In this episode
Mike Kaput, Chief Content Officer at Marketing AI Institute and its parent company SmarterX, joins Greg Kihlström to explain why the gap between individual AI adoption and organizational AI capability keeps widening. Institute research covering 2,100 respondents found that more than half of individuals are integrating AI into their workflows — or already changing how they work — while only about a quarter of organizations are scaling with a strategy behind them. Kaput walks through the three signals that separate an organization that is genuinely operationalizing AI from one that has a roadmap slide: executive-level communication, AI literacy pursued across every role rather than only technical ones, and a working plan for how agents fit the org chart. The conversation then moves to measurement, where hours saved is treated as a starting metric rather than a business case, and to talent, where the entry-level work junior marketers used to learn on is exactly the work AI absorbs first.
Key takeaways
- More than half of individuals are integrating AI into their work, but only about 25% of organizations are actually scaling with a strategy. Marketing AI Institute’s AI for Business research polled 2,100 people and found the gap sits between individual adoption and organizational adoption, not between believers and skeptics.
- If AI direction is not communicated and championed from the CEO down, be skeptical that a strategy exists at all. Kaput treats top-level communication as the first and non-negotiable maturity signal.
- AI literacy has to reach every level and function of the marketing team, not just technical roles. It should be customized to each person’s role and work, but no one is exempt.
- Maturity is a roadmap for how agents fit the org chart — hiring, staffing, business model — not a count of pilots. Nobody has that figured out, but organizations that have not started asking are not operationalizing.
- Silence about AI does not mean employees aren’t hearing about it. Kaput’s point: staff are absorbing information, misinformation and debate whether or not leadership says anything, so cohesive internal messaging is the baseline.
- A badly run AI rollout is a referendum on the company, not on the technology. Tools thrown at a team with one email and no training produce cynicism that gets misattributed to AI itself.
- Productivity is doing something 10% better; innovation is doing it 10X better. Kaput cites Marketing AI Institute founder Paul Roetzer on the distinction, and argues the point of freeing time in the first bucket is to buy room in the second.
- Time savings is the easiest first measure and a short-sighted end state. Piling more of the same work onto the hours AI returns caps out in burnout — doing the job of three or five people with a swarm of agents and no relief.
- Entry-level jobs may have to be rebuilt as apprenticeships. If AI does the tactical work marketers used to cut their teeth on, judgment has to be taught deliberately — otherwise no one can tell whether the AI output is any good.
Chapters
- 0:00 — Cold open: can anyone in your company say what the AI actually does?
- 1:00 — The question behind “we have an AI strategy,” and who is accountable when it goes wrong
- 3:10 — Mike Kaput, Marketing AI Institute and SmarterX: making AI actionable for non-technical professionals since 2016
- 5:34 — What “AI strategy” actually consists of when a marketing leader says they have one
- 6:05 — The research: 2,100 respondents, half integrating AI individually, ~25% of organizations scaling with strategy
- 7:16 — Signs the market is maturing: token budgets, access permissions, how to deploy agents
- 9:07 — Three maturity signals: CEO championship, org-wide AI literacy, and moving past siloed pilots
- 12:48 — The staffing question: fewer job losses so far than people doing the work of three
- 14:13 — Where leaders should start: communicate first, then take something off people’s plates
- 17:13 — “They’re talking about you anyway”: the bank that avoided social media
- 18:16 — When the rollout is the problem, not the technology
- 19:44 — Measurement beyond efficiency: what reporting should actually reinforce
- 21:11 — Productivity vs. innovation: 10% better against 10X better
- 22:50 — If AI does the tactical work, how do juniors learn marketing fundamentals?
- 23:49 — The Architect, the Orchestrator and the Apprentice: rethinking talent development
- 25:29 — Inside MAICON 2026: two tracks, Karen Hao, Andrew Yang, Cleveland, October 13–15
- 27:20 — Staying agile: the forcing function, and why five minutes of hands-on beats another explainer
Why “AI strategy” describes very different things at different companies
Kaput’s starting observation is that the phrase is doing a lot of work. Some leaders have a genuinely roadmapped view of the next one to three years — use cases, technology, pilot projects, impact on talent, business model, leadership — and he says it is still rare to see anyone nail all of it. Others have a set of tools and a stated intention. What the Institute’s research surfaces underneath the phrase is a consistent split: individual adoption is running well ahead of organizational scaling, year after year, which suggests something is being lost in translation between the person using the tool and the company trying to build on it.
