across the team.
• Sales conversations are more confident, credible, and effective.
• Establishing a self-serve learning culture without forcing reps into structured training.

💡 Takeaway:

Sales teams need faster access to the right content, not more content. 

AI knowledge assistants like Docket meet reps where they are, reduce hesitation, and turn every sales conversation into a more confident one. 

If your team is constantly asking, “Where do I find that?”, this is the fix.

8. How an insurance provider cut costs by 45% and sped up renewals with AI voice agents

Challenge: A major insurance provider was facing a wave of operational pain: overwhelmed call centers, long wait times, missed policy renewals, and rising agent workloads. 

Customers were frustrated by delays, confused by complex renewal processes, and increasingly at risk of churning.

The company needed a way to reduce costs, boost retention, and deliver a better experience without overloading its team.

Solution: They turned to Convin’s AI-powered call automation, deploying voice agents to handle routine policy renewal calls at scale. 

Instead of relying solely on human agents, AI took on the heavy lifting by proactively reminding customers about upcoming renewals, answering FAQs, and completing the process over the phone in minutes.

The system even handled multilingual support and personalized conversations based on customer profiles, helping policyholders feel heard without ever waiting on hold.

Results:

• 36% faster renewal processing, thanks to automated reminders and real-time voice interactions.
• 50% reduction in agent workload, freeing up human reps for complex or high-risk cases.
• 45% cut in operational costs, driven by scalable AI sales automation.
• 28% drop in policy lapse rates through proactive outreach and risk mitigation.

💡 Takeaway:

AI voice agents aren’t just a support tool - they’re a revenue driver.

If your team is buried under repeatable tasks like renewals, billing calls, or reminders, AI automation can reduce costs and boost CX at the same time.

9. How Spirit Airlines cut employee support inquiries by 76% using AI video

Challenge: With over 13,000 employees across airports, cockpits, and offices, Spirit Airlines needed a better way to communicate updated health, wellness, and benefits policies. 

Traditional methods like long emails and intranet posts weren’t cutting through, especially for mobile, deskless workers like flight attendants.

Manual video creation helped a little, but constant re-recordings made it time-consuming and hard to scale. 

This resulted in low engagement and a constant flood of employee support calls asking the same questions over and over.

Solution: Spirit turned to Synthesia, an AI-powered video platform that transforms written documents into polished, engaging videos at scale. 

Instead of writing lengthy emails or filming updates manually, the HR team now feeds content into Synthesia’s AI assistant, which creates a video draft in minutes.

These videos are embedded across internal channels (email, intranet, employee app), giving everyone easy access anytime, anywhere.

The team especially values the ability to quickly update scripts and regenerate videos without reshoots, which is crucial for communicating frequent policy changes to a constantly moving workforce.

Results:

• 76% reduction in phone-based employee support.
• 600% increase in engagement with benefits content.
• Nearly 300 videos created and updated in real time.

💡 Takeaway:

If you’re sharing important internal updates through walls of text, it might be time to switch channels. 

AI video tools like Synthesia make it easy to scale communication, increase retention, and reduce internal support burden without needing an entire production crew.

10. How Okta runs revenue in real time using AI-powered forecasting

Challenge: As a fast-scaling enterprise cybersecurity leader, Okta needed a more reliable, aligned, and proactive approach to managing revenue. 

Their revenue teams were spread across functions and tools, making it hard to answer critical questions like: 

Where are we headed this quarter? What’s at risk? And who needs to act right now?

Manual forecasting, siloed data, and reactive decision-making weren’t cutting it at scale. 

Okta needed a system to predict outcomes, surface risks, and unify the entire organization around pipeline health and execution.

Solution: Enter Clari’s AI-powered Revenue Orchestration Platform. 

Okta uses Clari daily across sales, finance, and leadership to align on pipeline status, forecast with confidence, and drive action where it matters most.

