Episode #111 Why AI Is NOT a Go-To-Market Strategy (And What To Do Instead)

Everyone is talking about AI in go-to-market, but most of it is noise. In this raw and unfiltered episode of Bridge the Gap, Adam Jay and Dale Zwizinski cut through the hype to break down:

 • The real AI use cases that move revenue (and the ones that are pure vaporware)
 • Why AI is not a strategy—but must be part of your GTM strategy
 • The biggest mistakes CROs, founders, and RevOps leaders make when adopting AI
 • How to evaluate which tools are worth investing in and which will sink your pipeline
 • Why “AI SDRs” could destroy your brand before they help it

If you’re a founder, CRO, RevOps leader, or seller trying to figure out how to integrate AI without automating yourself into irrelevance—this episode is for you.

PS - huge shout out to Sendoso for sponsoring our show.

We could not do this without you.

See how Sendoso can help increase pipeline, ROI, and customer retention.

🎁 Lastly, we have a gift for you! We’re tired of seeing people getting critical GTM components wrong. Need help with your ICP, Buyer Persona, and Value Prop? Tired of the shitty “resources” people “give away” to gain followers?

We’ve developed a tool that creates your basic GTM Foundations (ICP, BP, abd Value Prop) for you. Snag it here.

Transcript

This is Bridge the Gap powered by Revenue Reimagined, the podcast where we dive into all things revenue. Each episode, we bring you the top founders and go-to-market leaders to challenge how you think about growth and help you bridge your biggest go-to-market gaps. I'm Adam Jay. 

And I'm Dale Zwizinski. As always, thanks for hanging with us. There's a million ways you can be spending your time and we're grateful for you choosing to spend it with us. Be sure to check out our newsletter if you want the show notes and tactical advice on how to bridge your GTM Gaps. Let's get to it. Welcome back to another episode of the Bridge the Gap podcast powered by Revenue Reimagined. And today, oh, 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 going to get a little more 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. 

So, 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 is beautiful. We are on site with a client. We have an executive meeting today where the CEO is like, totally casual, don't worry about it. I am in an all-bit upscale T-shirt. 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 I have to say. Let's go. Let's talk. No one wants to talk about what you're wearing anymore. One of your biggest happy topics is the bullshit radar. 

That is completely maxed out. Let's start with the obvious. Everyone is shouting out AI and go to market right now. What's the most egregious things that you've seen to date? I mean, I feel like 90% of it is egregious, man. I feel like when people are talking AI 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, I'm automating my emails. Or, oh, I set up agent mode to send me a daily list of my tasks. 

Listen, that's cool. 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 me to laugh down 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 think part of the challenge people are feeling, a long time ago, I was at an AI company. 

I was doing voice AI. And I went to the engineers and I was talking to them, 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? So just using chat GPT and just building out your daily tasks or it's not going to move the needle enough, especially in an organization. Personally, yes. 

Individually, yes. But from an organization perspective, that's never going to move the needle. So what are GTM teams failing and vaporware in this space? Chat GPT is one thing, but there's so many other technologies. What other things are people trying to use that are just not working? So that's a loaded question, right? I would rather focus on what are people using that I think is working than the things that aren't. I honestly, I don't know because I don't really hear about those. And I'm going to talk out of both sides of my mouth. So I'm a huge user of Bolt.new, right? 

I love it. I think it's great for low code, dare I use the word, vibe code, building simple apps, simple interfaces that would have taken anywhere from $40,000 to $50,000 and weeks and weeks to months of engineers' time. Think ROI calculators, think simple landing pages, think light scale apps to do certain various tasks. And I think that that's a really good use of AI for someone who's bootstrapped who can't necessarily afford a high dollar coder or end team or thinks somebody 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 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 a full-scale compliance solution that's going to pass SOP2? 

Absolutely the F-NOT. And I think that now more... Do you even know what SOP2 is? I do know what SOP2 is. 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 of tools. I'll give a perfect example. 

For one of our clients, I built a compliance calculator and it's great. Where's the data going? Great, the customer gets the data, but where does the data go? 

We built SuperBase and all sorts of other things, but 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, customer information is coming into that. You've got to be really clear about where your data is going so you're not putting your clients at risk. 

If you're a company that's working with one of these folks that are building things like this, you've 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 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 are. Because you develop this cool little GUI interface thing. 

You're like, wow. And I remember when I coded back in college, that was my first thing. I remember writing my first line of code and saying back to me, hello, Dale, on the screen. 

You were so excited, right? I wrote something and it wrote back to me. I think that newness of the AI world in enabling what was once turned the citizen developer, these business people that can build these applications, have a place where they can see something that they're writing develop into something that could be used, is super exciting. There's a lot of infrastructure back end like you're starting 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. What I'd like to make sure people get is that there is a strategy behind all these things. Build it and they will come, Dale. Build it and they will come. 

