AI Strategy Starts With Leadership, Not Technology

0:00John Jantsch:So what happens to a business with the entry-level work that trained your people gets absorbed by AI? Today's guest has been thinking about that maybe harder and longer than most, and his answer is possibly uncomfortable. The traditional path from junior to senior breaks, and most organizations have no plan for what replaces it. You know, most small businesses don't have a marketing problem. They have a strategy problem underneath the marketing. I wrote a new workbook called Seven Steps to Small Business Marketing Success that walks through exactly how to fix it. From getting clear as a founder all the way to running marketing like an operating system.

0:39John Jantsch:20 years of working with small businesses condensed into a framework you can actually use. And right now it's only five bucks. Go grab it at dtm.world slash seven steps. That's dtm.world slash seven steps.

1:04John Jantsch:Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantz. My guest today is Paul Ritzer. He is a former, or I'm sorry, he's the founder, not former, and CEO of SmarterX and Marketing AI Institute and co-author of Marketing Artificial intelligence. He launched the marketing AI conference, Mekon, co-hosts the artificial intelligence show, and has delivered more than 200 keynotes for AI for organizations, including Google, LinkedIn, and the US government. I think after ChatGPT launched, even though Paul was on the trail, that certainly opened up many doors for him.

1:41John Jantsch:So Paul, welcome back to the show. China, it's always good to be with you and to catch up. It doesn't happen often enough. I think your first appearance was when PR 2020, maybe book-wise was, that was the name of the book, right? The agency was PR 2020. That was the agency I sold back in 2021. And then we had, I don't know, the marketing agency blueprint and the marketing performance blueprint. It could have been one of those that we were on for. Awesome. All right. Well, let's dive into the AI Institute. You built it really to help marketers understand AI. And then it just kind of blew up, right?

2:12John Jantsch:I mean, it was an idea that then... Seven and a half years later.

2:19John Jantsch:So, what made it clear that you needed to build that, which at the time was kind of outside of the marketing realm. Yeah. So, I'll give the quick origin story. So, actually, it goes back to the PR 2020 days. In 2011, I wrote the marketing agency blueprints. That was my first book. And at the time we were a few years into being HubSpot's first partner and kind of at the forefront of marketing technology and social media and inbound marketing and content marketing and all of those things. And that was the year IBM Watson won on Jeopardy. And I became obsessed with understanding how that technology worked.

2:54And then could it actually be applied that same idea that was basically a prediction engine, take data in, understand the language behind it, then you make predictions about what comes next. And so I started working on this concept of what I was calling a marketing intelligence engine. And this is back in 2012 and 13. And the premise was, if we could use Watson-like technology to predict what to do next, what next best action, next strategy, how to spend our marketing dollars, then we could build an entirely new way of doing marketing. And so that was the original hypothesis. And I shared that idea in my 2014 book.

3:29And then that was like out of the 50 ,000 word manuscript, it was like a thousand words. and the book was not about AI otherwise. And that was all anybody wanted me to talk about. And so fast forward to 2016 and we were like, well, what do we do with this? Like, I'm really intrigued by it. I'm convinced it's gonna change marketing and business in the world, but like, I don't really know what's possible. So we created the Marketing Institute to research it ourselves and then tell the story of AI. Like what was real, what was happening? And so, yeah, we created the Marketing Institute in 2016 And then like I always half joke, like we survived long enough financially for ChatGPT to show up.

4:09I sold my agency in 2021, focused exclusively then on AI and the Institute and eventually SmarterX. Raised a seed round of funding that kind of got me through the really lean years. And ChatGPT came and all of a sudden the interest in AI exploded.

4:25John Jantsch:So I've been through, I've been doing this a long time. I've been through several of these game changing technologies that came along. And there seems to be this curve, you know, there's the early adopters, of course, and, you know, and then there's the over hypers, you know, and then there's like, oh, my God, I guess it's not going away. We better figure it out. And then there's just now it's plumbing. We don't even call it anything anymore. Do you see AI having a similar path, even if it's faster and more disruptive? I did. So my belief was actually by 2020, we wouldn't have to call it AI anymore.

5:01I just thought it was going to be like marketing and software and stuff. So what I've always said was I overestimated how quickly everyone else was going to figure this out and the impact it would have like in the near term. But then I underestimated the long term, like true transformation was going to cause to the economy and businesses and things like that. So I have always had this feeling that like, well, maybe we shouldn't even call it an AI institute or AI technology or whatever. We shouldn't differentiate in that way. But I've now become convinced that we have a very extended runway ahead of us where being AI matters, like being AI forward matters, like it's a differentiator within organizations to say that you're AI forward, that you understand the technology, you use the technology.