Results: 

• Accurate, real-time forecasting trusted by execs across the org.
• Faster response to pipeline risks, with opportunity scoring and trend analysis.
• Seamless team alignment through a single source of revenue truth.
• Hours saved every week by removing guesswork from sales workflows.
• Reliable data and stage hygiene driving cleaner forecasts and tighter execution.

💡 Takeaway:

Forecasting is more about good orchestration than reporting. 

With AI surfacing the right signals and risks in real time, revenue teams can act earlier, move faster, and close stronger. 

If your team is still stitching together forecasts in spreadsheets, it’s time to run revenue like Okta: live, aligned, and AI-driven.

Next steps: Making AI real inside your sales team

If there’s one theme running through every example in this article, it’s this: AI in sales is primarily about good execution.

But adopting AI isn’t about chasing the latest tool or adding another widget to your stack. 

It’s about rethinking how your team operates:

Where are reps spending time they shouldn’t be? Where are leads falling through the cracks? Where is your pipeline stalling?

Those are the friction points AI is built to solve.

This is why the smartest teams in 2025 are operationalizing AI use. 

And not with theory, but with real, practical workflows that automate the boring stuff, surface the important stuff, and give reps the context they need to sell with confidence.

If you’re ready to build your own AI-powered sales funnel, Warmly can help.

From signal-based outreach to full-cycle agentic SDRs, our platform is built to help modern sales teams work smarter, move faster, and scale without burning out.

Book a Warmly demo to see it in action and let AI do the heavy lifting. 

Read more

• 10 Ways To Use AI For Sales Enablement In 2025 [Reviewed] - Explore ten powerful ways AI is reshaping sales enablement, from onboarding to deal coaching.
• Outbound Sales Automation: Use Cases, Best Practices & Software - A practical guide to automating your outbound with real-world use cases, proven strategies, and top tools.
• AI-Powered Sales Automation: Use Cases, Examples & Software - See how AI is automating the full sales cycle with real examples, from prospecting to closing.
• How to Use AI in Your Sales and Marketing Tech Stack - Learn how to integrate AI into your existing GTM stack for smarter targeting, better engagement, and faster results.
• AI for Sales Prospecting: How to Use It? [2025] - Discover how AI is transforming sales prospecting, finding the right accounts, surfacing intent, and starting more conversations.
• AI in Sales and Marketing: How to Get More Sales? - A high-level look at how AI is driving more pipeline and revenue across both sales and marketing.
• 7 Factors To Consider When Buying An AI Sales Agent In 2025 - Before investing in AI sales agents, here are the seven key things every team should think about.
• 10 Best AI Sales Calls Tools & Software in 2025 [Reviewed] - Breakdown of the top AI tools for smarter, more effective sales calls, plus what sets each one apart.
• Best 10 AI Sales Agents In 2025 [Reviewed] - A curated list of the top AI sales agents available in 2025, with insights on features, strengths, and fit.

AI advertising isn’t coming in the near future. It’s already rewriting the rules.

In 2025, the most competitive ad campaigns are both creative and intelligent. 

Powered by AI, advertisers are now automating testing, optimizing performance in real-time, and targeting with precision that was unthinkable just a few years ago.

No matter whether you’re running paid social, programmatic display, or search ads, the right AI tools can help you scale campaigns faster, spend smarter, and drive more conversions without increasing or burning out your team.

But with a growing list of platforms claiming to “optimize with AI,” knowing what actually works (and what’s just buzz) isn’t easy.

That’s where this guide comes in.

I’ve researched and reviewed dozens of platforms and came up with this list of the 10 best AI tools for advertising in 2025, based on real features, real outcomes, and real use cases, so you can cut through the noise and focus on what will actually move the needle.