The three signals that an organization has moved past the slide
Asked what distinguishes real operationalization, Kaput names three things in order. First, has the direction been communicated, embraced and championed from the very top — regular communication and vision from the CEO and leadership about where the organization is going despite the unknowns. Without that, he is deeply skeptical of any claimed strategy. Second, is AI literacy being pursued broadly, customized to role and seniority, rather than confined to technical functions and IT. Third, has the organization gone beyond solo use cases and siloed pilots into the day-to-day work of every department — and started building a roadmap for how agents affect the org chart, hiring and talent needs. He is explicit that nobody has the third one figured out; the signal is whether the questions are being asked.
Why hours saved is the beginning of a business case, not the case itself
Kaput does not dismiss productivity and time savings — they are the easiest thing to measure and, at the individual level, showing that lift is real business value. His objection is to treating the recovered time as capacity for more of the same work. That path caps out predictably: a marketer with a swarm of agents who is constantly working and burnt out. The alternative he describes is deliberate reinvestment of the freed time into more complex, more strategic, higher-impact work — including work AI does not accelerate at all. In his own business, the gain came from doing necessary-but-not-highest-value work faster, then spending the recovered hours on problems that needed a person sitting down and thinking.
The talent problem nobody has solved yet
Greg raises the structural version of the question: if AI absorbs the tactical marketing work that teaches people how marketing works, at what point does knowledge of AI outpace knowledge of marketing? Kaput’s answer is that there is no good answer yet, and points to Paul Roetzer’s MAICON keynote framing — the Architect, the Orchestrator and the Apprentice — as an initial attempt at a framework. His own read: entry-level jobs may need to be treated as apprenticeships, with experienced practitioners deliberately teaching how they think and develop judgment, rather than being written off because AI can do the tasks. Otherwise the person reviewing AI output has no basis for deciding whether it is good, useful or strategic. He frames it as a succession-planning problem for organizations, which may require new roles that are less valuable in the short term and necessary in the long one.
What a marketing leader should do about employees who are already using AI
The failure mode Kaput describes most vividly is the company that says nothing. Employees are hearing about AI regardless — through news, debate, criticism and misinformation — so the absence of internal messaging is itself a message. Greg offers the parallel of a bank a decade ago that stayed off social media so people would not say bad things about it, and had to be told they were being discussed anyway. Kaput’s recommendation for leaders is sequenced: get everyone on the same page that the organization is moving forward with AI and what that means for each role, with empathy for how people feel about it, then start small by taking work off people’s plates that they do not want to be doing.
FAQ
How many organizations actually have an AI strategy they are scaling with? According to Marketing AI Institute research covering 2,100 respondents, more than half of individuals are integrating AI into their workflows or transforming how they work, but only about 25% of organizations are genuinely scaling with a strategy behind it.
What separates an AI pilot from an AI capability? Kaput looks for three things: AI direction communicated and championed from the CEO down, AI literacy pursued across every role and seniority rather than only technical ones, and integration into the day-to-day work of every department with a roadmap for how agents affect the org chart, hiring and staffing.
Is time saved a good way to measure AI’s impact in marketing? It is the easiest initial measure and a legitimate signal of individual value, but Kaput argues it fails as an end state — if the recovered time is refilled with more of the same work, the organization caps out in burnout instead of capability.
What is the difference between productivity and innovation with AI? Kaput cites Paul Roetzer’s formulation: productivity asks how to do something 10% better, innovation asks how to do it 10X better. Freeing up time in the productivity bucket is worthwhile mainly because it creates room for the second.
How should companies develop junior marketers when AI does entry-level work? Kaput suggests treating entry-level roles as apprenticeships — deliberately teaching how experienced practitioners think and develop judgment — because someone who skipped that stage has no way to evaluate whether AI output is actually good or strategic.
What should a leader do first if their AI rollout has gone badly? Kaput’s framing is that a bad rollout is a referendum on how the company deployed AI, not on the technology. The correction starts with cohesive communication about where the organization is going and what it means for each role, followed by small, concrete wins rather than another wave of tools.