5:45And then as a business, I think it's becoming fundamental for leaders of businesses to be able to think of themselves as an AI forward organization, that they're looking at ways to infuse it into people, processes, technology. And so, I don't know, it's like I thought we would be past it by now. And I honestly, I feel like we're just in the first innings still.

6:04John Jantsch:Yeah. Yeah. You think about how many defunct social media marketing agencies are out there, for example. Right. And I think your idea that, oh, we don't want to, it's great, that's the thing now, but we don't want to go down that to where it just becomes, you know, business consulting or something. But, you know, I think one of the major differences is AI is impacting every area of a business. I mean, you know, the finance people are using it, the operations people are using it. I mean, obviously the marketing people are using it. And I think that's probably a significant, I mean, there are many others, but would you say that's maybe in some ways why it's, you've got this long runway is because, you know, it's basically going to impact everything?

6:46Yeah, I said years ago that I believed that AI was going to become the underlying operating system to businesses and society, that it was literally going to be woven into every aspect of what organizations do, their people, their processes, their technology. And then within society, it was going to become the epicenter of the economy. It was going to basically be the driver of growth. And that's all starting to happen. And so I do think that...

7:11John Jantsch:There are definitely people suggesting that's where we are. Yeah. Yes. It's like if we stopped building data centers right now, and if the five technology companies that are spending north of 80 to 100 billion a year on AI infrastructure stopped doing it, the economy would crumble. Like, whether people realize it or not, we have become an AI-driven economy for better or for worse. And so, yeah, I think we've gotten to the point where it's a general purpose technology. Social media is a tool. This is on par with, like, the invention of computers and electricity. And, like, yeah, so that's what's different.

7:48John Jantsch:Yeah. So there's a little bit of a rising bubble of people that are anti-AI. You know, you see the marketing positioning of, you know, no AI was used in the creation of this. Do you think that is simply a trend or do you think that will grow? I think it's going to grow significantly. I think it's going to be stoked by interest groups that want it to grow. And then I think it'll naturally grow because people's lives and communities are going to be impacted in negative ways. So I always like the closest thing I can equate to try and make it tangible for people is, you know, if we go back to 1994, 1995, the Internet's like becoming a real thing in society.

8:30And at that moment, we said, you know what? There's going to be this thing called the dark web where these like horrible people do horrible things. And it's going to cause like online bullying. And like you're going to have all these downstream super negative things that happen. But we go back and say, but would we still build the Internet? Yeah, like 100 times out of 100, you would probably still build the Internet because it has changed society in a bunch of profoundly like positive ways. And I think AI is going to be the exact same thing. there's going to be absolutely negative things that happen as a result of it, whether it's building of data centers in communities that don't want them, job loss and displacement, whatever.

9:09Like those things are gonna happen. They're a byproduct of it. But if all goes well, it's also gonna transform health and create growth engines and opportunities we've never had before and solve mysteries in the universe. Like it's gonna do all these things too. So it's totally natural that there's just, there's pushback because it's starting to affect people's lives. And we, you know, wherever your role in this is, you have to be empathetic to that. Like it's, and that's my problem with a lot of like the Silicon Valley mentality is accelerate at all costs and like forget if there's risks and fears, like throw those aside.

9:45I'm not in that boat. I feel like we have to embrace the fact that not everyone loves this and it isn't all just abundance and amazing things. There's actually a bunch of things we have to deal with as a society, as a result of this.

10:00John Jantsch:And, you know, another issue that I think is, I mean, I think there were some unforeseen things that came out of other technologies, but it feels like even if you ask the smartest people in the world who are making this stuff, they don't really know where it's going to go. And I think that there's an element of that. I think people, some regulation needs to be in order to like not get too far out in front of something they can't stop. Yeah, there's growing, like, So recently, Demis Asabas posted online about the need for regulation and X presenting a framework. He's the co-founder of Google DeepMind.

10:35Anthropic has made proposals around regulation frameworks. Sam Altman has called for regulation on Capitol Hill. He's like, they all claim to want it in different forms, but regulation can be done where it actually has the negative effect on society. So there's this like very fine line that I am not the expert in by any means about how to do regulation well. There are very few people that are building the technology who don't think that there needs to be some protections and guardrails in place. That we don't have to stop and say, this is going to have a serious impact. We should be thinking more deeply about it.

