Why AI Is NOT a Go-To-Market Strategy (And What To Do Instead)

The current landscape of Go-To-Market is saturated with AI hype, leading many organizations to adopt tools that are little more than thin wrappers around public models. Many leaders fall into the trap of using AI as a blanket solution for growth, similar to the 'growth at all costs' mindset of the past, bolting AI onto broken processes and expecting miraculous results. However, applying AI to poor CRM data only serves to regurgitate bad information faster, proving that AI is not a strategy on its own, but an accelerant for an existing, solid foundation. To effectively leverage AI, organizations must develop a formal AI Charter that clearly dictates strategy, data governance, and brand voice. Data security is paramount, as many users carelessly upload sensitive corporate or client information into public models without understanding the infrastructure or SOC 2 compliance requirements. Building simple internal tools and ROI calculators using low-code AI apps is highly effective, but leaders must recognize the boundary between helpful internal workflows and enterprise-grade software. The most valuable applications of AI in GTM currently reside in intelligence and enablement—empowering reps with deep account research, summarizing challenges, and automating routine workflows. Conversely, fully autonomous AI outbound SDRs are largely viewed as a risky delusion that damages brand reputation. Human-to-human relationships, particularly in enterprise sales, remain the ultimate differentiator. Revenue leaders must get hands-on with AI tools themselves to cut through the vendor noise and focus on solving real operational problems.

Discussed in this episode

The prevalence of low-value AI tools that are simply ChatGPT or Claude skins lacking real product infrastructure.
Using low-code AI builders like Bolt and Lovable for simple ROI calculators versus the dangers of using them for enterprise-grade apps.
The critical need for data privacy and understanding where customer data flows when implementing new AI tools.
Developing an 'AI Charter' to govern brand voice, tool usage, and data security across the entire organization.
Why applying AI to poorly managed CRM data just results in faster, more automated bad reporting.
The severe brand risks and low effectiveness associated with fully autonomous AI SDRs for cold outbound.
How intelligence and enablement AI tools significantly reduce rep research time and accelerate pipeline velocity.
The necessity for CROs and sales leaders to get hands-on with AI tools to avoid buying vaporware.

Episode highlights

0:00 — Introduction and the AI GTM landscape
2:15 — The bullshit radar: AI hype vs reality
4:30 — Using Bolt for low-code GTM apps
6:45 — Data privacy and SOC 2 compliance risks
8:30 — Defining your organization's AI Charter
10:45 — Why AI is not a standalone strategy
13:00 — Mapping the best categories of AI usage
15:30 — The delusion of fully autonomous AI SDRs
18:00 — Why CROs must evaluate AI hands-on
20:15 — The one question to ask AI vendors

Key takeaways

AI is a GTM accelerant, not a standalone strategy.
Create an AI charter for data governance and security.
Avoid fully autonomous AI SDRs for cold outbound.
Prioritize AI for sales intelligence, enablement, and account research.
Leaders must get hands-on to evaluate true AI capabilities.

Transcript

Welcome back to another episode of the Bridge the Gap podcast powered by Revenue Remagine. And today, well, it's a little bit of a special day. You have Dale all dressed up who just took the jacket off. We'll get him to show it at some point during the show.

I'm lounging in a t-shirt. No way. And it's just us. No guests, no filters, no bullshit.

We're going to talk about AI and go to market, what's actually working, what is completely overhyped and where we're seeing real friction on the front lines. If you're a founder, CRO, RevOps leader, even a seller, just trying to figure out how the hell do I integrate AI without at the same time automating myself into irrelevance. This episode is one that you're going to want to listen to. There's going to be no M-dashes, there's going to be no bullshit, there's going to be no, oh, use AI to complete your repetitive tasks.

We're we're going to get a little more um in depth than that. Yeah, Dale. That's what I got, man. Show the jacket.

Come on, show the jacket. I like it. I like it. It's hanging out here.

It's hanging out here. And and so for background for everyone, Dale and I are in, well, not so sunny Los Angeles, California right now. It was supposed to be sunny. The weather's beautiful.

We are onsite with a client. We have an executive meeting today where the CEO's like, totally casual. Don't worry about it. I am in a albeit upscale t-shirt.

