Becoming AI-Native: Inside Atlan’s Growth Engine with Abhishek GP

Today I’m joined by someone very special to me, Abhishek GP. We worked together at Freshworks and have stayed close ever since. I’ve had the chance to mentor him over the years, and it has been incredible to watch him grow into a leader who is respected, thoughtful, and already driving major impact.

Now he is running growth at Atlan, one of the fastest rising and most AI native companies out there. This episode is a behind the scenes look at what it actually feels like to operate inside a company where AI is not an experiment but a core part of how marketing works.

We get into:
 • How Atlan connects Google Ads, HubSpot, and Gong to find real demand signals
 • The paid search insight that reshaped their strategy
 • The internal BDR intelligence system his team built without adding new tools
 • How Atlan’s AI task force partners with marketing to push what is possible
 • Why AI still needs human judgment and strategic thinking
 • What it looks like to grow your career inside a truly AI forward company

This is a killer episode with someone who is already doing big things and is only going to go further. Do not miss it.

Transcript

Stacey Epstein (00:28)
Today on the show, I’m so excited to have my former colleague and teammate, Abhishek GP. We worked together at Freshworks, got to know each other really well, and have stayed in super close touch. GP is doing some incredible work at Atlan, running growth marketing there.

And what a meteoric rise Atlan is having. Just an awesome company. We’re going to get into that, but first let’s talk about your meteoric rise. Tell me a little about your journey and what got you to Atlan — then we’ll dig into AI.

GP (01:06)
Stacey, thank you for having me. It’s pretty surreal being here. I reported to you at Freshworks when you took the company public, and so much of how I think about marketing leadership comes from that experience. Thank you for that.

The last 15 years of my career have been split in two. The first half was in consumer — sales, brand marketing, and e-commerce. Then I moved into B2B SaaS, landed at Freshworks (working for you, of course), and now I’m at Atlan leading the growth team. That includes everything from content and influencer marketing to paid channels and BDR — basically responsible for pipeline. For those who don’t know, Atlan is a data and AI platform. It’s the context layer that connects your data to AI.

Stacey Epstein (01:54)
Awesome. Congratulations on joining such a hot company. And there’s no CMO at Atlan, right? You report directly to the CEO?

GP (02:01)
That’s right. I report directly to the CEO and founder.

Stacey Epstein (02:05)
Great. So let’s dig in. You joined Atlan right as GenAI was becoming hot. I know you’ve done some incredible things. What was it like in the early days? Were you building the function from scratch?

GP (02:31)
The function was semi-built. We had a humming BDR team, some paid marketing, and a strong SEO engine. My contribution has been scaling those functions and building new ones. One of the big focus areas — for me and for Atlan overall — has been infusing AI into GTM. Not as an add-on, but as something transformational. How do you reimagine daily workflows around AI versus adding AI on top? That’s been core for us, and we’ve already seen some great results and learnings.

Stacey Epstein (03:14)
Give us some examples. What did you do?

GP (03:18)
After a few months of tinkering with AI, I realized it operates in two zones. The first is efficiency — making things faster. Drafts, reports, analysis, data crunching. Useful, but mostly time savings.

The second is effectiveness — using AI to maximize revenue. That part is harder. It requires thinking of AI not as a tool, but as a core integration layer. When you do that, you can extract patterns from data no human ever could. That’s where the magic happens.

One example was paid search. Classic marketer headache: data silos. We were spending money in Google Ads, tracking conversions in HubSpot, and running sales conversations in Gong — three separate systems, three sources of truth.

Before AI, a paid marketer would make educated guesses on keywords and hope for the best. But we didn’t know whether what prospects talked about on Gong calls — the real demand signal — aligned with where we were spending.

So we integrated Google Ads, HubSpot, and Gong. And we found that prospects were bringing up “AI governance” in about 30 percent of sales calls. But less than 10 percent of our paid search spend was going toward that keyword. Huge misalignment. We moved spend immediately. It even became a whitespace opportunity because competitors weren’t bidding heavily yet. For me, this changed the whole conversation around justifying marketing spend.

Stacey Epstein (06:18)
Totally. And did that influence other areas of marketing — campaigns, website positioning, sales deck?

