AI-Powered Seller

AI Bubble or Breakout: The Reality of AI in Sales

• Jake Dunlap

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AI Bubble or Breakout: Are you building real, needle-moving workflows with AI, or collecting “bubble” use cases that create overlap and extra change management?

In this episode of AI Powered Seller, Jake Dunlap explains why the “AI bubble” is not AI itself, but the noise on top of it, including duplicate tools, overlapping features, and organizations investing without clear ownership. He breaks down how GTM leaders and frontline sellers can evaluate AI the right way: start with the revenue bottleneck, then choose technology that solves it.
Innovative Seller

You’ll also get Jake’s tactical seller playbook for adopting GenAI in a sustainable way:

  • Identify your three most painful tasks
  • Refine AI outputs so they sound like you
  • Build a simple ongoing roadmap so you don’t try to solve everything at once

Check Out: 

  • JourneyAI (free trial): https://meetjourney.ai/
  • Jake Dunlap – https://www.linkedin.com/in/jakedunlap/
  • Skaled - https://skaled.com/

If you got value from this episode, share it with a teammate in Sales, RevOps, Enablement, or Marketing, and make sure you’re subscribed so you don’t miss the next drop.

SPEAKER_00:

If we fast forward a year from now, are you gonna be cleaning up a bunch of bubble-based AI use cases that never move the needle? Or is your organization gonna be heading into 2027 looking completely different and working completely different? Are we solving real businesses challenges here that are truly the bottleneck within our org or with our customers? Yes or no? How do you make sure that you're implementing in your day-to-day breakout use cases and not bubble use cases? What's up, everybody? Welcome to another episode of the AI Powered Seller. I am your host, Jake Dunlap. Today's episode AI bubble or breakout. So today we're gonna talk about the hype. We're gonna talk about what's real, what's not. You see companies like Microsoft, they are doubling, tripling down on their infrastructure. Amazon is going all in with the new custom silicone, which I don't even know what that means. Google just released the Gemini, I think it's called the 3.0 model, which is insane, by the way, if you haven't tried it. Nvidia keeps crushing expectations. OpenAI is just continuing to roll out enterprise features. So you have all of these organizations, these companies that are valued at trillions of dollars in market cap continuing to double down, continuing to show tremendous potential. But what does that mean for all of you as sellers? So today's episode, I'm going to break down is this more bubble behavior, or is this more breakout sustainable behavior? Because I think we all agree this isn't going anywhere, right? AI is going to be here. It's going to be something that we're using for in some some form or fashion for quite some time to come. The key is all these other tools, right? All these different AI go-to-market tools. You know, I can't even tell you how many new tools pop up where a go-to-market leader's like, Jake, have you heard of this one? Or have you heard of this one? And I think the the issue we see is because we see all these breakout AI use cases, we then say, well, oh, these RevTech companies, you know, could they be the next X? And for most of them, the answer is no, right? But the reality is, I think we have to try as go-to-market sellers, as leaders, to stay at the forefront, but also try to break down what's actually going to drive impact because that's the key to AI. The key to AI is not thinking about, hey, here's a cool new tool that can do X. Should we do X? It's what's the issue I'm having in my business and can this tool solve it? This episode is going to break down the real AI bubble. What's inflated? What do I think is real? Because there is a lot of very like real potential here. And why go-to-market teams and frontline sellers have to start to invest time to learn these tools, become experts, and make sure that they can stay at the forefront of what we know is going to happen and spend less time worrying about, you know, maybe some fringe use case. So, with all that being said, let's jump into it. AI powered seller. All right. So, first let's talk about what the AI bubble actually is. Right? What is what is an AI bubble, right? Is it overhyped? Is it doomed? To me, when it comes to AI, it's not that there's a bubble, right? For for those of you, I wasn't in the workforce when you know the internet bubble happened, for example, where all these companies raised a ton of money, you know, it's all the dot-com boom, and then there was this huge, you know, uh reckoning where all these companies went out of business. But what didn't change is that the internet changed the world. And I think that is where we are at now when it comes to AI, that it's not that AI isn't the next thing. It's all the noise sitting on top of the real capabilities. It's all the noise of like this thing's AI, this thing's AI, this thing's AI, to where, you know, potentially we might see and probably will see some of these companies go the way of pets.com. Shout out to pets.com. If you don't know that story, it's a good one about you know, a really overvalued company that everyone thought was gonna be huge and then tanked. So for many of you listening, understand this AI as a technology, generative AI specifically, is not going anywhere. So investing