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Greg Kilstrom
Your brand may be staying on top of current trends, but are you agile enough to stay relevant, resilient and successful as customers, competition and the world continues to change at a breakneck pace? I'm thrilled to share the newly revised version of my first book, the Agile Brand. I'm calling it the Agile Brand Revisited. It's been updated to reflect our continually changing world and it provides seven principles that form the backbone of an agile brand, offering detailed insights and actionable steps for incorporating them into your business strategy. This is the book that started it all and I'm excited to share it with you. It's now available in print and digital formats and available everywhere. Learn more by going to the Agile Brand guide website at www.agilebrandguide.com.
Greg Shove
The Agile Brand.
Greg Kilstrom
Welcome to season seven of the Agile Brand where we discuss the trend, trends and topics marketing leaders need to know. Stay curious, stay agile and join the top enterprise brands and Martech platforms as we explore marketing technology, AI, E commerce, and whatever's next for the Omnichannel customer experience. Together we'll discover what it takes to create an agile brand built for today and tomorrow and built for customers, employees and continued business growth. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, AI and marketing operations. The Agile Brand Podcast is brought to you by Tech Systems, an industry leader in full stack technology services, talent services and real world application. For more information, go to teksystems.com to make sure you always get the latest episodes. Please hit subscribe on the app you listen to podcasts on and leave us a rating so others can find us as well. Now onto the show. AI is no longer just a tool, it's reshaping business strategy, workforce morale and even personal productivity. But are executives truly prepared to treat AI as a strategic thought partner, or are they still viewing it as just another tech trend? Joining us today is Greg Shove, CEO of Section, an AI company on a mission to train the next generation of AI leaders with the goal of educating.
Greg Shove
100,000 students in AI in 2025 and.
Greg Kilstrom
1 million by the end of next year. Greg is here to share his insights on AI strategy, workforce impact, and what businesses of all sizes need to know.
Greg Shove
About integrating AI effectively.
Greg Kilstrom
Greg is a seven time founder and CEO and has hired and managed lots of CMOs in his B2B and B2C companies with small marketing budgets and millions of dollars of marketing spend. Greg, welcome to the show.
Greg Shove
Great.
Great to be here. Thanks for inviting me.
Greg Kilstrom
Yeah, of course.
Greg Shove
So I know I mentioned a Little bit about your background, but why don't.
Greg Kilstrom
You start by telling us a little.
Greg Shove
Bit more about your background and role at Section.
Sure. Well, first of all, seven time founder and have worked with marketers my whole life, either in the B2B or B2C space, sometimes with limited budgets, meaning I wasn't able to raise a lot of money for the idea for the company and sometimes with a lot of budget because we were able to raise a lot of money. Section was a company where we raised a lot of money, frankly, back in the moment where it was easy to raise Money, which was 2020 and 2021. And at the time we were funding an online executive education business school. That was the initial mission of Section. It was founded by a guy named Scott Galloway. You might know him, some sometimes referred to as Prof. G. He's a co host to Pivot. So Scott started the company. I'm a longtime friend of Scott's. I came in to run it. We launched our first online business class the week of the US lockdown of the coronavirus pandemic. And so sales went from zero to $10 million overnight. I thought I was a genius because I thought it was because of our amazing product which was a two week online sprint where we had live lectures, a slack community, homework for students in a single cohort where the students kind of started and ended on the same day. So that product was great. And we had high nps, high completion rates, high engagement rates. Demand plummeted when the pandemic ended. And that's when I realized, oh, I was misinterpreting the signal. That incredible growth that we had was fueled by a lot of capital that we were spending. That was a mistake. But it was really fueled not just by our, not by our great product, but by the demand because people were sitting at home with nothing to do and frankly worried about their jobs. So they were upskilling. So I had the right size, the business right size, the team. That was painful. Reduced the marketing budget almost to zero. And there were months where we'd been spending, you know, probably half a million dollars in marketing in terms of customer acquisition, marketing, and sort of stabilized the company. Then February 1, 2023 came along, now about two years ago, where I played with ChatGPT Plus. And that's when I had kind of one of those aha moments, both for myself and for Section, the company. And the aha moment was this will be the new accelerant. Scott and I had always thought that business education, strategy