About Mike Kaput
Mike Kaput is a recognized expert on marketing, content, and artificial intelligence. He is also a writer, speaker, and author. Mike currently serves as Chief Content Officer at Marketing AI Institute, where he uses marketing, content, and AI to grow traffic, leads, and revenue. Mike previously served in a marketing leadership role at HubSpot’s first-ever partner agency.
Mike Kaput on LinkedIn: https://www.linkedin.com/in/mikekaput/
Resources
Marketing AI Institute: www.marketingaiinstitute.com
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Transcript
[00:01:00] Greg Kihlström: [gentle music] Hi, I’m Greg Kihlström, host of the Agile Brand, and here’s a question for you. Your company has an AI strategy, but can anyone in it tell you what the AI actually does and who’s accountable when it does it badly? Agility isn’t the number of AI pilots you can launch, it’s whether the ones you keep still add up to one company acting with one logic. Today we’re talking about what happens after the experiments when marketing organizations have to turn scattered AI projects into something the business can actually run on. We’re gonna talk about why AI as a single label hides very different decisions and what leaders should be asking instead, what separates a pilot that demos well from a capability that enterprise can depend on, and how marketing operations, team structure, and measurement have to change to keep the output coherent as it scales. To help me discuss this topic, I’d like to welcome Mike Kaput, Chief Content Officer at Marketing AI Institute. Mike, welcome to the show.
[00:02:41] Mike Kaput: Greg, thanks for having me. Great to be here.
[00:02:43] Greg Kihlström: Yeah, looking forward to talking through this. Certainly, certainly lots to discuss, and of course we’ve got MAICON coming up, a- any day now. This, this show’s gonna go, go live in September, so, it’s, it’s, it’s coming up soon, right? [laughs] So look- looking forward to it.
[00:02:58] Mike Kaput: It really is. [laughs]
[00:03:00] Greg Kihlström: [laughs] Nice. So for those that are a little less familiar with, with you and Marketing AI Institute, as well as MAICON, do you mind just giving a little intro on, on yourself and, and, and all that?
[00:03:10] Mike Kaput: Yeah, of course. So my name’s Mike Kaput. Like you said, I’m the Chief Content Officer at Marketing AI Institute and our parent company, SmarterX. So Marketing AI Institute basically started way back in 2016. our founder, Paul Roetzer, got it started, and I was one of the early people contributing to that project. And basically we started it off as a way to make AI approachable and actionable for marketers and business leaders. obviously a lot has changed since 2016. Marketing AI Institute has been here from the very beginning or before the beginning of the whole generative AI wave, and over the last several years it’s actually become one of the core brands of SmarterX, which is kind of the overall AI transformation company that Paul owns,
[00:03:55] Mike Kaput: that I work for, and we help every type of company, every profession, not just marketers, though marketers are a huge part of our audience, adopt AI. So our focus is definitely on marketers and business leaders, especially non-technical professionals who are trying to understand and apply AI, and we teach them how to do that through a variety of online education. We have a whole online learning platform called AI Academy, research, media, events, like you mentioned, MAICON, the Marketing AI Conference, which is happening, very soon in Cleveland, our home base, from October 13th to the 15th, and through our own podcast, The Artificial Intelligence Show. So long story short, I spend all day every day basically testing, researching, using, deploying AI
[00:04:40] Mike Kaput: tools across marketing, content, and a bunch of other business applications for our own business, and then advise and teach hundreds if not thousands of other businesses and learners how to do the same thing in a totally approachable and accessible way.
[00:04:56] Greg Kihlström: Yeah. Yeah, love it. So yeah, let’s, that gives you a, a pretty good purview over definitely what we’re gonna talk about today-
[00:05:03] Mike Kaput: [laughs] Yeah
[00:05:04] Greg Kihlström: … but over a, a lot of things that are very top of mind for, for, you know, at least everyone I talk with today. So, you know, AI s- AI strategy, I’ll just put it in the, in the air quotes here, has certainly changed a lot over, I would imagine over the last, I mean, certainly since 2016, but even, even over the last two or three years. I think a lot of the, the organizations that I see doing it well are, um… I mean, I, I wrote a book called, AI Isn’t a Goal or a Strategy, [laughs] but-
[00:05:34] Mike Kaput: [laughs]
[00:05:34] Greg Kihlström: … an AI strategy is a little different than that. So, you know, let’s, let’s start with what you’re actually seeing. When a marketing leader tells you that they have an AI strategy, you know, what, what are you… What does that usually consist of today, and maybe, maybe draw a contrast with what it might have been at the, let’s say, you know, ChatGPT just launched, you know. How, how has it kind of evolved over the last few years?
