GTM AI Adoption That Actually Sticks: Optimization, Amplification, and Reinvention (with Jonathan Kvarfordt)

Mandy Hornaday: If you've been on LinkedIn lately, you've probably felt it - the pressure to be doing more with AI, moving faster, transforming your marketing organization, and yesterday. But when you look past the noise, the data tells a very different story. As of mid-2025, only about 7% of companies had actually operationalized AI - not just handed out a ChatGPT license, but truly embedded it into how their teams work. By the end of the year, that number had grown to about 25%, which means the vast majority of companies are still trying to figure it out.

So what does it look like to close that gap? And more importantly, where should marketing leaders really be focusing their time right now in 2026 as the pace of change continues to accelerate? My guest today has a front-row seat to how this transformation is actually happening inside go-to-market teams. Jonathan Kvarfordt - Coach K - has spent the last five years deep in AI strategy.

He teaches AI and sales at Bryant University and advises companies on how to rethink their go-to-market strategies in the age of AI. He's also currently the VP of Go-to-Market Strategy and Marketing at Momentum.io, a conversational data platform recently acquired by Salesforce, which means he's working with real pipeline data on how companies are actually adopting AI. In this conversation, we get into the three levels of change every marketing team needs to understand, why AI amplifies your existing systems - good or bad - and why your human genius may actually be your biggest competitive moat.

If you're a CMO or marketing leader trying to figure out where to place your bets right now, this conversation will give you a much clearer lens. Let's dive in. Mandy Hornaday: Hey Jonathan, welcome to the Growth Activated show today. We're so excited to have you.

Jonathan Kvarfordt: Thanks for having me. It's so good to see you. Mandy Hornaday: You too. I know you go by Coach K.

I've listened to your podcast. I've followed you on LinkedIn for a little while. Why don't you give us a quick overview of your background, where you're currently at, and what you're working on that's really firing you up. Jonathan Kvarfordt: You caught me in the middle of flux, because I'm not sure exactly where I'm going to be in the next while.

But I'll give you the shortest version. My dad owns a mechanic shop, so I started sweeping floors when I was 10. I've been in the sales world since I was a teenager, then transitioned into enablement. And for the last few years I've been doing marketing.

A lot of what I do comes from being on the front end - creating go-to-market motions from scratch and making sure the sales process is running and everything in the back end is actually getting done. That's me. Jonathan Kvarfordt: For the last five years or so, I've been involved with AI. The company I was with at the time bought an AI technology - this was before ChatGPT came out.

The guy who literally built his own model, a brilliant person based in India, came on as our Chief AI Officer, and my job was to make sure the customers and salespeople understood how it worked. So I learned a tremendous amount from him. Then when ChatGPT came out, like the rest of the world, I jumped in - and I realized quickly that people were using it not wrong, but incomplete. I knew that from my enablement background and from working with someone I consider a true AI expert.

So I started the Academy in December of 2022. We've had 10,000-plus people go through it over the last three years. I teach at Bryant University - AI 101 and AI and Sales. I advise ten different companies on either AI strategy or go-to-market strategy.

And currently, at least for the next month, I'm the VP of Go-to-Market Strategy and Marketing for Momentum - a data and agentic platform that was recently acquired by Salesforce. Mandy Hornaday: And which was recently acquired by Salesforce - that's why things are in flux? Jonathan Kvarfordt: Exactly. There's some things happening that I can't talk about just yet, but there's going to be change in the next month.

I just don't know what it looks like yet. Mandy Hornaday: Well, I'm excited to get into what you're seeing around AI and go-to-market. But before we go there, I would love your perspective on where we truly are right now with AI adoption - because if you just follow LinkedIn, it sometimes feels like a mess. Really overwhelming.

I sometimes wonder how much of it reflects reality. What would you share? Jonathan Kvarfordt: I'll give you actual data instead of just opinion. At Momentum, we're a data company that works off conversations - emails, calls, and so on.