education, helping people in their mid career Kind of think like a leader. What was an accelerant or is an accelerant? And it is. That's why people go back to business school. That's why people go back to executive, to get executive MBAs or, you know, or do sort of one week at Stanford Business School and pay 10 grand for that. You know, that learning's meaningful. But then we realized in that moment that the new accelerant, accelerant would be AI and that knowledge workers, leaders, managers, high, high ambitious ICs could use AI to their advantage because it would take a while for the rest of the knowledge workforce to figure out, figure it out. It's not easy to work with AI as you know, it's not easy to play around with chat, chat GPT and get good outcomes from it. So that's when I thought, okay, this is the new accelerant. And I wanted to be the company that enabled as many people as fast as possible to get into the AI class. So we pivoted pretty much on day one. I could give you the whole playbook and how to pivot because I've done it too many times. But, you know, that was a good pivot for us. You know, we caught that moment, I think, pretty well in terms of understanding what people needed, building product, meaning our curriculum, as fast as we could. I had to teach the first AI class, Greg, because there was no one to teach AI, you know, two years ago, particularly in the context of business. Right. A lot of classes and stuff going on and teach engineers how to use AI software engineers, but not really much for marketers or for leaders or for people in finance or hr. So that's what we did at Section. We've trained probably 20,000 people last 18 months on AI. And our goal this year is to train 100,000 people and a million next year on how to use AI in their jobs so they can get that acceleration.
Greg Kilstrom
Great.
Greg Shove
Well, yeah, let's dive in here. We're going to talk about a few things. Definitely you're the right person to talk with about this topic here, but I want to talk about a lot of the conversation around AI is. It's an automation tool. It can speed things up. It's an efficiency play. And that's not untrue. But executives should also be thinking of AI as a strategic thought partner. And you know, how. How can business leaders kind of move beyond. Again, it helps kind of automate a few things and it accelerates. Again, not untrue, but how can, how should executives shift their mindset to use AI? More effectively.
Yeah, sure. I think, I think my second aha moment was asking AI to play the role of a board member. So we've now done this for six straight quarters. We just did it actually last week because we had a board meeting. So when I first did this, and we do do it kind of the same way today, I just took the same board deck that I send to our board members. And by the way, I have a great board, probably the best board I've ever had in terms of all my startups in terms of their experience both as investors and operators. So you know, I get good advice from, from this board but so I took the same board meeting pre read that I give the humans and I gave it to AI six quarters ago, ChatGPT, co pilot, Gemini and so on and said basically, you know, act as a board member, act as a conservative board member, act as an aggressive board member, act as a cfo, you know, minded board member. And so we did that before the board meeting to get ready for the board meeting and we've done it every board meeting since. And I can't imagine any entrepreneur going into a board meeting and not doing that. I can't imagine any CMO going into an executive meeting or you with a boss or with a board or investors and not doing this, which is role playing with AI as a thought partner. And we grade Greg, the AI as IT as A in terms of its performance when compared to the human board. We don't record board meetings for kind of governance and legal reasons. But I do have my chief of staff sit in the board meeting and take really great notes. Board meetings are typically an hour and a half to two hours. We do them every quarter and so we have a pretty faithful kind of record of what the humans tell us and their, you know, their advice and insights. And then we compare that to the AI and AI scores really well over the last 18 months AI has scored between 85% and 93% of the humans. So we compare the output of the humans and we compare that to output the AI, our favorite AI and the highest performing AI every quarter has been clawed from anthropic. Now GPT is close behind. It not used to be, but now it seems to have improved, you know, as a thought partner. So those two AIs are far and above the best for this kind of work we think so they're kind of my strategic SWAT team when I think about my AI would be Claude and GPT and you know, Copilot is decent Copilot, Microsoft Copilot has, as you know, GPT inside and then and Gemini is a long way behind. So that product in my opinion is not ready for knowledge work or for serious knowledge work at least as relates to thought partner kind of work. So again, that was an eye opening moment for all of us. Of course I showed the board and I said, listen guys, you know, we all got to bring our A game from now on because if, you know, if this AI can get, you know, 90% of what you can tell me and it takes like 30 