TL;DR

• The best AI-powered advertising tool on the market is Warmly, with its signal-based ad targeting that aligns campaigns with real-time buyer intent so you can reach the right audience at the right time.
• Advertising tools like Albert and Birch are ideal for autonomous digital marketing management and multichannel ad management
• On the other hand, there are tools like AdCreative and Jacquard that can help you create the ad campaigns, such as the copy and imagery.
• The most important factors to consider when choosing AI tools for advertising include alignment with your ad channels and real-time optimization capabilities.

Key factors to consider when buying AI tools for advertising

Before we dive into the list of top AI advertising tools, it’s worth zooming out for a second.

Choosing the right platform isn’t just about who has the flashiest features or most integrations. It’s about finding the best fit for your strategy, channels, and team.

Therefore, below are a few key things to keep in mind as you evaluate your options, as they’re what separates tools that actually drive performance from those that just add complexity.

1. Alignment with your ad channels

Not every AI tool is built for every channel. 

Make sure the platform you choose actually supports the channels you use most, whether that’s Google Ads, Meta, LinkedIn, programmatic display, or all of the above.

2. Real-time optimization capabilities

One of AI’s biggest value props in advertising is its ability to adjust campaigns in real-time. 

Look for tools that actively monitor your audience and performance data and make smart, on-the-fly adjustments, targeting the right people with the right offer at the right time.

3. Creative and copy generation features

If you're looking to save time (and mental energy), tools that generate headlines, ad variations, and visuals using AI can be a huge win. 

But it’s not just about quantity. Check if the creative actually converts and if it can be customized to match your brand voice.

4. Integration with your existing stack

Your AI tool shouldn't live in a silo. 

Make sure it plays nicely with your CRM, analytics tools, ad platforms, and any creative software you’re already using because disconnected systems = missed insights.

5. Level of control and transparency

AI shouldn’t be a black box. 

Look for platforms that give you visibility into why certain decisions are made, and let you fine-tune campaign parameters instead of fully automating everything with no human input.

6. Pricing and scalability

Some tools price based on ad spend, others on features or team size. 

Pick something that fits your budget today but won’t punish you for growing, especially if you’re scaling campaigns across multiple channels or regions.

What are the 10 best AI tools for advertising in 2025?

Here are the best AI-powered advertising tools on the market in 2025 after evaluating 30+ tools:

1. Warmly: Signal-based ad targeting.
2. Albert: Autonomous digital marketing management.
3. AdCreative: AI-powered ad creatives.
4. Proxima: Predictive analytics for improved audience targeting.
5. Jacquard: AI-generated marketing copy.
6. Birch: Automated multichannel ad management.
7. Neural.love: AI-generated visual content.
8. Madgicx: Meta ads optimization and automation.
9. Pencil: AI-powered ad generation.
10. Adzooma: PPC performance insights for seamless ad optimization.

1. Warmly

Best for: Signal-based ad targeting that aligns campaigns with real-time buyer intent, allowing you to reach the right audience at the right time.

Who is it for: B2B marketing and demand gen teams looking to run hyper-targeted, intent-driven ad campaigns across LinkedIn and other key channels.

Warmly (that’s us) offers the best AI tool for advertising with our AI-powered revenue platform built to help teams identify, engage, and convert high-intent buyers using signal-based targeting and AI-driven workflows. 

Unlike traditional ad tools that rely on static lists or guesswork, Warmly combines real-time behavioral signals with powerful orchestration to automatically serve the right message to the right prospect at the right moment.

The best part? It lets you reach warm leads not only through ads, but also through personalized onsite experiences and email and LinkedIn.

Let’s take a look at the key features that make Warmly the perfect choice for advertising.

Feature #1: Signal-based ad targeting

Warmly’s standout feature is its ability to track onsite and offsite signals - such as website visits and interactions, research intent, and social signals (e.g., LinkedIn engagement) - and leverage them to create highly targeted custom ad audiences.

For example, using Bombora intent data and Warmly’s Orchestrator, you can detect when companies are researching your competitors, integration partners, or relevant keywords. 

Warmly then syncs those companies to LinkedIn Ad audiences, triggering campaigns that speak directly to what those prospects are actively exploring.