Think of it like a Gong, but more comprehensive. We did a research paper looking at the first half of 2025 and the second half of 2025, examining patterns of conversation around AI. In April 2025, the Shopify memo came out - that was one of the things that started accelerating AI budgets, because people started feeling board-level pressure to adopt AI and drive efficiency so they wouldn't be left behind. So our data shows that in the first half of 2025, only 7% of companies had actually operationalized AI.

Now, there's an important distinction: operationalizing AI inside your systems and processes is very different from just handing someone a ChatGPT license. A lot of companies have adopted AI in that second sense - but adoption does not equal transformation. You've just thrown a license to someone who doesn't know how to prompt and doesn't know where to apply it. Writing emails faster is nice, but it's not creating revenue change in the business.

In the second half of the year, we saw that number accelerate from 7% to 25% - a threefold increase. But that still means 75% of companies are way behind. Everyone I talk to feels like they're behind and everyone else is ahead. I tell them: no, we're all behind.

We're all figuring this out. The handful of companies who did the hard work in 2025 are accelerating fast in 2026 - but they're the exception. This year is the year you have to get things in order, because the ones who are moving are going to get so far ahead it'll be hard to catch up. Mandy Hornaday: Absolutely.

And it feels like 2026 is already moving at an even more accelerated pace. So when you say people need to get started - where should they begin? Jonathan Kvarfordt: It depends on size and how much they're willing to disrupt. If you're a 50-person startup, it's easier to change than a 10,000-person enterprise - but it can be done.

I've seen enterprises make major changes. It just requires time and investment. A lot of people feel this pressure and say they need transformation now, but they're not willing to do the hard work. They think throwing AI technology at the problem will solve it.

It doesn't. So I always tell people: there are three levels of change, and two ways to approach it. On one side, you can do what you were already doing - but better, faster, cheaper. On the other side, you can think about doing something totally different.

The three levels are: first, optimization - there's so much wasted time everywhere that you can generate major ROI just from optimizing the time of your people and processes. The next level is amplification or augmentation - not just saving time, but amplifying what's happening so the human is enhanced, not just the clock. And the third level is total reinvention - transformation. But that requires shifting everything.

Jonathan Kvarfordt: Let me give you a real example. I had the Sendoso team on the podcast - and by the way, they did this on their own; I'm using them because they fit this model perfectly. They had 15 BDRs generating 15% of pipeline. They kept hearing about AI and said, 'Let's blow this up.'

If BDRs had been generating 90% of pipeline, they probably wouldn't have taken that risk. But 15% gave them room to experiment. They let go of most of the BDRs, kept one who was already experimenting with AI, and rebuilt the entire process from scratch - figuring out where the human creates the most value and how to use AI for everything else. It took about a month to a month and a half to stop, rethink, and rebuild.

At month three, three BDRs were generating as much pipeline as the original 15. Now they have four or five BDRs generating 30% of pipeline - a third of the team doing twice the output. But it required a hard look at what they were doing, what the customer experience looked like, and a willingness to commit. That process was six months.

They lost three months of pipeline build, but caught up quickly. It's like a slingshot - you're getting pulled back, it feels like you're going the wrong way, but when you let go, you accelerate past where you would have been. You just have to be patient in the middle, when it feels discouraging. Mandy Hornaday: That's such a fascinating example.

One thing that's top of mind for me - as a CMO in a larger org, what can I control? Was the Sendoso transformation a company-wide commitment, or was it something the sales leader or CRO could run within their own department? Because I think about the balance between what I can control within my organization and transform - even if the broader organization isn't operating at that speed. Jonathan Kvarfordt: In that particular instance, it was top-down - the CEO was on the podcast with us because he wanted to be there.

And Sendoso is mid-market, not massive, so it's a different environment than a 10,000-person org. That said, it is possible in larger organizations. I've been talking to the CMO of Salesforce - they have a massive organization with a lot of history behind them. It's a totally different world.

But some leaders in massive orgs are blowing things up, and others are moving more slowly. Everyone has to do what's right for their business. If you're a CMO in a large org and you don't feel like you can make dramatic changes - if all you did was optimize, just look at how to save time - you'd be surprised how much more you can get done. It does require you to slow down and get past the day-to-day whirlwind to think about first principles: what are we doing and what are we actually trying to accomplish?