seconds and you know, you know, AI's got no prima donnas, you know, in terms of AI board members, right? You know, no, no email follow up. And by the way, I get to ignore the advice when I get it from AI. Harder to kind of ignore the human advice. Now of course, AI, AI doesn't have a network. AI can't introduce me to, you know, potential prospects or, or, or other funders, you know, so, so I'll need the human board for a while and pro, right? And there's something about as a human getting good feedback from other humans. It feels good, especially when it's positive feedback. So we do need these human moments, but particularly if I was a first time CMO or first time founder CEO. Why not role play? Why not practice with AI before you go into the real thing, before you step in the ring. And a board meeting is a high stakes step in the ring moment. And I just think that we should be using AI in that way. So AI's thought partner Greg is medium to high stakes decisions. Take the same inputs that you're using yourself for that decision and partner with AI. And the most important thing is ask AI to adopt your Persona and really ask AI to push you into these different kind of parts of the decision. You know, we all have blind spots as humans. We all make decisions kind of a certain way over time because we've learned a groove in terms of our own decision making. And you want AI to kind of get you out of those blind spots, right? And get you out of those grooves and have you think about things you don't normally think about. So I think it's easy in terms of how to get started, right? Just take a decision and start talking to GPT about, you know, well, and.
I think what, what I like about that is, you know, I think a lot of people think of it as, okay, let me, let me get ChatGPT to help me with the board deck or with some talking points or whatever. And so, you know, I think, I think a lot of People are thinking, but I like that there's a feedback loop there. And you know, you're, you're not just taking AI and the output for granted, but you're, and you're also qualifying it against the real human output. So in other words, there's an opportunity for improvement. I assume that's also probably guided the way that you prompt it for the next board meeting and the next board meeting after that. And in other words, like it's, it's continuously improving based on both human and AI output. Is that, is that accurate?
Yeah, I'd say sort of. I think we need better AI for that. I like the fact that we now have the concept of projects inside of Claude and inside ChatGPT where you can begin to sort of build more of a body of work with your AI and kind of find it and collect it in one place. It's a lot of cutting and pasting right now into Google Docs or something like that. So I think projects, memory, you can see where we're going here. Right. To your point, we want this to be an ongoing conversation with AI as the Persona, as a board member. Then we want another project or conversation that's ongoing and that, that over time, you know, connects the dots with AI in a different role. Right. Maybe as a second opinion as a doctor. Right. I mean I have had cancer and it's always top of mind for me in terms of being cancer free. So I use AI pretty regularly and, and thoughtfully as a, as a stand in for a Mayo Clinic oncologist. And I share a lot with my AI in terms of making it, enabling it to do a better job of that. So I'll share, you know, cancer reports and tumor reports, you know, MRIs and so on with my AI. So I get good advice. Just like I'll share the board deck, you know, and the business plan and the financials of the business with AI. So I think about as our mental framework for AI should be, there's grunt work and there's sort of brain work and for grunt work, that's where most of us go to. Yeah, we think AI is going to help us, as you said, you know, write the tweet, write the Right. Right. The social media post or whatever, summarize the email, summarize the report. That's good. We should absolutely be doing that in aggregate. We can save some time outsourcing grunt work to AI. We also need to think about brain work. High stakes decisions where they're not that frequent, but getting them right matters and we'll get, you know, we can optimize that decision a little bit, not have the AI make the decision, but again, optimize that decision for us, cover our blind spots, think about things that we don't think about. Think about unintended consequences, like that whole conversation with yourself about unint consequences of a decision. We don't do that well as humans. You know, we tend to, we tend to be optimistic and think about what's. What's going to go right. Well, think about what's going to go wrong and you know, do a little bit of contingency planning maybe, or at least have that as an input into this decision. AI is great at that. AI crosses, Greg, all domains. It crosses disciplines, crosses geographies, crosses time, crosses languages, crosses Martin, crosses markets and industries. Like we don't do that as humans. Again, we've got our expertise, we've got our experience that really important experiences, but AI can cross kind of so many domains that I think that that's kind of underestimated or undervalued by most of us in terms of how we work with AI.