GP (06:41)
Yes. We built different flows for different touchpoints, but the core idea was the same: integrate multiple data sources, extract insights, and build narratives from that. Product marketing, growth, BDR, paid search, SEO — all of them now have some flavor of that integrated workflow.

Stacey Epstein (07:39)
In practice, did AI literally say, “Hey GP, here’s the gap”? Or did you review the data and come to the conclusion yourself?

GP (07:56)
Great question. We didn’t get to the point where AI was recommending actions. The insight came from reviewing the data. The gap between “mentions on Gong” and “paid spend allocation” was obvious enough for us to take action.

Stacey Epstein (08:27)
Got it. You’ve always been very data-oriented. Do you ever think back to Freshworks — such a large org with tons of data — and wish you’d had this back then?

GP (09:03)
Absolutely. Large companies have so much data and so many surface touchpoints. If we’d had AI in its current form, we could have created stronger narratives, captured whitespace, produced content no one else had written. More data and more channels would have given AI even more to work with.

Stacey Epstein (09:35)
Totally. One of our challenges was so much data but no easy way to bring it together. The idea of a tool that can actually do that is transformative. What else have you been doing with AI?

GP (10:05)
Another big one — and a classic problem — was BDR context switching. They use four different tools to figure out account context. By the time they piece it all together, they’ve wasted minutes, or worse, they skip research and go in cold.

We mapped out their day and built a system that surfaces a “good enough” view of every account, plus AI-generated recommendations. It showed who from the buying committee had engaged, conversation history, third-party signals — all critical for us since Atlan is a six-figure ACV with long cycles.

It also recommended next steps. Should you invite buyer A to a one-to-one event? A roundtable? These rules were based on past data, then applied to new data. Huge unlock.

Stacey Epstein (12:11)
And you built this yourself. Did you consider off-the-shelf AI tools?

GP (12:50)
We’re fortunate to have an AI task force. Their job is to evaluate tools, validate whether they solve a real problem, and work with functions to implement. But I always recommend starting with your existing stack. Don’t add new software until you’ve exhausted what AI can do inside HubSpot, Google Ads, your CRM, Gong. Then look at new tools based on the problem you’re solving.

Stacey Epstein (13:46)
Tell me more about the task force. Where does it sit? How does it work with marketing?

GP (14:15)
It was created by our founders. Early this year they made it clear: we need to be AI-native by year-end. The task force reports directly to the founder and acts like an internal consulting squad.

Business teams — CX, marketing, sales — know the problems and the goals. They define the problem statements. The AI task force explores how to solve them and shares workflows and ideas across teams. Over time, marketers on my team have become AI-native themselves. There’s a real osmosis effect.

Stacey Epstein (15:51)
It’s fascinating hearing how AI-forward Atlan is. I think about traditional SaaS companies trying to evolve when AI shows up. Freshworks had that early Slack group — people posting how they were using AI. No blueprint. I think legacy SaaS marketers may face a reckoning when people from AI-native companies show up with totally different expectations and skill sets.

GP (17:08)
We’re in fascinating times. While we’re moving toward being AI-native, foundational work still matters — for everyone. Legacy SaaS needs foundational data work; even AI-native companies like Atlan need operational data hygiene. You have to operate at both ends.

Stacey Epstein (17:40)
Exactly. You still have the same goals — pipeline, MQLs, brand, sales support. AI doesn’t replace the job; it changes the toolkit. Before we wrap, any other ideas or examples?

GP (18:21)
A big learning for me has been around automated content. There’s a promise that AI will write all your content. What I’ve seen — and what most marketers see — is that AI writes mediocre content faster than humans write mediocre content. That’s it.

You still need strategy. You still need editorial judgment. I haven’t seen AI produce content that performs better than human-written content — just content that’s faster and cheaper. We’re still early.

Stacey Epstein (19:10)
Totally. Human-in-the-loop is still so important. I use AI constantly, but I’m always correcting it or adding insights. We’re not getting replaced anytime soon.

GP (19:32)
100 percent.

Stacey Epstein (19:33)
It has been such a joy having you on the podcast — as I knew it would be. Always super insightful. Best of luck on the rocket ship, and we’ll stay in touch.

GP (19:45)
It was great being here.

Stacey Epstein (19:47)
Bye bye.