In marketing, AI can do an amazing job of analyzing data, identifying patterns, telling you what's working across channels. But the best ideas - the crazy brand or demand generation idea - those come from your brain. The best ideas come in the shower, not from AI. I use AI to think through the process, make sure I'm not missing anything, and then execute on the plan.

I don't think AI can replace that unique creativity. The difference will be between AI-generated strategy and a specialist experienced marketing leader's strategy. Mandy Hornaday: Absolutely. And one of my areas of specialization is operational excellence - building agile operating systems.

If anything, AI is amplifying the problems marketing organizations have always had. If you haven't solved them, you're just making the problems worse. Jonathan Kvarfordt: Exactly. AI is forcing people - both individually and organizationally - to look at problems they've never had to face before.

When demand is strong, you can glide past a broken sales process. But with AI, you have to look at the skeletons. Because AI will amplify them, and you don't want that. Mandy Hornaday: So what are some of your favorite AI use cases in marketing right now?

Jonathan Kvarfordt: There's so much cool stuff. One thing I love is AI's ability to synthesize large amounts of data - taking market trends, third-party signals, advertising data from whatever platform you choose, your social media data, organic content performance, broad market indicators - and finding patterns across all of it to surface insights I couldn't build myself. That synthesis capability is, to me, one of the most exciting things happening in marketing right now. I also think AI is a really good pattern-matcher.

There's a marketer in healthcare I follow who inspires me - I watch what she does with branding and apply it to my own work. I can use AI to say, 'Go look at this company and help me figure out what I can apply to mine.' And then there are the basic, high-value automations - identifying what content will have the biggest impact, which channels are performing best, where your ICP is and what messaging resonates - and automating that process. But the most impactful things I did at Momentum - AI absolutely amplified them, but the ideas never came from AI.

What I'm finding is a consistent pattern: the more human-centered the approach, the more success I had. I focus on where the human ICP is and how to surround that person with value - whatever means are needed. And the value itself? That has to come from me, because I am the ICP.

AI will give you the generalized version of what the ICP cares about. But that instinct, that gut feel - it's just as important now as it ever was. Mandy Hornaday: I love that. The synthesis piece is something I find really powerful too - being able to learn at a faster speed than ever before.

But where I see people falling short is in the activation of that information. It's one thing to have competitor insights delivered to a Slack channel weekly. But what are you actually going to do with them? Are you seeing information overload?

Jonathan Kvarfordt: It's a good point, and it's very easy to get overwhelmed with anything AI right now. But I do think this year is when that starts to shift. Have you been following open agentic tools - things like OpenClaw? I've been testing things out with Perplexity computer use, and what you can do now is moving from pure analysis into analysis plus execution - actually getting things done.

When you have an AI connected to all your different systems that can do the analysis and then understand, 'I'm seeing TikTok doing this thing,' and automatically creates a UGC-style video around your product, posts it, looks at that video's performance, comes back, optimizes it, and loops - that is happening right now. People are having success with it. But it requires infrastructure and a level of trust in AI that most people don't have yet. And I'd tell anyone listening: if you're not an expert in AI and don't know what you're doing, don't jump into the most advanced agentic tools yet - there are security considerations you need to understand first.

But the concept is where we're going. Jonathan Kvarfordt: And there's a broader shift happening. Google released web MCP - the idea being that the internet was built for humans, not AI agents. We're forcing AI to search the way humans do, and that's the wrong approach.

So there's a movement to rebuild the architecture of the internet to be agent-friendly. A major banking system recently said the same: banking infrastructure was built for humans, and they're now thinking about a different protocol for AI agents to operate through. As a marketer, you have to start thinking about how to market to the AI and how to market to the human. It's no longer just one channel.

There may be no human involved - just an agent making decisions. That's where you've got to be thinking. Mandy Hornaday: I actually saw a LinkedIn post recently that made me pause - talking about how marketing leaders in AI-forward companies with room to explore and experiment will have a 10x advantage over those in tightly constrained corporate environments. Are you seeing that?