[00:05:58] Mike Kaput: Yeah, well, I’ll start by saying it’d be nicer if more marketing leaders came to me saying, “I have an AI strategy” [chuckles]
[00:06:05] Greg Kihlström: Fair point
[00:06:06] Mike Kaput: … because I can’t say that it’s as prevalent as I’d like it to be. I think some people think they have a strategy and perhaps don’t or, don’t have one at all, that there are plenty of firms, like you mentioned, moving forward quickly. But I think the, the real key here is that strategy or not, there’s this big gap that we see. So we did a bunch of r- research this year on AI, our AI, for Business report that we did this year, where we polled 2,100 people, a lot of them in marketing. We do marketing-specific research and data as well, and we found that more than half of individuals are integrating AI into their workflows a- or even transforming how they work, but only about 25% of organizations are really actually scaling with a strategy.
[00:06:51] Greg Kihlström: Mm.
[00:06:51] Mike Kaput: So there’s this individual versus organizational gap. So to the point of an AI strategy, I think a lot of people that think they have one, they might have this really well roadmapped on paper what the next one, two, three years look like, in terms of AI use cases, technology, pilot projects, impact on talent, business model leadership. I would say that’s still very rare to see someone nail all of that.
[00:07:15] Greg Kihlström: Yeah. [chuckles] Yeah.
[00:07:16] Mike Kaput: but even if they are, the simple fact remains there’s this reported, at least, that we see year after year, individual versus organizational gap, so I think something is getting lost in translation here. But I, I will say the market is maturing quite a bit. There’s plenty more people that have AI strategies and roadmaps. There’s a lot more talk and a lot more action around not just which tools to adopt, but how to adop- adopt these things effectively, not just like pilot projects necessarily or one-off use cases, but how do we actually integrate AI at the organizational level for real transformation? And, you know, a big thing these days is things like token budgets, access permissions. How do we deploy agents? All of that is very different and more sophisticated than what we’ve seen in the last
[00:08:01] Mike Kaput: few years. So there’s really positive motion towards asking the right questions, but as any marketer listening to this knows, it’s also really hard to predict a year or two, three years in advance exactly how this technology is going to impact your organization. So it’s, it’s… I don’t envy having the job of building AI strategies. [chuckles]
[00:08:20] Greg Kihlström: Yeah, yeah. I mean, I find myself saying things like, you know, in the early days or whatever, and that refers to like 12 months ago of, of something.
[00:08:29] Mike Kaput: [chuckles]
[00:08:29] Greg Kihlström: So, you know, I, I don’t remember doing… You know, it, it, there was at least a longer time horizon for some of the [chuckles] some, some other things. So, you know, and, and some of the things that you mentioned, like, like token budgets and, and some of those other things, to me, to me, that sounds like, you know, organizations that are at least beginning to operationalize this stuff. And so, you know, are, are, what, beyond some of those things, like, what are you seeing? What are the signs that a, that an organization is really beyond slide where, you know, the, the, that kind of scenario that they’re truly operationalizing things, or at least moving in the right direction? ‘Cause to your point, it’s gonna be different in six months, but-
[00:09:07] Mike Kaput: I would say there’s a few broad things I would look for to start. Well, one, and first and foremost, is has this been communicated, embraced, and championed from the very top by your CEO-
[00:09:19] Greg Kihlström: Mm. Yep
[00:09:19] Mike Kaput: … by all your leadership? Are we getting regular communication, vision, direction on exactly where the organization is going or trying to go, despite the unknowns with AI? So that’s number one. If that’s not there, I’m deeply skeptical of [chuckles] any strategy that claims to be in place, I would say. and it’s not a knock on people. People are trying to do the best they can with the tools they have. It’s just this has to come from the top. I would say number two, and we’re biased in this respect, but I think it is critical, is I need to have some sense that AI literacy is being pursued, not just in marketing, but across the organization. Obviously, a marketing AI strategy, at the very least, I wanna see the whole marketing team, no matter what level, seniority, function, everyone needs to be pursuing some form of AI literacy, customized,
[00:10:04] Mike Kaput: personalized to their role, their job, their work, but to varying degrees, of course. Um.