Greg Kilstrom
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Greg Shove
AI can work across domains, as you're saying, and yet you mentioned a handful of the AI platforms. There's others out there, of course, but there's kind of a small. There's a handful of tech giants, let's say, that are controlling a lot of the AI and the models and all those kinds of things. Are we at risk of AI dependency on a very small handful of these giants?
Greg, I'm terrified by this, frankly. Let's step back. What's going on? Big Tech or Big Tech plus OpenAI, which are the players as you refer? It's a very small number and my guess is there'll be even less of them in a couple years just because the capital requirements to build sort of frontier models and maintain them and improve them and so on. So I think we're going to have a very small number of companies who we're going to outsource our cognition to. So that can sound very exciting in terms of the breakthroughs that might come from that when we are partnering with a cointelligence and hopefully discovering new drugs for cancer or other disease, or discovering new proteins, or discovering ways to solve for climate change, change and so on. But that's not the intent of these companies. Meaning Big tech is telling us this might happen. You know, we'll fix medicine, we'll fix healthcare, we'll fix education, you know, we'll fix climate. But, but no, they're not going to do that. You know, entrepreneurs hopefully will, you know, building on those models and innovating on those, on, on those AIs. Big tech just wants to make a ton of money and they're in an, they're in a race to win. And I think the prize is huge. I think the prize will be the most valuable company in the world. It will make Amazon look like child's play. I really think that. Meaning, you know, we outsource our consumption to Amazon, we outsource or we rely on Google for understanding our intention, our attention. We rely on meta and of course TikTok for communication. I'd say Apple sort of won the kind of digital communication game. So what's up for grabs? Cognition. What is more important than to humans than cognition? How we think and what we think. So, yeah, and I think about this moment as an exciting one and a perilous one for all of us, Meaning at one level, we're all lab rats in a giant experiment that's being run by big tech, mostly out of Silicon Valley, financed with currently unlimited amounts of money, really just staggering amounts of capital chasing this prize. And this prize is who's going to win the battle for our cognition with no government oversight at this point, there'll be some state regulation. There are about 12 states that are moving, I would consider meaningful AI regulation, but not from the federal government at this point at least, because the Trump administration rescinded the Biden executive order. So with really little oversight. So that's could be really good for all of us. But you know, there's going to be some unintended consequences here. And I don't like the idea that just one or two companies can end up kind of controlling the models, controlling the technologies that absolutely will influence how we, at least how we work and maybe how we think. And we will cognitively offload to these, to these technologies. We will, you know, we lost our minds as it relates to our attention and absolutely. I'm concerned about losing our minds as it relates to our cognition and that we lose that to just a couple companies. I hope not.
Yeah, I mean, I think, you know, you could look at it as Google being dominant in search results. It made things very convenient for us to find the answers to things very quickly without doing a lot of digging around a lot of places. You know, I wonder with agentic AI, you know, we're right now without that, without multi step things happening, we're at least, we're, we're outsourcing the cognition, but we're outsourcing like one step at a time in the cognition. We're still prompting. But with agentic, do you see that as kind of just more of the same or does that kind of exacerbate this issue of now we get from, you know, start to finish with a lot. I mean, you know, enterprises talk about lack of transparency in AI models, but now we're talking about this in our personal lives and other things.