And Dale, always having to one up me, is in dress slacks, a button down shirt and a fucking jacket. I wonder who they're going to take more seriously today. Hey, Look good, feel good. Look good, feel good, baby.

That's all that's all I have to say. Let's go. Let's talk A. No one wants to talk about what you're wearing anymore.

So, um, one of your biggest happy topics is the bullshit radar. Um, and that is completely maxed out. So, let's start with the obvious. Like everyone's shouting out AI and go to market right now.

What's the most egregious things that you're you've seen to date? Oh, I I mean, I feel like 90% of it is egregious, man. I I feel like when people are talking AI um and go to market, what I'm really seeing is I use chat GPT. I use Claude.

And it's not real AI. It's, oh, like I'm automating my emails or, oh, like I I set up agent mode to, you know, send me a uh a daily list of my tasks. Like, listen, that that's cool, right? I have I I use an agent to get a daily list of my tasks.

But if I were to go to a founder who said, how do you use AI and say, oh, I get an automated list of my tasks, I would expect to be laughed out of the room. I think for me where I really see it being egregious is the low value chat GPT or Claude skins where what you really have is chat GPT with a pretty front end or UI, and you don't really have a product. And you're convincing people that you have this cool AI because you strung two prompts together. That is not AI in any way, shape or form.

I I think the, I think part of the challenge people are feeling, like just a a long time ago, I was at a AI company, I was doing voice AI, and I went to the engineers and I was talking to them like, you know, are we really doing AI? And they're like, no, it's just like a rule engine or their decisions or their orchestrations being made, but there's not really true AI. And so while there are things that are truly AI, I think the challenge becomes, how do you identify them? How do you build a strategy around them?

And what are you actually doing about those strategies and orchestrations that are going to drive from an AI perspective? Um, so just using Chat GPT and just building out, you know, your daily tasks or, you know, it's not it's not going to move the needle enough, especially in an in an organization. Personally, yes. Individually, yes.

But from an uh uh organization perspective, that's never going to move the needle. So, I I What what are where where what are GTM teams failing and vaporware in this space? Like, what Chat GPT's one thing, but like there's so many other technologies. What other things are people trying to use that are just like not working?

So, that's a loaded question, right? I I I would rather focus on what are people using that I think is working. Because the things that aren't, I I honestly I I don't know cuz I don't really hear about those. Um what I and I'm going to talk out of both sides of my mouth.

So, I'm a huge user of Bolt. uh nu, right? I love it. I think it's great for low code, dare I use the word, vibe code building simple apps, uh simple interfaces that would have taken anywhere from $40 to $50,000 and, you know, weeks and weeks to months of engineers' times.

Think ROI calculators, think um simple landing pages, um think light scale apps to, you know, do certain various tasks. And I think that that's a a really good use of AI for, you know, someone who's bootstrapped, who doesn't necessa can't necessarily afford, you know, uh a high dollar, you know, coder and team, or think someone who just needs to build something really fast. Where I think people are getting confused and where I think people are going to screw themselves is thinking that a tool like Bolt or Lovable is going to build an enterprise-grade application. Listen, I I built an ROI calculator for us.

I built a couple for clients. It's great for an ROI calculator as a lead magnet. Am I going to go build, you know, a full scale compliance solution that's going to, you know, pass SOC two? Absolutely the F not.

Um and I think that now more Do you even know what SOC two is? than ever. You know what SOC two is? Um I I think now more than ever, customers with newer companies that aren't established, need to be really careful and ask the right questions about the back end infrastructure, um of tools.

I'll give a perfect example. In for one of our clients, I I built a compliance calculator and it's great. Where's the data going? Like great, the customer gets the data, but where does the data go?

So we we, you know, we built super base and all sorts of other things, but like this is stuff that I had to learn and I didn't know about. So if you're going to build something for a client and customer information is coming into that, like you got to be really clear about where your data is going so you're not putting your client at risk. If you're a company that's working with one of these folks that are building things like this, like you got to be really clear about where your data is going so you don't put yourself at risk. That is a super good point.