[00:10:09] Greg Kihlström: Yeah.
[00:10:10] Mike Kaput: So I need to see some level of extensive AI literacy being pursued broadly, not just within the more technical roles, IT, et cetera. and then third, I would say I would wanna see more of, okay, how have we gone beyond those initial u- s- solo use cases, siloed pilots, et cetera? That’s all really good to start doing, but if we’re not deeply integrating this technology into the day-to-day work of everybody and every department, and we’re not starting to at least think about the fact that if you do that, this fundamentally changes business models, this changes staffing, this changes hiring… I’m not saying you have to have all that figured out. Nobody has that all figured out. But if you’re not starting to have a roadmap of how are agents going to fit into the org chart, how are agents going to affect our hiring, our
[00:10:55] Mike Kaput: firing, our, our talent needs-
[00:10:57] Greg Kihlström: Yeah
[00:10:57] Mike Kaput: …how we communicate this stuff, then that would be levels of maturity that would say to me, “Okay, you’re really going down w- the road that we see this going down regardless.”
[00:12:48] Greg Kihlström: I wanna talk a little bit about the, the staffing part of that, ’cause I, I do think that’s a, that’s a critical piece. And I’ll just give the caveat that, you know, I, I don’t wanna discount people being concerned about, you know, losing their jobs and, and things like that. So, what I’m about to say, I, I’m consider myself an optimist when it comes to this stuff. So what I see, to be honest, more than people losing their jobs at this point, is I see people working, like, almost twice as hard. And there’s some survey, I just interviewed somebody saying, you know, pe- most people are … feel like they’re doing the job of three different people. And so I know that there will be some, you know, some job loss or at least shifts and, and things like that. But that said, I think to me,
[00:13:33] Greg Kihlström: from my standpoint, like, the true adoption of AI and making this work is, is touching on what you just said, which is making it work for the people that are, you know, w- jobs are gonna shift, roles are gonna shift, but it’s like, how does a, how does a leader, knowing all the things that we said, which is we can’t know the future, you know, to any large degree, but we’ve gotta start making moves in the right direction, like, what roles or parts of the business should leaders focus on shifting fir- Like, is this a marketing operations thing? Is this a tactical execution? I- Where should leaders’ headspace be, I guess?
[00:14:13] Mike Kaput: That’s a really good question. I think it’s gonna somewhat depend on the organization.
[00:14:17] Greg Kihlström: Sure.
[00:14:17] Mike Kaput: But, you know, first we start, it’s kind of why I mentioned go back to, like, that communication from the top. I mean, step one is, like, whether it’s the marketing leader within the marketing team or overall the CEO, et cetera, like, we need to get everyone on the same page that regardless of your feelings around AI, which we can talk about, and there should be communication and empathy around, we are using it. We are moving forward with it, and here’s what that means for you and your role. It does not mean, hopefully, I mean, we would encourage and teach people, like, should not mean we’re sitting here figuring out who stays and who goes. It’s saying that we are moving as an organization to become AI forward, and here’s exactly what that means. Again, it’s gonna look a different for every company. But communicate that. That has to be step one because there’s so many… I like to say to people, “If you’re not talking about AI, that doesn’t mean your staff, your employees, your teams are not hearing about AI.” [laughs] I mean, this is such a hot button issue, and there’s a lot of information, misinformation, commentary, critiques, et cetera out there, a lot of debate. So people are hearing stuff whether you say it or not. So I think having consistent, cohesive messaging around, “Okay, we are AI forward. Here’s where we’re going,” then from there it’s like, okay, let’s, you know, let’s start small. Let’s figure out how AI can make you happier and more productive at your job. Like, I realize that it doesn’t always work that way. We all can sometimes feel like, yes, we’re doing the job of three or five people. I’d hope we don’t go that way en masse, but it can happen. But I think you start small and you say, “Okay, let’s, let’s just start with taking some things off your plate that you don’t wanna be doing on nights and weekends, or that you hate doing at work when you’re
[00:15:58] Mike Kaput: in the office.” I think small is good, get people bought in. The bigger picture organizational change and the talent changes, I just think that takes time, and I’ve heard plenty of really positive stories at least of people that you would assume on paper are the last people to be interested in AI or AI- embrace AI, and then they’re leading changes-
[00:16:19] Greg Kihlström: Mm.