Warmly’s DemandGen AI agent does the same, but at a higher level.

The AI agent uses all three types of intent signals to detect high-value opportunities, including them instantly in paid social campaigns across LinkedIn, Google Ads, Facebook, etc.

The result? 

A constantly refreshed audience of in-market accounts sees highly relevant ads on all the channels they live in, while your competitors are still guessing. 

It’s a scalable, automated way to increase awareness, warm up your ICP, and capture mindshare early in the buying journey.

Feature #2: Warm Offers

With Warm Offers, you can dynamically personalize offers or CTAs on your website based on a visitor’s traffic source, persona, and intent level.

Let’s say a buyer arrives via a high-intent keyword ad. 

Instead of showing them a generic landing page, Warmly’s DemandGen agent can surface a tailored message or time-sensitive offer that aligns with their use case, dramatically increasing the odds they’ll convert.

It’s not just personalization for personalization’s sake.

It’s smart, signal-based customization designed to convert pipeline-ready prospects faster.

Feature #3: AI-powered outreach workflows

Warmly doesn’t stop at ads. It also orchestrates what happens before and after someone clicks or converts.

With AI-powered lead workflows, you can automatically include each lead into specific engagement workflows based on their intent score.

For example, you can:

1. Engage high-intent leads via AI Chat - Warmly’s highly customizable AI-driven chatbot can qualify leads, answer their questions, book meetings, and loop in human reps when necessary, all the while maintaining your brand’s tone of voice and remaining context-aware.
2. Nurture leads via hyper-personalized campaigns - Warmly’s AI agents pick up warm leads in real-time, including them in tailored LinkedIn and email drip campaigns that take personalization way beyond first names and firmographics, including things like research intent, previous interactions, etc.
3. Reengage leads through retargeted ad sets - Leads who didn’t convert the first time around can be warmed up again through carefully crafted ads and warm offers tailored to their intent and actual needs.

This makes Warmly more than just an ad tool. 

In fact, it’s much fairer to say that it’s a full-funnel engagement engine that ensures no high-intent lead slips through the cracks, ever.

Try it yourself 👇or watch it in action. 

💡Note: You will need to be on one of Warmly’s paid plans to gain access to AI Prospector. For ARC, the ROI was 200% over 6 months. 

Pricing

Warmly offers a free forever plan that allows you to reveal up to 500 monthly visitors, set up ICP filters to quickly identify high-quality leads, and automate basic lead routing.

If you need more, there are three tiers to choose from:

1. Data Only: Starts at $599/mo when billed monthly or $5,000 when billed annually, lets you identify up to 5,000 monthly visitors, first-party intent signals, alerts, and access to Warmly’s B2B prospecting database.
2. Business: Starts at $19,000/year for up to 10,000 visitors or $45,000/year for up to 75,000 visitors, everything in Data Only, plus third and second-party signals, sales orchestration, AI Chat, and lead routing.
3. Enterprise: Custom pricing, custom number of visitors, everything in Business, plus custom signals and warm calling.

Pros & Cons

✅ Advanced signal tracking lets you create hyper-targeted ad campaigns.

✅ Seamless integrations with your entire sales and marketing stack, including LinkedIn Ads, Google Ads, Facebook and Instagram ads, Zapier, Bombora, CRMs, Slack, and more.

✅ Dynamic website personalization based on lead behavior and source.

✅ AI workflows that go beyond advertising and automate multi-channel outreach and follow-up.

✅ Real-time updates to ad audiences based on intent and live behavior, not static lists.

✅ Highly customizable and configurable, so teams of all sizes and experience levels can adjust it to their needs.

❌ Its most advanced features are available only on the paid plans.

2. Albert

Best for: Autonomous cross-channel campaign management and optimization.

Who is it for: Mid-size to large marketing teams aiming to scale digital advertising with minimal manual intervention.