11:11The challenge has been the leaders of these labs. They're so focused on just building the technology and competing with each other and competing with China and other countries.

11:19John Jantsch:Trying to make money. Yeah, they don't sit around and think about the writers who are going to lose their jobs. Like, it's just not. And they live in a bubble where it's like, they're all just technologists and engineers. And like, they're all going to have jobs for the foreseeable future because they're all growing and hiring more of those people. But they don't think about the average knowledge worker and the impact it's going to have. So they're hiring economists and philosophers and like, they're trying to now consider it. But for a long time, they were just heads down, accelerated at all costs.

11:48Yeah. Well, and I think, unfortunately, when it comes to regulation, you know, you think about the government bodies that are going to decide they need to regulate this.

11:57John Jantsch:I mean, they can't even line a swimming pool, you know, so the idea that, sorry, that was a cheap one. But the idea that they're going to actually, you know, regulate an industry like this, you know, is probably kind of frightening. Well, yeah, and they don't understand the technology and where it's going. Like the idea originally a couple of years ago was to limit it based on how much compute was needed to train a model. Well, that's laughable amounts of compute these days. And then they just find ways around it. So every time they try and find a way to regulate it, it generally is a very narrow-minded way of thinking about it that would eventually be obsolete within like a year or two.

12:32John Jantsch:You know, I've spent over 20 years watching good businesses waste money on marketing that doesn't add up. And usually the problem isn't the tactics. It's the missing foundation underneath them all. So I put the whole system in a new workbook called Seven Steps to Small Business Marketing Success. Seven steps, the right order with everything you need to build that actually compounds. You can pick it up right now for five bucks at dtm.world slash seven steps. That's dtm.world slash seven steps. So let's talk about eight pillars of business AI transformation. That's something that you have written about.

13:13John Jantsch:Hopefully you remember writing about that. I'll name them for you. Vision, strategy, data, technology, governance, literacy, people, and performance. The key thing, whether you want to check any of those boxes, is you said no company has ever passed this test yet. Where do companies break down in terms of any of those elements when it comes to transformation at an organization? Yeah, so this is a relatively new concept that I shared. It's part of a larger transformation system that I'm developing. And it's like the first piece to it because we talk to a lot of companies of all sizes, small, midsize businesses, large enterprises, and everybody's trying to figure out like, what does it actually look like?

13:51We throw out this term transformation, but like no one really has quantified how do we actually do that? And what we've seen time and time again is especially in larger enterprises, but it happens in small businesses too, just treat it as this technology problem. Like, oh, we just got to go get some ChadCBT licenses and give them to people and like, then we're going to get all these amazing benefits of AI.

14:09John Jantsch:And the CTO is in charge of it. Yeah. And they throw it into the technology pool to do it. What needs to happen and the fundamental flaw that we see is a lack of situational awareness and vision from leadership. And so my, like, if I boiled this down to one simple thing, the CEO has to drive the transformation. Like, it has to be so important to the organization that the CEO has embedded him or herself in the deep understanding of the moment, of what the technology is capable of, of the impact it's going to have on their organizational structure, their people, their products, their markets. And if the C-suite doesn't have that, then you are not going to see a complete transformation within an organization.

14:55So vision and strategy from the leadership on down is what's fundamental. What's driving most of the innovation and transformation companies so far is actually bottom up, where people are just like bringing their own devices to work or getting their own personal accounts and just like doing their own thing. And then sometimes that turns into a collective of people doing their own thing. And then maybe a department's like, oh, let's form around this and let's get a marketing AI council or something. But what often lacks is that top leadership that truly understands this needs to be one of like the three biggest priorities we are working on as an organization.

15:31John Jantsch:Well, and I think you hit on a really thing I see all the time is that they're treating it like tools, like, oh, here's a new laptop. You know, as opposed to the fact that this is probably, you probably need to rethink your entire organization. You probably need to think what it is, rethink what it is you actually do. And that might be a little bigger question, you know, about do you even have the right people? You know, do you have, you know, is the structure make any sense anymore? I mean, there's just, you know, a lot of people like you and I sit around and talk about this stuff. And I think a lot of 15 person business businesses are saying, yeah, okay, tell us.