[00:16:19] Mike Kaput: …12 months after, you know literacy and adoption is rolled out effectively in a company. So it can, it can have a very positive effect too. But yeah, as you get into sort of how it’s actually changing roles and talent, there is going to be real issues where some people just are not on board or refuse to adapt or can’t adapt, frankly, to some of the demands that AI might make on certain roles. That’s not, like, across the board, but it’s gonna be messy.
[00:16:48] Greg Kihlström: Yeah. But I, but I think to your point, like, pretending that it doesn’t exist or trying to ignore it isn’t, you know, it’s, I’m, for some reason I’m just, I’m reminded, you know, this was, like, over 10 years ago or so, I was, I was working with a financial services client, like a bank, and talking about social media, and they were like, “Well, you know, we’re not on social media because we don’t want people talking bad about us.”
[00:17:13] Greg Kihlström: And I had to be the one in the meeting to tell the president of this bank, “You know they’re talking about you anyway, [laughs] right?” So, you know, it, I’m just reminded of that. A little bit different, but still, your employees are using AI. Let’s just face it. You know-
[00:17:27] Greg Kihlström: …if you, enable them and train them, you know, to, and, and use some of the great training tools and, and enablement tools out there to do that, you’re gonna get some good results. And, and, you know, to what you were saying, you might get some people that you’d never expect in a million years being leaders and having whole new job opportunities open to them, whether it’s at your company or not. So, you know, there’s, again, an optimistic view, but not an unrealistic view o- of, of this. So I think, you know, I, I think that’s, it’s something that, for those still sitting out there just trying to, trying to say, “Okay, well, you know, the, maybe not us, but every- everybody else is affected by AI but not us,”
[00:18:13] Greg Kihlström: it’s, I, I think they, they need to kinda wake up to this, right?
[00:18:16] Mike Kaput: And I, I think, look, too, it’s, I wanna ver- be very clear, like I very much empathize and understand if people are like listening to this and being like, “Oh my God, like we’re rolling out AI, it’s a disaster,” or, “I hate how we’re doing it.” Like I get that. A lot of places are not doing it [chuckles] the right way. Like there’s horror stories out there where companies or executives are like, “Hey, I’m gonna throw a bunch of tools at you,” send you one email being like, “We’re all AI now,” and not tell you anything about what that means, not give you any education around it. You have no idea or time in addition to your own job to figure out the tools. You’re like, “Oh, okay, it like rewrites an email. Great.” Like-
[00:18:52] Greg Kihlström: Right
[00:18:52] Mike Kaput: …all I would say to you is that unfortunately if that resonates or you’re hearing that or you’re like worried, you’re like, “Oh, it’s typical corporate BS,” like this, this thing again, like I get it, and that’s unfortunately not, I would say, a referendum on all of AI. That is a referendum on how your company is rolling it out, and it would behoove you in your career and in your own personal life to d- to maybe take a step back and say, “Okay, there’s a better way to do this.” This technology, I can tell you, is real. It is creating real impact, and obviously I’m biased, but like I have dozens of hundreds of examples of this if it’s approached in the right way. So don’t get soured on the fact that your company is doing it wrong. I get that’s hard to deal with, but you… It would benefit
[00:19:37] Mike Kaput: you to maybe in your personal life take a step back and start playing around with certain models and tools yourself and start k- forming your own opinion as well.