And what would you advise to CMOs and marketing leaders in security-driven organizations? Jonathan Kvarfordt: I'd say: be aware and be patient - but don't stop. I'm security-conscious because I have to be for work, and because I think it matters. But if I were in a massive org, I would absolutely deep-dive into the possibilities - and then be patient, because more secure versions are coming.

The question is: will you be ready for them? Take Salesforce as an example: I don't have their budget or distribution. The only way I can compete is using AI. In fact, before Momentum was acquired, I was ranking higher than Salesforce on certain terms - and it's Salesforce I was competing against.

So there is a way to beat the bigger players if you're smaller. But the big organizations have things smaller teams don't. They just have a larger ship to turn. That's why I say start with optimization - there are SOC 2-compliant platforms where you can do meaningful automation right now.

MindStudio.ai is one I'm a big advocate for - you can do a ton with marketing automation in a secure environment. It's not at the level of the most advanced agentic tools yet, but we'll get there. Get as far as you can now versus waiting.

If you don't make progress this year, you're going to feel it in the next year or two. Mandy Hornaday: Any other tools besides MindStudio that you think are really powerful right now? Jonathan Kvarfordt: I'm a big AI search geek, so a few come to mind. Profound is a great tool in that space.

I'm also a fan of Searchable - Searchable.com. And then there's Peak. Both Searchable and Peak are really strong for AI search optimization.

For general marketing automation and orchestration, MindStudio is my go-to. And honestly, right now I'm deep in Claude - specifically Claude Code and the MCP integrations. It's kind of blowing my mind. The more MCP connections you build, the more it takes the place of tools like Zapier because you can build things customized entirely to your workflow.

Just the other day I took a group of marketers through how to use Claude Cowork to analyze multiple data points and create a brand deck they could present to their board in under half an hour. That same work used to take me weeks. When you compound that speed advantage over time, the gap between someone doing this and someone not doing it is going to be enormous. So if you're a marketer, you should absolutely be looking at Claude at some level - and also learning what skills-based AI frameworks mean.

Skills are kind of where I think things are going. Go to YouTube, there's a ton of free content on it. Start geeking out, because it's where this is heading. Mandy Hornaday: That's such a great note to close on.

One of my last questions was going to be where you'd encourage CMOs and marketing leaders to start - and it sounds like learning skills-based frameworks is a big one. Anything else? Jonathan Kvarfordt: There are a ton of great people - yourself included - putting out really good free education on YouTube. Lean on that.

And just be willing to experiment, in a lower-risk, safer way. Even if you're in a large enterprise with limited room, push it - try it, see what you can learn. And the other thing I'd say is: don't neglect fundamentals. I can't emphasize enough how much the fundamentals matter right now - maybe more than ever.

And whatever your genius is - that unique human thing you bring - that's going to be part of your moat. Even when AI is smarter than us, even when it can do most of what we can do, it will not have your specific experience, your instincts, your soul. Whatever geeks you out about marketing: dive in, get really good at it, give yourself permission to be passionate about it. Your passion will be your moat.

Mandy Hornaday: Completely agree. So fun to have you here today, Jonathan. Thank you so much. Where should people go to keep learning from you?

Jonathan Kvarfordt: LinkedIn is the best place - I treat it like my GTM AI journal. And then GTMAIpodcast.com - that's where I put everything about go-to-market in the age of AI. Mandy Hornaday: I love it.

Thank you so much, Jonathan. Such a pleasure. We'll have to catch up again soon. Jonathan Kvarfordt: Thank you so much.

SHOW OUTRO: Thanks so much for tuning into this episode of Growth Activated. I hope this conversation sparked new ideas, challenged your thinking, and gave you practical tools to help elevate your impact as a marketing leader. If it did, I would love for you to pass it along to a friend or a colleague in B2B marketing. The more we grow together, the more we raise the bar for what marketing leadership can look like.

And as always, in the meantime, keep activating growth for yourself and your company. See you next time.