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 who's going to be using what, making sure that you have brand voice, making sure that your data is not getting leaked. There's a lot of things that need to be wrapped around that and it's not just 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 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 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. Your 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 let me just explain what I mean by that real quick. 

So growth at all costs, we're all familiar with. 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 founders, CEOs, RevOps leaders, sales leaders that I talked to is, oh, I'm just going to use AI for that. Blanket statement. No AI starter, no deliverables, no scope, no idea what the metrics are. Like, oh, I want to improve pipeline. I'm just going to use AI for that. Talk to 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 starter, 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 of 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 have 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 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. 

Right, because no one reads the 37. What are you going to do? You're going to message open AI and say, sorry. I'd like to red line term 57B. 

I'd imagine that's not going to work well. Yeah, it is true. All right, let's shift gears for a second. So let's talk about some buckets of AI and go to market. 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 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 things such as summarization, automation, light agents or super agents like attention, deal rooms, coaching platforms like growth. So AI, I think 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 up. Tell me they're all the wrong use case. 

Yeah, I would say the intelligence and enablement side of the world. The things that take a lot of time when I'm working with a lot of reps are like all the reasons. Wait a minute, you work with reps? 

Who am I going to reach out? He's very, very inferior. All my reps are president's club reps. So I don't know where your reps end up going. Because that's where it takes a lot of time. It's not the actual work of calling people or sending an email or it's like finding the research, understanding what their challenges are. All of those pieces take a lot of time. So if we could take 30 minutes of, 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 and taking the time to write the content based on what you learn. Not anything like, hey, you're in California. I'm in California. 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 an hour. We can help you build XYZ. So it's what's the impact that they're having on the value you're trying to deliver. And so I think the intelligence part, the content now found, 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. I don't believe in the AI, SDR outreach thing. 

Don't skip ahead to help complete or shit. But that's kind of where I would see the best use of time right now. And at a macro level, like if I go to the CEO level, as they're looking for maybe funding or conversations with investors or their team, like utilizing that research function and capability to gather the data and to get prepped for meetings so they don't have to do other research. That's where I think content and outbound. AI should be used. 

I have yet to see AI that I think truly generates good copy without human intervention. I think it's all the same. I noticed this. I saw that 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 10K, is listening to podcasts. I think you could just speed up the process of zero-to-revenue. But the intelligence is exactly it. How do we drive getting that information in the right hands and making it actionable? Coupled with, in my opinion, the workflow automation. 

I think there's so many manuals. I could wait for you to be that type. I'm fucking with you, but I hear it in my ear. I'm normally the one guilty of this. 

You are not Dale. The workflow automation, I think, is an interesting one. But I think that that is arguably fairly complex. And I think that if you do it wrong, and I've seen it done wrong, where people just pop AI into HubSpot through the Cloud Connector or the GPT Connector and try to build out some workflows, and they're not taking into account the things they could break, which we'll talk about in a minute about AI not being a GTM strategy. But where does it introduce risk, right? 

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 agree with you. You could not give me enough money to have an AI agent or person calling out as an SDR. 

I think there's so much risk there to burning your Tamsam Psalm, where you have such shit messaging. I think of a 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, just to make sure that we're not throwing Tesla under the bus for all you Tesla fans. But it was just bad. 

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

What do you think? People buy from people. That's why companies who invest in meaningful connections win. The best part, gifting doesn't have to be expensive to drive results. 

Just awful. Sendoza's intelligent gifting platform is designed to boost personalized engagement throughout the entire sales process. Trust me, I let sales for a Sendoza competitor and I could tell you no one does gifting better than Sendoza. 

If you're looking for a proven way to win and retain more customers, visit Sendoza.com. Yeah, 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. I don't think it's just going to be human and obviously deal size and a bunch of things. I live in the enterprise world. 

Flex, now, flex. I think that enterprise motion is going to get much more in-depth with in-person, small events, not these big events, and enable people to weed out the noise of all the automation. Yes, we could still use automation on recaps and setting things up, but the actual sale process of it will be 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 connected. I think that's an effort today to be in-person. 

Listen, we're at a client on site now, which is one of the things I said yesterday. Who's getting on an airplane? Like at the end of the day, you've got to stand out. Cool, so let's finalize and go through the next iteration of the process. I think where we want to go next is AI a strategy? 

Is it a process? What is AI and how can you leverage it for go-to-market? AI is not a go-to-market strategy. 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. 

I'm not an example. I need to do a deep pipeline analysis for my board. They want to know everything about my pipeline, my deal stages, where deals are, deal velocity, everything that a board would want to know. 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. 