[00:19:44] Greg Kihlström: I mean, what, what role does measurement have in this as well? You know, I think there’s, there’s a lot of focus on efficiency gains and, and things, and I mean, I see it in my own work that I, I’m, I’m more efficient by using some tools that either I’ve vibe coded or, adopted. But that’s not the whole picture, right? You know-
[00:20:05] Greg Kihlström: …so what, what, how can like reporting on effect- on, on, effectiveness or, or, or things like that actually help maybe, employees feel better about adopting and, and, and kind of reinforce some of this, some of the positive growth parts of this?
[00:20:25] Mike Kaput: I think we can’t get away from productivity and time-
[00:20:29] Greg Kihlström: Sure
[00:20:29] Mike Kaput: …savings as an initial measure. It’s just the easiest thing to do. But I think like it is better to look at this, if you can, as less like, “Oh, I’m gonna be more productive or save more time, and they’re… so I can just pile on more of the same work.” Like that’s a-
[00:20:44] Greg Kihlström: Yeah
[00:20:44] Mike Kaput: …very short-sighted opinion in my perspective. I realize that’s how sometimes this goes. I don’t think it’s the best way to do it. You’re still gonna run into the same problem again, which is at some point you cap out where you say, “Wow, I’m really burnt out because I’m doing the job of three, five, 10 people, or I have a swarm of agents helping me do a bunch of stuff, but I’m constantly working.” Like that’s not to me, like I don’t just wanna spin the wheel faster. I wanna like throw the wheel out entirely-
[00:21:11] Greg Kihlström: Yeah
[00:21:11] Mike Kaput: …reinvent it. Like, so I would say that productivity efficiency lift is at, can actually be at an individual level for a marketer beneficial if you can start showing that. That’s real business value being created. That’s impressive. It’s helpful to you. I think what you do with that time, where, where you invest it and reinvest it is actually really important. I think we should all be trying to move higher up the value chain in terms of more complex, more strategic, more higher impact work. Maybe that takes more time and you can’t do as much with AI, that we see this a lot in our business where a lot… I even- I wouldn’t say we’ve automated the lower level work, but we have been able to be massively more productive in things that still matter to our business but are probably not the best and highest use of what we should all be doing
[00:21:56] Mike Kaput: in an ideal world. And as a result of being able to do those things faster, better, cheaper, or do more of those things in the same time, we’re then able to allocate more time and resources towards like maybe it is just me sitting down for an hour or two and actually just physically handwriting out a solution to a problem [chuckles] we need to solve for our business. Like it doesn’t always have to be like go use AI to do more stuff. So I think as long as we think of it as two sides of a coin, there’s productivity, the obvious thing, then there’s innovation, right? Which is a lot harder. Like, our founder, Paul Roetzer, is like fond of saying, I love this quite a bit, “Productivity is saying how can we do this 10% better? How can we get 10% more gains here? Innovation is how do we do this 10X better?” And I think the more you can get in that second bucket by freeing up time in the first bucket, the better off you’re gonna be long-term, both a- as an individual and as an organization as much as you can.
[00:22:50] Greg Kihlström: Yeah. Yeah. Well, and then, you know, with all, with all the education about using AI effectively, you know, one, one concern might be, okay, now we’ve got a bunch of people, let’s say, you know, straight out of college that used to do the tactical marketing stuff that teaches you kind of how marketing works and, and things like that, but now they’re, they’re kinda ins- they’re instantly jumping up a level. Like how do the fundamentals of marketing get learned while you’re understanding the fundamentals of, you know, good AI adoption and all the governance and, and all those th- You know, it’s like ’cause leaders have, have to balance… Like right now I feel like we’re in a great spot because we’ve got a lot of people that know a ton of, you know, classically
[00:23:35] Greg Kihlström: trained marketing stuff.
[00:23:37] Greg Kihlström: It’s like at what point does the, knowledge of AI out- outpace the knowledge of marketing?
[00:23:46] Mike Kaput: That’s an excellent question. I don’t think there’s a good answer to it yet.
[00:23:49] Greg Kihlström: Yeah. Yeah.