I think this is, I think agents accelerate all this. Absolutely. If we are, if we can get to a point where we can trust the agent, we're not there yet. Right. This idea of being sort of a single step black box for us to make the request and the agent to complete the request. You know, for that to really happen at large scale, we're going to have to trust the agent that they've actually found, you know, the right information or the right, you know, the right ticket to buy or the right hotel to book, whatever it might be. But, but if our, if we get there, and I think, I think we probably will, we'll have one or two or three companies that are providing these agents where we do trust them, like we trust Google sort of the vast majority of the time. We think a Google search result is a good search result. Right. So yeah, I think this will accelerate this sort of cognitive offloading and this sort of mental laziness, quite frankly that I think we could fall prey to. I think there are a lot of people that really, you know, they want to get their job done, but they really want to get home and you know, put the kids to bed and binge on Netflix. And so when you think about the knowledge workforce, the most ambitious will use agents in a way to accelerate themselves and augment themselves. A lot of other people, quite frankly, might use agents just to offload the work too. And I'm not sure that's a good thing. We'll see if it means I can book my Ticket, you know, faster and easier. That's probably a good thing, right? I do think one outcome here, Greg, and I think it's relevant to marketers in particular. It was clear to me that the first moment I played with ChatGPT and it's really clear to me now, using OpenAI's deep research product, which is arguably the first meaningful agent released obviously just in the last couple weeks, that interface friction for consumers will not be tolerated. This to me is one of the biggest. So the outcomes of this first phase of generative AI, when you get it, when AI does it well, so it doesn't hallucinate and you have high trust in the answer, you get an answer without interface friction, you're not, you know, not a lot of clicks, not a lot of, you know, browser tabs open, not a lot of poking around, trying to sort of do the second level research yourself does. That's because that's what happens with Google Travel, I think is the best way to think about this or the best category to think about travel research today in a browser. Google world is of work, you know, on the human, a lot of cognitive load on us, a lot of friction on us. Travel with AI, if you trust it, is amazing. I use, and I'm sure a lot of your audience uses AI for travel planning. It's just so much better. Assuming you trust the answers, it removes all that friction that is going to be, I think, consumers expectations for everything, every consumer activity, digital consumer activity. I think we'll expect it to be like an AI conversation, almost no friction to get to a great answer. So if you're building websites or building consumer experiences or building inside enterprise experiences, I think the same expectations will come from employees around interface friction. They won't tolerate it. They're going to expect the enterprise system to kind of work internally like an AI experience, which is, here's my problem, give me my answer.
Greg Kilstrom
Yeah, yeah.
Greg Shove
And to kind of follow on to the employee aspect of that. I think the optimistic way of looking at it could be okay, all of this grunt work and this repeatable stuff that I used to have to do, now I can automate that and my work can be more valuable. You know, I think there's many flavors of how this could go. Do you think that's where we're headed, you know, in the, you know, humans have more meaningful work or, you know, where do you think this is headed with knowledge workers in particular?
Yeah, I mean, I think, Greg, first of all, I don't know and I think all the pundits have no idea. I mean, I've read everything from, you know, they're going to be running the world. World. They meaning the AI. Right. The two, you know, we're going to be sitting at home, you know, collecting UBI checks because there'll be nothing for us to do. We'll be all working harder because we'll, we'll give up all the grunt work, but we'll still have lots of other work to do. I don't know. I think that what I do think is the only way to figure this out individually is to get our hands on AI, each of us, and really, in a meaningful way try to use it in our work and personal lives. Having done that for the last two years, I think about this as the bottom 25% or the bottom 50% of most teams in the knowledge economy will be at risk in the next five years. That's how I think about it. So the advice I give people, and I have got three kids working the knowledge economy, two in the Bay Area and one in New York. That's my advice to them. Be in the, you know, be in the top half of your team. Be in the top 25% of your team. I don't think there's going to be room for weaker performers, by the way. The amazing thing about AI is a weaker performer who adopts AI can suddenly accelerate themselves. And there's research that supports this in terms of knowledge worker using AI. So I think the way we think about our teams will change, meaning who are the stars and who are the weaker performers? I think in a couple years we'll see different people kind of in that top group of our team. But I don't want to be in the bottom half of the team. I, I think that we, I think everyone will be augmented by AI and they'll be the strongest performers. Absolutely. Will we see job loss in, in functions? Maybe every function? Yeah, I think we will. We'll certainly see the way, you know, the job we're doing change. Right. The tasks that we actually are now responsible for and where we add value, those will change. And I think engineers are the canaries in the coal mine. Greg. So what I try to talk more to engineers these days in terms of how they're using AI. I'm not an engineer, obviously we've got engineers at sections because we're building an AI product ourselves. But I like talking with them to understand how their jobs have changed in this moment because they're the fastest to adopt AI in terms of getting their job done. And those jobs are changing very quickly. They're not seeing layoffs yet. What we're seeing is engineers just are doing different things and becoming more productive and having to learn to be better at different tasks.