16:05John Jantsch:I mean, it's one thing to say you need to rethink your organization. Okay. But like, what's the roadmap for that? I mean, how does somebody, you know, when you talk about those pillars, are there two or three that they ought to be addressing before they ever like sign up for a subscription? Yeah. So, I mean, literacy is the fundamental thing. So it's number six on my list, but it's actually probably number one overall because even the C-suite needs AI literacy. They need the knowledge and the understanding and the belief system around AI and its impact before they can prioritize it strategically within a business.

16:37So developing understanding of AI capabilities, the comprehension of like what it is and what it's capable of, and then the competency to use the tools in an intelligent way that like, you know, when to go in and ask chat GPT for help. And then you know what good looks like. So AI literacy is actually the foundation of all the other components. And then if you do that individually and you go through the organization and say, OK, we're going to raise the skill level of everyone, the understanding of AI and the ability to work with it, then you can move the organization forward more, not only efficiency with higher efficiency and productivity, but drive actual innovation and growth as a result of it.

17:13And then as a small business, you can start to think, wow, like for 20 people, we could be performing at the level of 50 people. I was actually having this conversation today with our director of operations who she and I used to work at my agency together. And we were laughing. I said, could you imagine if we had these tools back when we owned an agency? Like 90 % of what we did for clients, AI is capable of doing now. And so like the perfect example we gave was we used to like give monthly performance reports to clients by the 15th of the following month. So you'd wrap the month up, you'd organize the data, you'd put it into the thing, you do the analysis, you would create the PowerPoint, you'd schedule the meeting.

17:58And by the middle of the month, you were talking about what happened the previous month. We now at SmarterX, our COO runs those things in real time. So like at any moment, she has it connected to the data. She can tell the narrative of what is happening across all of our KPIs. And boom, here's the update in Zoom. Stuff that we used to spend dozens of hours creating on a 15-day lag, we now do in real time. And so when you apply that across entire businesses, all different departments, you start to realize how different we can run companies today.

18:33John Jantsch:One thing that, and I said it in my beginning kind of question, was that also trained a lot of people, right? A lot of the people that did that work learned a lot about marketing by doing that work. And they're now missing that. How do we fill that gap? I don't know. It is the focus of my MECON 2026 keynote. So the name of the keynote is The Architect, The Orchestrator, and The Apprentice. And my basic hypothesis is that we have to redefine entry-level work because the tactical things that all of us did to become experts, to know what good looks like, to have judgment and taste, and to be able to work with these amazing tools in a responsible way, we can do it because we did the data-driven repetitive work all those years and learned right from wrong and good from bad and things like that.

19:22And then we edited other people's work. And it's like, if you remove all of that work from the first three to five years of our careers, how do we get to become the experts we all became and have that domain expertise and institutional knowledge? And so I don't know the answer, but my current theory is that it looks something like an apprenticeship, that organizations will have an increased revenue per employee number as a benefit of AI. So you use AI to run a more efficient business, thereby generating more revenue per employee. But rather than putting that straight to the bottom line, you reinvest a portion of that increased revenue and profit back into developing entry-level talent through an apprenticeship program where they don't have a direct impact on revenue.

20:08They're actually an expense item for the first maybe two to three years of their career. And so that's a theory. But then you actually have to operationalize, well, okay, if that actually is a viable idea, how do we do it? How do we train them? How do we use these tools to advance their learning so they still come out after two or three years with not only the level we had after two or three years, but maybe like 2x that. So we actually accelerate their learning, their taste, their judgment, their capabilities by leveraging AI technology to train them in new ways. And I have yet to meet a single leader of any company of any size that has solved for that.

20:47John Jantsch:Yeah, that's really interesting too, because I mean, I see it every day. It's like right now, some of the entry level people can't recognize when AI is just hallucinating and saying stupid stuff and, or just off brand, you know, even. And I think a lot of that comes from, you know, the fact that you can sit around and look at something and immediately, you know, know the course correct. But that just comes from experience. And I think that's a really brilliant idea, the idea of apprentice. But again, you also mentioned expense. I think that's what's going to make it hard for people. But, you know, companies that invest like that, you know, long term, we've seen it time and time again, a win.

21:29So you have to play the long game for sure. And a lot of companies aren't going to have that benefit. Like I've always said, if you're publicly traded, venture capital backed or private equity owned, you're fighting an uphill battle to follow that kind of model, to play the long game and not just take the near term benefits of cost reduction.