[00:23:49] Mike Kaput: And you know, that I honestly, [chuckles] this is a shameless MAICON plug because it’s, our founder and CEO Paul’s, keynote is called The Architector- The Architect, The Orchestrator, and The Apprentice, and it’s basically this idea of like we need a new framework for understanding how AI is going to transform talent development in marketing. Because to your point, if I have AI that can do all the stuff that I cut my teeth on, lucky enough to be, you know, I… It’s crazy to say I’m lucky enough to almost be turning 40, right? So I’m like, uh-
[00:24:19] Greg Kihlström: [chuckles]
[00:24:20] Mike Kaput: …I have like decades of, at least a decade and a half of experience cutting my teeth in the agency world, in the marketing world, in the business writing world where I learned how to do all this stuff and acquire taste and judgment and- Understand complex real world problems that I now bring that to supercharging myself with AI. But if you skip that step, how, how do I tell if the AI output is actually good, useful, strategic, et cetera? I think it’s a huge problem. That’s what Paul’s keynote’s all about, is we need a new system to figure out… I, I, I’m not sure we have all the answers. I think he’s kind of floating an initial perspective on this, but it’s this idea that we’re gonna really have to start rethinking… It’s almost like you’re going to start thinking of entry-level jobs as apprenticeships. We need to start teaching you exactly how the, the more experienced humans
[00:25:10] Mike Kaput: think and develop judgment and, a- and, and intentionally do that instead of saying, “Oh, the entry level jobs are gone because AI can do them.” We might have to come up with new roles that are longer term and less short term valuable in order to have a, for lack of a better word, succession plans at these organizations, right?
[00:25:29] Greg Kihlström: Yeah. Yeah. Love it. Well, yeah, no, looking forward to that. And speaking of MAICON, again, com- coming up soon, what else, you know, as, as you’re wrapping up planning and, and getting ready to, to, to go live with the event, you know, what, what else can we expect?
[00:25:47] Mike Kaput: So we have some awesome speakers planned. I mean, we’ve got, Karen Hao, a expert AI journalist who just wrote a book, Empire of AI, on OpenAI. She’ll be on the main stage. Andrew Yang, former presidential candidate who is much more back in the news these days as AI. He, he was the first one to really run on kind of universal basic income and automation being a threat to jobs. Be very interested to see what he has to say. Things have really, come forward quite a bit since he was in the political mix. I think he’s more relevant today than ever. So we’ve got all these great speakers, but really too, I think the biggest thing is, like, we’ve really restructured this event, because the conversation has moved much more from, like, what is AI, how do I wrap my head around it, to, like, how do you operationalize, scale, govern it, prove business value? Like, everyone’s in this. We don’t have to convince anyone this matters anymore.
[00:26:37] Greg Kihlström: Yeah.
[00:26:38] Mike Kaput: So we’ve actually restructured the co- the conference to have two big tracks, which is applied AI, focusing on tactics, workflows, and use cases, and strategic AI, focused on strategy, governance, leadership, decision-making, et cetera. So we’re gonna bring thousands of people together. You can dabble in either of these tracks. You don’t have to pick just one. So there’s tons of content for every level, every learner, every, uh… Frankly, it’s not just marketing. Like, every function can benefit from a lot of these conversations and connections. So if you’re interested, feel free to reach out to us at smarterx.ai. MAICON, m-a-i-c-o-n.ai is the event page itself. You can check out the agenda. Find me on LinkedIn. Just ping me if you have any questions about anything. We’d love to see you.
[00:27:20] Greg Kihlström: Yeah. Love it. Love it. And, last question for you as we wrap up here, what do you do to stay agile in your role, and how do you find a way to do it consistently?
[00:27:29] Mike Kaput: Oh, my gosh. Well, thankfully, I’m paid to do it consistently, otherwise I think I would struggle. so honestly, co-hosting our podcast is the easy but true answer because it is a forcing function. Like, I have to learn this stuff every week to be able to jump on and talk about it with our CEO for 90 minutes. so I’m lucky in the sense that even though that’s a heavy lift, it does force me to stay on top of it. But outside of that, like, I couldn’t, advocate more for, like, if you’re curious about something, if you are like, “I’m not sure how that works,” like, literally just jump into an AI tool and first ask, but second, and much better, just do the thing. Go be like, “Hey, I, I don’t know what a GPT is.” Okay, go click on GPT in ChatGPT and start messing around. Like, I realize we don’t all have unlimited time, but in five minutes of getting your hands dirty, you’ll learn more than if, like, “Let me go listen to a podcast on all about GPTs,” which are great, but, like, just go use it.