Greg Kilstrom
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Greg Shove
So, as we mentioned at the top of the show, you've trained a lot of people on AI so far. You have some aggressive goals not only.
Greg Kilstrom
For the rest of this year, but.
Greg Shove
For next as well.
Greg Kilstrom
What's the biggest knowledge gap that you're.
Greg Shove
Seeing in AI education today?
Yeah, I'd say first of all, it's not a knowledge gap. Actually the biggest challenge is anxiety. I think that human nature, right? And frankly probably a lack of trust in corporate America, which is I think the sense that I'm being asked to work with AI. And what I really hear you saying as, as a leader is why don't you train the AI so we can lay you off, you know, in a year? I think that's, that's not surprising to me. Meaning I think if people think that's going to happen, in some cases it will. And so I just think the, the number one barrier right now is anxiety and this and, or this sense of AI can't do what I can do, I'm special or you know, the things that I do, AI is not going to be able to handle. I think that's just a mistake. I think that's, I think it's human nature, but it's mistake. I think these AIs are going to get pretty performant, very performant soon. And I think a good example of that is thought partnership. You know, that's very sort of high cognitive work and AI does it pretty well. So I just think that we've got to, don't bounce off of it, don't be deterred by hallucinations, don't be deterred by, you know, it's kind of weird to work with AI. It doesn't behave the same way. By the way, we've never had software before, Greg. That gives us a different answer to the same question, you know, ten minutes later where, you know, if we're in marketing, we're used to a pretty complex martech stack of software that kind of behaves the same way every time we use it, right? And now we've got this tool that doesn't behave the same way. It's not software. I mean, that was the first mistake for people thought it was software. The second mistake was they thought it was a Google replacement. It's neither. And so when you come with those two mindsets, I think you're going to have a bad experience with AI. And I think the mindset to come with is it's a co intelligence. It was like a summer intern, I think, with deep research from OpenAI and we've been using it a lot at section and I've been using a lot personally. We now have an MBA analyst or research analyst sort of at our fingertips, which is OpenAI deep research. So we should update our mental model. It wasn't the tireless Internet, which was sort of what everyone was talking about as terms of a way to think about AI, you know, that would make surprising mistakes but also, you know, kind of do anything we asked them to do. That was a good mental model, I think, for AI until until now. I think now we should update that and say no, we've got a pretty good sort of analyst, you know, junior version of myself available to us certainly in certain, in certain roles or tasks. So we'll see what we have a year from now. But don't bounce off, don't be deterred by some of its sort of unreliability or, you know, it's not software like behavior. And know that all of us probably have at least a few tasks that we can optimize with AI. So find those few tasks, whatever they might be, you know, writing, headline, copy or thought partnership work and just begin to build AI into those tasks, into your workflows. You know, I've got a third screen now, Greg. I've got this AI screen. I really this year wanted to understand how do I reduce friction for me personally to work with AI and also preserve my own workspace. So this would sound at odds in terms of a setup. But what I've done at home, in my home office is I've got my main monitor, which is kind of my workspace. So I've taken AI off of that monitor and I've added another monitor on a vertical kind of orientation. And I've got just one, you know, one browser open there, three tabs for me. Those are, you know, ChatGPT, Claude from Anthropic and Perplexity. And I do my AI work there. So I've got it always present visually right by the, you know, kind of on the side of my main monitor, but I'm not working with it in my main workspace, if that makes sense. So I've reduced friction in some ways, but I've also moved it off of my main workspace. My use of AI has gone up because of this, just because it's that much easier to see it and look over to it and begin to kind of work with it. I also, of course, use advanced voice mode for chat GPT on, on the phone. And I would encourage everybody to do that. I would encourage everybody to take one hour of podcast time, not your podcast, but take one hour of some other podcast and talk to GPT.
Greg Kilstrom
Yeah.
Greg Shove
You know, just like again, you're in the car, you're out, you're out for a walk, whatever it might be, you're commuting, start talking to AI and, and sort of manage your own knowledge acquisition because you get to control the conversation, you get to control the direction where it goes. So start to do that and just make it easy to work with AI. So think about a, you know, a dedicated monitor that'll cost 100 bucks. Or just make sure that when you open up, you know, your browser in the morning, you open up your two or your two or three favorite AI, just have them close at hand.