in the tools, knowing how to use them, finding new ways to use them in your day-to-day is gonna be required. And so when I think about the bubble, right, this is a really good example. I talked to a CEO and he told me, Jake, look, we invested in three AI tools and none of them worked. Okay. And when I asked him, I said, okay, well, great. Whenever you were evaluating, when you were thinking about these technologies, what was the workflow or bottlenecks in the revenue engine that you were trying to solve? The answer, yeah, that's a good point. And I think with a lot of AI use cases, that's exactly what we're we're doing. We're saying, hey, look, intuitively, this tool sounds kind of cool. But guess what? If we're implementing a tool that solves priority number 32 and is a big change management lift, it's probably not worth it. And so for a lot of you out there, when we think about how I can make sure I'm investing my time and energy in breakout use cases, it really all goes back to the issues or areas of opportunity within the revenue engine, from how we generate leads, work with customers, how we actually go and grow our current customer relationships, making people more productive, et cetera. And so where I see the bubble is tools that have identical features. I cannot tell you right now, and I'm sure many of you see this, how many RevOps teams I work with that have invested in one tool maybe a year or two ago. That tool now does five things, but now they've layered in three other tools that did, you know, this feature set when this company didn't have that feature set. And so for a lot of my AI technology investment individuals out there, what I want you to think about is are you staying up to speed with how the tools you already have are using AI, or are you layering in tools that have 20, 30, 40, 50% overlap just because the tools are evolving? And I think for a lot of GTM RevOps and enablement leaders, it really is critical to continue to go back and understand what the tool stack is that you have today. And even for my reps out there, if I was a rep, I would constantly be paying attention to the roadmap of my sales engagement platform or my call monitoring platform. So this isn't just about RevOps or an enablement. If you're a rep, you need to be paying attention. So if your team's not paying attention, you can still go and capitalize on those features. The other big issue I see is no ownership, is that there's nobody really internally owning the AI roadmap to see the redundancies or the issues with the workflow. Again, we do a lot of this type of work for companies because it is very difficult to do internally, where marketing is investing in a technology or tools or data set, finance is investing, sales is investing, customer, everyone's investing. And again, not only is there redundancy, there's just a ton of overlap in people doing very similar work. Whereas if you have, and I'm all for, by the way, a decentralized slash department by department rollout of Gen AI. That's what we preach to our clients. But you have to have a centralized group that's paying attention to all the technologies being used, all the new agents and assistants being used to speed up development time because you're gonna see a lot of different groups creating flavors of the same thing. So if you don't have that kind of centralized workflow, you're gonna really, really struggle to move as fast as you can and not have just a ton of overlap. And so to me, those are the two big ones that as organizations are trying to say, Jake, look, we know we need to invest in AI. We want to make sure we're not investing in the bubble tech, but the breakout tech. That is really what I try to look at is I say, okay, are we solving real business's challenges here that are truly the bottleneck within our org or with our customers? Yes or no? Do we have a centralized place where you know we can look at best practices of what people are doing, allow departments to yes, they know their business better than you know, IT, for example. So we do those two things, and that helps to make sure structurally as an organization, we are continuing to implement things that are going to actually move the needle for the business. So that's the big first piece here. And what I want to do with the rest of the same time, getting very, very tactical into what frontline sellers need to know and do about the bubble. And as usual, everyone, if you are enjoying the episode, please make sure to like, subscribe if you're watching us live on YouTube, uh, if you're listening on your favorite podcast platform, make sure to sign up to get the alerts and downloads when those come out. Definitely share some of these tidbits with your team. That's what I always encourage people. They'll say, Jake, what do I need to do to stay on top of things? I said, Look, you know, myself, the team, we're doing a lot to make sure we're staying at the forefront of what's happening in AI. So, you know, share this little clip with your team, maybe your RevOps team, your sales leader. I think any of them are gonna get a ton of value out of it. So without further ado, let's get a little tactical. Let's talk about what we need to be doing in the trenches around this. I gave the example a little earlier of staying on top of your own product roadmap and the product roadmap of the tech stack that your team is invested in. I think that to me is probably number one that if you are a seller, your team is