And I think where I I think people will get frustrated as well because I think as good as some of these things are or as bad as some of these things 100%. Because like you developed this like cool little gooey UI interface thing. You're like, wow. And I remember like when I coded back in college, that was my first thing.

Like I remember writing my first line of code and it like saying back to me like, hello, Dale on the screen. I'm like You were so excited, right? I wrote something and it wrote back to me. Yeah.

And it's like I think that that newness of the AI world in enabling what was once termed the citizen developer, kind of like these business people that can build these applications, um, have a place where they can see something that they're writing develop into something that could be used is is super exciting. There's a lot of infrastructure, back end, like you're talking databases, scaling. There's a lot of things that people don't truly understand from an architecture perspective. But where I'd like to bring the conversation is actually up to a higher level.

And it's not just go to market. Um, what I'd like to make sure people get is that there is a strategy behind all of these things. And not only a strategy Build it and they will come, Dale. Build it and they will come.

Yeah. Yeah, yeah, yeah. And so, one of the things we've been talking to a lot of investors as well as CEOs about at the moment is this concept of an AI charter. And in this concept of an AI charter, there's stuff like governance, there's stuff like, uh, who's going to be using what?

Making sure that you have brand voice, um, making sure that your data is not getting leaked. Like there's a lot of things that need to be wrapped around that, and it's not just in go to market. We find with our clients because we know go to market as domain experts, we find that you can actually build these things super easily, um, or you can, that's where we see the efficiencies. Now, someone that has been in finance all the time may say, hey, we should be using AI in, you know, spreadsheet applications or in something else that I'm trying to do analysis on.

And so, I think there'll be if we pull it up a level, this AI charter will help organizations really figure out what you're trying to accomplish. So what's the strategy? Like what's the outcome you're trying to accomplish? I'm not just trying to give myself back more time, but in an organization, I'm trying to reduce my expenses, drive more revenue, get more leads, close more deals.

And then you can start attacking these things one at a time. The other big thing I think that's going to happen is people are like, AI, let's go build everything in AI and then it's going to completely fail as well. So, I'm curious your perspective on that. You you're spot on.

Where I think people go wrong is they're looking at, excuse me, it's almost as if they're using AI as the growth at all costs. And and let me just explain what I mean by that real quick. So growth at all costs, we're all familiar with, right? Dale, I need to hit $20 million this year.

I'm going to hire 20 reps. I'm going to give them all a million dollar quota and shit, man, we're going to hit $20 million. We all saw how that worked out, right? It doesn't work out well.

But what I feel I'm seeing now with a lot of um founders, CEOs, RevOps leaders, sales leaders that I talk to is, oh, I I'm just going to use AI for that. Blanket statement. No AI charter, no deliverables, no scope, no idea of what the metrics are, like, oh, I I want to improve pipeline. I'm just going to use AI for that.

What the fuck do you mean you're just going to use AI for that? It's the same as, oh, I'm just going to go hire 20 people. So to your point of an AI charter, it's the same thing. You have to be very specific, just like you're building a team.

What is the purpose? What are the goals? What are the deliverables? What is acceptable and what isn't?

What's the data privacy? What's the data security? Who has access to this? How many people have you and I both personally spoken to in the past 30 days that are using a public version of Chat GPT and uploading all of their damn financial records.

Like it blows my mind. My wife's company literally has a policy if you get caught using a non-company version, you will be fired immediately. Like that's how seriously they take their data. Yeah, it's it it it does need to be thought through and people, I think it's like some people that have they click through the like accept all the terms and user.

Right, because no one reads the 37 What are you going to do? You're going to you're going to message OpenAI and say, sorry, I'd like to redline term 57B. I'd imagine that's not going to work well. Yeah, it's true.

All right, let's let's let's shift gears for a second. So, let let let's talk about some buckets of AI and go to market. And and I want to kind of map this landscape and I want your thoughts on like, what are the real categories of AI usage right now? So, and and whether they're good or bad.

So, the most common one I see for better or worse, Dale, content and outbound. I'm going to use AI to build my email copy, to build personalization and say, hi Dale, I saw you were in LA last week. I happen to live in LA and it's a great email. It's not.