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. The problem here is shit in is shit out. 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 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 16 days longer than average. We're not even touching on the fact that the RevOps are putting deals in that are deals or the RevOps are not closed-losing deals that should be closed-lost. Like AI can't pick that up yet. So 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 think that's really important. It is a part of a strategy. As I think through a lot of the things that are happening in the AI world, the problems are the same. 

This is not just in go-to-market. The problems are the same. You're having problems, bottoms up modeling. You're having problems with top of funnel. You're having problems with recruiting. All these things could be a challenge. Yes, AI is a way to solve it without the traditional way of solving it. Traditional way of recruiting is having a bunch of recruiters out there scouring them, internet calling people, et cetera, et cetera. Or you could leverage AI as a part of that strategy and mix it in with the human part of it. 

The problem remains the same. The way we are solving the problem could be traditional, could be AI, could be a mixture of both of them. 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. Yes, I think you're spot on. 

This is the biggest one that I just think is a miss because of how fast AI is going, where the world, for lack of other terms, thinks it's a strategy and it's not. You have to be really careful because people are going to call you out on your bullshit really fast. If you're a CRO right now, we'll take you back a little bit, so you're a CRO, whatever company. 

You have a VP of sales, a VP of marketing, you report to the CEO. How do you evaluate what AI investments are actually worth it and which ones are just noise? I evaluate it by actually using it and I actually get my hands dirty in figuring out what's working and what's not working. I'm educating myself in the literacy side of it and then I'm actually using it to figure out what I can and can't do. This is a big advantage I think people have if they actually do the work is that they can figure out what is fact and what's myth. When I was a CRO, because I did development work and I was in any of the technical conversations, I actually could talk about it a lot better than most other CROs. I pushed that into the AI space. 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. 

I love it and I think that's important. This isn't something that you could just pawn off and hope someone else does it. 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. We have a couple more minutes. I want to flip it here. I know my answer. 

I'm curious your answer. Was it one company, one team or one approach that's doing this really well right now? I think the companies that are doing it well actually were not even around two years ago. I'm thinking of a swan where they're building it from the ground up and they're thinking of it from an autonomous business engine. Will they get there the way they're thinking about it? 

Maybe, maybe not. It's still to be determined how far you can push the AI because I think some of it is a little bit early because you're going to have, like humans get in the loop on this stuff, like when buyers get in the loop, 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. 

If you have someone that has $10, $15 million, but they're laden a bit with legacy the way they solve problems, and you have an up and comer that is thinking about it from an AI-native economist perspective, they will have the advantage even though they don't have the name recognition. I agree with you. I think that's a great example. 

No surprise to anyone listening. I think the other great example is attention. I think what started out as conversational intelligence, what mapped into, morphed into a little bit of agents and now the super agent that you could literally give 15 tasks and tell it to take this action item and put it in click-off and take this action item and send this email. 

What happened on my last five deals, like I think they're doing a lot of cool things, it's going to be exciting to actually see AI that can truly improve pipeline quality performance and not just be one of these things that, for lack of better terms, automates tasks. 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? What's the last? 

I'm not from putting you on the spot. Yeah, very first tool is probably the open AI or quad, depending on where I'm going. That would be more of a platform type play where I'm leveraging it for multiple things and be able to use it for multiple things. The last one I'm bringing in, I think any of the ones that were built two years ago, like they're just outdated already. Things are so fast, right? I don't want to name anybody out, but some of the ones that I saw early on, they were just too early to begin. 100%. Yeah, what's one AI promise that's never going to come through? That robots are going to take over the world. 

I like that one. I'm going to go fully autonomous AI outbound. What's the most underrated AI use case that no one's talking about? I think bottom's up modeling and connecting to the data. 

We didn't do it well in the beginning, and I don't think people know it very well. Conceptually, they think top-down modeling. I think it's less of an AI thing and more of a mindset shift, but you can leverage AI to do that. 

Will you go on record and say your biggest AI sales tool disappointment? Or are you going to pass on that? I don't really have one just yet because they're all just so new, so I don't really have one. 

I'm just thinking. No, I don't have one just yet. I have a couple. Anyone listening, you can DM me if you want to talk about those, and I'll prevent you from buying them. 

But I'm not going to publicly change someone here. All right, last question, Dale. One question every go-to-market leader should ask before buying any AI tool. 

The question I would ask is, what's the vision of the product in the next six to 12 months? 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 a 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. Thanks for listening, y'all. Thanks so much for listening. We hope you enjoyed the conversation as much as we did. 

As we say at the end of every show, give more than you receive. Reach out to someone today and offer your assistance. Don't forget to sign up for our newsletter at revenue-reimagines .com. For your chance to win today's giveaway, member only exclusives and actionable tips delivered directly to your inbox. 

We would really appreciate if you head over to your favorite podcast site, drop a five star review, and share your favorite episodes with your network. Until next time.