investing a lot of money. I can't remember the last number I saw. I want to say it was maybe$800 per rep per month in tech, something like that. If you include CRM and all the other things happening, so you're talking about you know, companies investing tens of thousands of dollars in every rep around the tech. Now, again, the issue is many times your own internal team can't keep up with the updates. And so that's what I would encourage all of you to do is step one, become an expert in the tools that your organization already has. I do believe many of you, as reps, should be getting certified in those tech. You know, you can imagine rep number one really knows the nooks and cranny of this AI-powered platform. Rep number two is hey, I was trained to use it this way. This is what I was told to do. And they're just going through the motions. I have to imagine that rep number one, even if they're not quite as good, is gonna get a ton more value out of the platform and hopefully more results based on what it was supposed to drive. And I think nothing illustrates that. I was talking to a rep who were talking about AI, and what he mentioned is that I feel like AI slows me down or it just it's just not good enough. So I need to do things manually, right? He was using it to, you know, write me a cold email, tweak this email before I send it out, etc. And what happened is literally with a couple of tweaks around how he thought about prompting, how he thought about what the role of AI is, which isn't to do the job for me, but to get me to V1, immediately came back and said, I was a complete skeptic. I'd been using it, not impressed. He's I'm all in now. What it took to get him to all in was him realizing that the tool wasn't the problem. It's the workflow and the way that he was using the tool that became the problem. And I think for a lot of people who are AI still step one, I think that is probably outside of staying on top of your own tech, that behavior of understanding that the tool can do a lot for me, but its job isn't to just do it for me, it's to be a collaboration partner. And so many reps don't need more AI tools. What they need is a workflow that removes the real effort so then they can turn their brain on and then get this thing to V3 or V4 in the same amount of time. And so if you're a rep out there, you're expecting AI to do your job for you, or you're a rep who says, Well, actually, this AI output's pretty good. I'm just gonna copy and paste it and send and ship it. Both of those use cases are not sustainable. I just want to be straight up, right? Think about those use cases. If you give up on AI or you just, you know, you know, say, hey, I've got this thing, it's working for me. There's going to be people that are gonna outpace you. They can just be more productive. Like it just is what it is because they know how to use the tools. On the flip side, if you're copying and pasting AI, well, guess what? Pretty soon the AI is just gonna say, Oh, I'm already plugged into this workflow to send emails or whatever. I'll just generate it and send it. And so when you think about at the rep level, I want all of you to think about your gen AI workflow. And and I'm gonna give you kind of my step one, two, three for how to break down where you should be using AI and how to do it. And we'll try to go into a couple of very specific use cases for each one. So the first is to identify your three most painful tasks. So I'm talking about those kind of tasks that you dread, right? The ones where you wake up in the morning, you look at your calendar, you go, Oh gosh, I have to do that. Or over the weekend, you're thinking through it and you're like, oh my gosh, this is gonna take forever. So identify your top three. And those could be prep related, they could be creativity related, it could be, hey, I'm not really sure how to handle this, and maybe that's where AI can help me. It could be efficiency, meaning you know, there's a lot of different ways. So some of the automations and things that we're building for clients are can it just look at my calendar invite, look at the domain, and automatically run an assistant that does my account prep? Yes, is the answer. So it's really just looking for those different ways that you can alleviate your biggest pains. So, step one for any rep out there, what are your three biggest pains? For most of our clients, I will tell you the first area that we eliminate for reps when it comes to like let's use AI to eliminate the pain is account prep, prospect-based research. So coming up with snippets of sub-industry trends. So we call it the triangle, right? Which is the persona, the role of the person, the industry or sub-industry they're in, and then the trends on how we solve that. So we work with VPs of operations and industrial manufacturing to solve these two things, roughly something like that. Gen AI is really good at pulling out those trends. So those are those are, you know, a couple of big ones for me. Identify the top three biggest pain points. Once you've done that, you need to have a little bit of a mental shift. And that's number two. So once you've identified your top three, I want you to pick the first one. And number two is you have to refine the outputs to sound like you. You're going to need to spend a little bit of time saying it's a little more like this. It's a lot more like that. I would say it this way. And again, you can create a custom GPT, you could create a Gemini Gym