Number two, and I think this one is arguably a much better use case in my opinion, that intelligence and enablement, right? So, think think things such as summarization, automation, uh light agents or super agents like attention, deal rooms, coaching platforms like Grow AI. Um, I I think that that takes it up to another level. And then thirdly, workflow and automation.

So, this is your routing, your enrichment, we're going to get a little controversial, agent-based outreach, which we'll talk about. Which one of these categories or two of these categories do you actually think makes reps more dangerous and is where companies should be investing their time and money? Or, blow it off. Tell me they're all the wrong use case.

Yeah, I I would say the intelligence and enablement side of the world. Um, the things that take a lot of time when I'm working with a lot of reps are like all the research. Wait a minute, you work with reps? Who am I going to reach out?

Very confused here. All my reps are president's club reps, so I I don't know where your reps end up going. Um because that's where it takes a lot of the time. It's it's not the actual work of calling people or sending an email or it's like finding the research, understanding what they're their challenges are.

Like all of those pieces take a lot of time. So, if we could take 30 minutes of, you know, we used to always talk about the three by three, like find three pieces of data in three minutes and blah, blah, blah. Like, you could find that information super easily right now. And then understanding how your value proposition may map to those particular situations.

Um, and taking the time to write the content based on what you learn, not not anything like, hey, you're in California, I'm in California. Let's let's connect and have a conversation. It's more like, hey, we have seen that people have been struggling with XYZ, it's costing them thousands of dollars, uh, an hour, we can help you build XYZ. So, it's what what's the impact that they're having on the value you're trying to deliver?

And so, I think the intelligence part, the the content and outbound, I think is overhyped. Marketing destroys all this stuff. Sales has been destroying all this stuff. I do think there is a place for workflow and automation.

Um, I don't believe in the AI SDR outreach thing. Don't skip ahead, Dale. Is complete horse shit. Um but that that's kind of where I would see the best use of time right now.

Um and at a macro level, like if I if I go to the CEO level, um as they're looking for maybe funding or uh conversations with investors or their team, like utilizing that research function and capability to gather the data um and to get prepped for meetings so they don't have to do all the research. So that's where I think um content and outbound AI should be used. Um I I have yet to see AI that I think truly generates good copy without human intervention. Um I think it's all the same, you know, I notice this, I saw that, um, trigger-based stuff.

But I think the research of what people used to have to spend time doing, whether that be as a BDR, an AE, a CEO, reading through 10Ks, listening to podcasts, like I think you could just speed up the process of zero to revenue. Um but the intelligence is exactly it, right? Like how do we drive um getting that information in the right hands and making it actionable? Coupled with, in my opinion, the workflow automation.

Um I think there's so many manual. I I could wait for you to be done typing. I'm fucking with you, but I hear it in my ear. Um I'm normally the one guilty of this you all, not Dale.

Um the workflow automation, I think is an interesting one, but I think that that is arguably fairly complex. Um and I think that if you do it wrong, and I've seen it done wrong where people just pop AI into, you know, Hubspot through the cloud connector or the GPT connector and try to build out some workflows and they're not taking into account um the things they could break, which we'll talk about in a minute about AI not being a GTM strategy. Um but where where does it introduce risk, right? Or or remove too much human friction?

And I'm going to tie this to my last question I have on this topic, and I'm going to go on a little bit of a rant. AI SDRs, vision or delusion? So, I I agree with you. You could not give me enough money to have an AI agent or person calling out as an SDR.

Um I think there's so much risk there to burning your TAM SAM SOM where you have such shit messaging. I think it was six months or so ago, there was this arguably viral clip going across LinkedIn about this Tesla AI SDR. And I don't think it was Tesla that did it, but the company used Tesla as a use case. Um just to make sure that we're not throwing Tesla under the bus for all you Tesla fans.

Um but it was just bad. Like I still believe, listen, I do think there's a place for AI when it comes to cold outbound, but I I I still believe humans want to buy from humans. What are your thoughts? What do you think?

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Yeah, I I actually am going to go a step further. I think human to human, but I actually believe that it's going to be human to human in person. Um, I don't think it's just going to be human and and obviously deal size and a bunch of things. I I I live in the, um, I live in the enterprise world.