Albert is an AI-driven marketing platform that autonomously manages and optimizes digital advertising campaigns across various channels, including search, social, and programmatic. 

Moreover, Albert enhances campaign performance and efficiency, by continuously analyzing data and making real-time adjustments, allowing teams to focus on strategy and creative development instead of manual tasks. 

Key features

• Autonomous ad management - Albert independently manages media across platforms like Google Ads, Facebook, Instagram, and YouTube, optimizing bids and campaign designs to maximize ROI. 
• Real-time analytics and insights - It provides real-time data and insights, enabling marketers to make informed decisions and quickly adapt to changing market conditions. 
• Personalization at scale - The platform personalizes ads for every audience segment, regardless of how small, using real-time insights and historical data for optimal results.

Pricing

Albert doesn’t disclose its pricing.

Contact its sales team to get a custom quote based on your advertising budget and goals.

Pros & Cons

✅ Integrates with all the major advertising platforms.

✅ Uses machine learning to learn and adjust to relevant changes on the fly.

❌ More suitable for larger organizations with substantial advertising budgets.

3. AdCreative

Best for: Quickly generating high-converting ad creatives using AI.

Who is it for: Marketers, agencies, and e-commerce businesses seeking to streamline ad creation and boost campaign performance.

AdCreative is an AI-powered platform designed to automate the creation of ad creatives, including banners, videos, and text, tailored for various advertising channels. 

By leveraging machine learning trained on a vast database of high-performing ads, it enables users to produce data-backed creatives quickly, aiming to boost conversion rates and reduce the time spent on manual design tasks.

Key features

• Uses AI to generate ad creatives - Lets you easily produce conversion-focused ad visuals in multiple formats and sizes suitable for platforms like Facebook, Instagram, Google Ads, and more. 
• Creative scoring - Allows you to assess the potential performance of each creative with AI-driven scoring, helping you prioritize assets likely to yield better results. 
• Stock image access - Provides access to a vast library of over 100 million royalty-free images to further improve ad visuals. 

Pricing

AdCreative has four pricing plans:

1. Starter: Starting at $39 and going up to $189 depending on the number of ad downloads you want, includes 2 users and 1 brand, in addition to access to all the platform’s AI features.
2. Professional: Starting at $249/mo and going up to $499/mo, includes 20 users, 3 brands, and access to Pro feature toolkit.
3. Ultimate: Starting at $599/mo and going up to $1099/mo, includes 50 users and 10 brands.
4. Enterprise: Custom pricing, has custom limits and advanced security features.

Pros & Cons

✅ Data-driven approach that helps in crafting high-performing ads.

✅ User-friendly interface suitable for users with varying levels of design expertise.

❌ Customization options are limited compared to traditional design tools.

4. Proxima

Best for: Predictive audience targeting to improve ad efficiency and ROI.

Who is it for: Consumer brands and performance marketers aiming to scale customer acquisition while reducing costs.

Proxima is a predictive data intelligence platform designed to help consumer brands identify and engage high-value customers through AI-driven insights. 

By analyzing vast datasets, Proxima enables marketers to optimize their advertising strategies, ensuring that campaigns reach the most receptive audiences. 

This approach not only improves conversion rates but also enhances overall marketing efficiency. 

Key features

• Predictive audience scoring - Uses machine learning to score and segment audiences based on their likelihood to convert, allowing for more targeted and effective ad campaigns.
• Real-time optimization - Continuously analyzes campaign performance data to provide actionable insights, facilitating timely adjustments for improved results.
• Data security - Ensures robust protection with end-to-end encryption.

Pricing

Proxima has two pricing plans:

1. Starter: $119/mo, includes basic audience categories, unlimited users, weekly seed refreshes, etc.
2. Pro: N/A, everything in Starter, plus advanced AI audiences, customer insights, Meta industry trends, performance benchmarks, etc.

There’s also a 30-day free trial that lets you try Proxima on for size.