or a copilot agent. I don't really care which one you use. And you're just you're fine-tuning what's what we call the custom instructions. And so just understand with just some basic prompting, you can probably get pretty far with some of these use cases. But step two is you have to get it to feel like you. Why is that so important? LLMs are really good out of the box, like really, really good at doing a lot of different things. Another reason why I feel like people struggle to fully adopt is they just it just doesn't feel right. You know what I mean? Like it's one of the like it doesn't feel authentic or feel quite like me. And so we tend to, you know, over over rely on our own human heuristics to do something, versus trying to figure out how we, you know, get AI to help us to do it. So step two is you have to invest just a little bit of time, 30 minutes, 45 minutes to truly make it your own. And then the next and final piece. So you've identified the bottlenecks, you've you've started to make sure it sounds like your own, is to create your ongoing roadmap. And what do I mean by that? Right. So I I said in the beginning, let's pick three tasks. The reality is I don't want you to try to solve all three at once. What I want you to do is pick one, train it on you, solve next up. And so, you know, many of you should start to use, I don't care if it's an Excel, I don't care what you know, if you use a sauna, we use a sauna, is to create a roadmap for yourself to do the next up thing. So then I'm like, okay, this one's in backlog, I'm gonna move it to next up, and then I'm gonna deploy, right? And then optimize in this whole circle, right, as a part as part of that. And so for a lot of you out there, if you just do those three things, it is going to have a massive, massive impact on your day-to-day. And if you're looking for a solution out of the box, I do want to recommend Journey AI. Journey AI already has a lot of these purpose-built agents and assistance for account research, deal strategy, uh, even helping with social posts. They've got a more general one called Rep GPT that you can, it can do kind of anything sales related. It's like a big sales brain that knows to help you to do one-to-one prep or any other random activity. So if you want to get ahead and skip over a lot of the day-to-day use cases, go sign up for a free trial of Journey AI. Link is in the show notes as well. Meetjourney.ai will be a big time saver and game changer for you for sure. So that's today's episode. So, today's episode, what I thought was really important and what when we were working on the outline was to really try to help everyone understand where we're at, big picture, and then get get tactical in terms of how do you make sure that you're implementing in your day-to-day breakout use cases and not bubble use cases? And there's no doubt, I think every organization in 2026 knows without a doubt that we have to invest in AI. But the key thing I want you to think about is this is if we fast forward a year from now, are you gonna be cleaning up a bunch of bubble-based AI use cases that never move the needle? Or is your organization gonna be heading into 2027 looking completely different and working completely different? Because that is the time and place that we are at right now. There's gonna be probably three types of companies. One, the company that continues to wait and work in the old school way. I think we all know what's gonna happen there. Two, the type of company that says, yes, AI, and then this group goes and buys clay, and this group buys this, and this group buys this. And then in about 12 months, somebody raises their hand and goes, guys, what are we doing here? We've invested in all this technology, all these things. I'm looking at our rep productivity year over year, and it's a blip. 5%. What happened to these 10, 20, 30 percent gains? And then organ and then organization three are gonna be the winners. These are the organizations that continue to say, okay, what are the bottlenecks in these roles? Okay, do we have a clear path for solving the bottlenecks for these people? The technology is step two or step three. How we're gonna solve that is step two or step three. Have we really identified the bottlenecks for each individual role, what these people are doing, the unlock to revenue or better customer conversations? And they continue to build and deploy AI around that. Those are gonna be the winners, my friends. So thank you so much for tuning in. I hope you got tremendous value out of the episode. And as usual, make sure if you did get value, like the video, subscribe to the channel, share with your favorite sales buddy as well. And if you're listening on your favorite podcast platform, make sure to sign up for alerts and downloads as well. So I hope you got a ton of value out of this. As I talk through this, it just becomes more clear and more clear to me every day that there is a right and a wrong way to implement Gen AI. And if you listen to today's episode, listen to it a few times over, and follow the step by step, I promise you're going to be in that third group of people that are a year from now looking back saying, I am so glad that we took this approach and didn't just start throwing every new AI tool at the problem. Thanks again, everybody, for tuning in, and we'll see you on the next one.

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Jake Dunlap

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