Um, so Black scale flex. I think I think, um, I think that enterprise motion is going to get much more in depth with in-person, small events, not these big events, um, and enable people to like weed out the noise of all the automation. Yes, we could still use automation and recaps and setting things up, but, um, but that the actual sale process of it will be uh in person. And will be more important from a networking perspective.

Like who you know, how you know them, how you're going to get connected, because that's the only way you're going to get I think more important than network will be in person. Like listen, we're we're at a client on site now. What's one of the things I said yesterday? Who's getting on an airplane?

Um, like at the end of the day, you've got to stand out. Yeah. Cool. So, let's um, let's let's let's finalize and and go through the next iteration of um of the process.

I think where we want to go next is is AI a strategy? Is it a process? Is it what what is AI and how can you leverage it for go to market? Um, AI is not a go to market strategy.

Um, AI is part of your go to market strategy. I think what people think is, I'll give you a perfect example. They're going to bolt some AI on and it's going to solve their problem. So, I am, and I I'm not, example.

I need to do a deep pipeline analysis for my board. They want to know everything about my pipeline, my deal stages, uh where deals are, deal velocity, everything that a board would want to know, right? That historically, your RevOps person is going to spend a good amount of time running numbers using reports from Salesforce, Hubspot, whatever it happens to be to put this information together. Well, now they're really excited because all they have to do is go to their public version of Chat GPT, use the connector, connect it to Hubspot, prompt it with natural language and ask some questions and it's going to give you this whole dandy little report, right?

The problem here is shit in is shit out. So, all that you're using AI to do is to regurgitate your crappy data because you haven't gone to the core issue of fixing the data problem. If all of this information isn't being put in the CRM correctly, and you're not following best practices, congratulations. You got all the data in, you know, three and a half minutes plus another five minutes to reformat it, so sub 10 minutes you have your report.

But it's not good data. And now you're going to the board with this fancy report that's talking about your conversion cycles that are, you know, 16 days longer than average. Well, we're we're not even touching on the fact that the reps are putting deals in that aren't deals or the reps are close not closing deals that should be closed loss. Like AI can't pick that up yet.

So, I I find that a lot of leaders are for lack of better terms, trying to oversimplify things by bolting AI on versus solving the core problem first and then using AI, going back to your AI charter. Yeah, and I I think that's that's really important. It it is a part of a strategy. When um, as I think through a lot of the things that are happening in the AI world, um, the problems are the same.

So whether and this is not just in go to market. Like the problems are the same. You're having problems, bottoms up modeling, you're having problems uh with top of funnel. You're having like whatever you're you're having problems with recruiting.

Like all of these things could be a challenge. Um, yes, AI is a way to solve it without the traditional way of solving it. So, traditional way of recruiting is having a bunch of recruiters out there scoring the internet, calling people, etcetera, etcetera. Or you could leverage AI as a part of that strategy and mix it in with the human uh human part of it.

So, the problem remains the same. The way we are solving the problem is could be traditional, could be AI, could be a mixture of both of them. And I think only until you identify the problems that you're trying to solve for and how you are going to solve them, you actually get into a place of mixing or integrating AI into an overall strategy, whether it's GTM or something else. Yeah, I I think you're you're spot on.

The this is the biggest one that I just think is a miss because of how fast AI is going. Um where the world, for lack of better terms, thinks it's a strategy and it it's not. And you have to be really careful because people are going to call you out on your bullshit, um really fast. So, if if you're a CRO right now, so we'll we'll take you back a little bit.

So, you're a CRO at whatever company. Um you have, you know, a VP of sales, a VP of marketing, you report to the CEO. How do you evaluate what AI investments are are actually worth it and which ones are just noise? Um, I evaluate it by actually using it.

Um, and I actually get my hands dirty and figuring out what's working and what's not working. I I'm not taking I'm I'm educating myself in the literary side of it, and then I'm actually using it to figure out what I can and can't do. Um, this is a big advantage, I think people have if they actually do the work is that they can, um, figure out what is fact and what's myth. And so, um, as I was a at when I was a CRO, because I did development work and I was in the a any of the technical any of the technical conversations, I actually could talk about it a lot better than most other CROs.

And so, I I push that into the AI space. So, if I was a CRO, and I was looking to use some technology, I would really try to just figure it out from the ground up. Yeah, I I love it. And I think that's important, right?

This isn't something that you could just pawn off um and hope someone else does it. You you have to be hands on. You have to be learning. I do not believe that AI is going to quote unquote eliminate 60, 70% of everyone's job.

I do believe if you don't understand how to use AI, if you don't learn AI, if you don't learn how it can accelerate everyone on your team, you are at a massive, massive risk. So, we we have a couple more minutes. I want I want to flip it here. I I know my answer.

I'm curious your answer. What's it one company, one team or one approach that's doing this really well right now? Um, I think the companies that are doing it well actually were not even around, um, you know, two years ago. So I think I'm thinking of like I Swan where they're building it from the ground up and they're thinking of it from an autonomous business engine.

Um, will they get there the way they're thinking about it? Maybe, maybe not. I like it's still to be determined. Um, how far you can push the AI because I I think some some of it is a little bit early.

Um, because you you're going to have like humans get in the loop on this stuff. Like when buyers get in the loop, like there's there are things that are going to challenge you. But I think those are the companies that have a huge advantage. It actually levels the playing field with the bigger players in the space.

So like if you have someone that has $10, $15 million, but they're laden a bit with um legacy, the way they solve problems, and you have an up-and-comer that is thinking about it from an AI native autonomous perspective, they will have the advantage even though they don't have the name recognition. Yeah, I agree with you. I think that's a great example. Um no surprise to anyone listening.

I think the other great example is attention. Um I think, you know, what started out as conversational intelligence, what mapped into morphed into a little bit of, you know, agents and now like the super agent that you could literally give, you know, 15 tasks and tell it to take this action item and put it in click up and take this action item and send this email. Um what happened on my last five deals? Like I think they're doing a lot of cool things.

Um it's going to be exciting to actually see AI that can truly improve pipeline quality, performance, um and not just be one of these things that um for lack of better terms, uh automates tasks. So, let me ask you a question. You're starting a new go to market from scratch. What's the very first AI tool you're going to bring in?

And what's the last? Ooh. That's for putting you on the spot. Very yeah, very first tool is probably um like the the open AI or Claude, like depending on which where I'm going.

Um that would be like more of a platform type play where I'm I'm leveraging it for multiple things and being able to use it for multiple things. The last one I'm bringing in, I think any of the ones that were built like two years ago, like they're just outdated already. Like the product. It changes so fast, right?

Yeah. Uh like I don't want to name anybody out, but some of the ones that I saw early on, they were just too early in the game. 100%. Dale, what's one AI promise that's never going to come true?

Um, that robots are going to take over the world. I like that one. I'm going to go full fully autonomous AI outbound. What uh what's the most underrated AI use case that no one's talking about?

Um, I think bottoms up modeling and connecting to the data and I mean, we didn't do it well in the beginning and I don't think people know it very well. And they like conceptually they think top down modeling. So, I think it's that it's less of an AI thing and more of a mindset shift, but you can leverage AI to do it. Will you go on record and say your biggest AI sales tool disappointment?

Or you're going to pass on that? Uh big AI I don't really have one just yet because I cuz they're all just so new, so I don't really have one. I'm just thinking. No, I don't I don't have no have one just yet.

I have a couple uh anyone listening, you could DM me if you want to talk about those and I'll prevent you from buying them. Um but I'm not not going to publicly shame someone here. Um all right, last question, Dale. One question every go to market leader should ask before buying any AI tool.

Um, the question I would ask is what's the vision of the product in the next six to 12 months? Hm. I like it. I like it.

All right, y'all, that is our vision on AI as it stands in go to market today. If you are going to be in the Salt Lake City area on Wednesday, August 27th, we are doing a AI focused true go to market workshop where you will get real tactical go to market foundations to help drive your business using AI the right way. This is going to be at Kiln in Salt Lake City. We're partnering with our friends at Growth Elevated, sponsored by our friends at Attention, Chili Piper, and EOS Worldwide.

Drop Dale or I a DM if you want to go. We are limiting this to 30 people. We have about eight seats left. We may or may not have a special code that we could give you.

Um but thanks for listening, y'all.