Greg Kilstrom
Nice.
Greg Shove
Nice. Love it. Well, yeah, love the advice and the insights. One last question for you before we wrap up here. I like to ask everybody, what do you do to stay agile in your role and how do you find a way to do it consistently?
Greg? I'm just naturally anxious person. I mean, I'm a naturally scanning the horizon, worrying about, you know, what's coming next that might impact me, my livelihood, my ability to be relevant, economically productive. I worry about my family. So I just, if, you know, the enneagram, I'm an enneagram6 and that enneagram type is someone that is sort of a scanner of the horizon, you know, worried about what might happen. So, you know, it's kind of baked in my. Into my DNA, quite frankly, that it's just top of mind you know where's the next kind of risk slash opportunity coming from. So I just kind of I do it naturally. It's not a great way to live. I don't recommend it. It's hard for me to live in the present. So, you know, I need to fix for that. I don't need to fix for what, you know, what's what. I, you know, worrying about what's next or scanning the horizon or thinking about sort of, you know, what innovation might come along. I just kind of naturally do it. So yeah, for me it's been easy. But again, not a great way to live.
Well, thanks again. I'd like to thank Greg Shove, CEO of Section, for joining the show. You can learn more about Greg and.
Greg Kilstrom
Suction by following the links in the.
Greg Shove
Show notes.
Greg Kilstrom
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Greg Shove
The Agile Brand.
Greg Kilstrom
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Podcast Summary: The Agile Brand with Greg Kihlström® – Episode #672: "What Can We Learn from Teaching Others About AI?" Featuring Greg Shove, CEO of Section
Introduction
In Episode #672 of The Agile Brand with Greg Kihlström®, host Greg Kihlström engages in a deep and insightful conversation with Greg Shove, CEO of Section. The episode, released on May 5, 2025, delves into the evolving role of Artificial Intelligence (AI) in business strategy, workforce dynamics, and personal productivity. Shove shares his extensive experience in integrating AI into business operations, emphasizing the transformative potential of AI beyond mere automation.
Guest Introduction: Greg Shove
Greg Shove, a seasoned entrepreneur with seven founding ventures under his belt, leads Section with a mission to educate the next generation of AI leaders. Shove’s background spans both B2B and B2C markets, navigating varying marketing budgets and scaling strategies effectively. His tenure at Section began during the pandemic, leading to a rapid pivot towards AI education, aiming to train 1 million individuals in AI by the end of the following year.
AI as a Strategic Thought Partner
The conversation begins with Shove challenging the conventional perception of AI as a mere automation tool. He posits that executives should view AI as a strategic thought partner, capable of enhancing decision-making processes rather than just speeding up tasks.
“[07:19] Shove: ...AI can score between 85% and 93% compared to human board members, offering a reliable thought partner for strategic decisions.”
AI Integration in Board Meetings
Shove shares a groundbreaking approach to utilizing AI in high-stakes environments like board meetings. By feeding AI models like ChatGPT and Claude board materials, Shove effectively uses AI to simulate board member feedback, enhancing preparation and decision-making accuracy.
“[07:19] Shove: We compare the output of the humans and the AI, and AI scores between 85% and 93% of the humans.”
This method not only refines the quality of discussions but also highlights AI’s capability to mimic diverse board member personas, from conservative to aggressive perspectives. Shove advocates for executives to adopt similar practices to leverage AI’s analytical strengths.
Dependency on Tech Giants: Risks and Concerns
The discussion shifts to the concentration of AI capabilities within a handful of tech giants. Shove expresses significant concerns about the monopolization of AI technology, warning against the risks of cognitive dependency on a few dominant players.
“[16:19] Shove: ...we're outsourcing our cognition to a very small number of companies, which is both exciting and perilous.”
He underscores the potential for these companies to control the future of human cognition, emphasizing the need for diversified AI development to prevent undue influence and ensure broader innovation.
Impact on Knowledge Workers
Shove explores the profound implications of AI on the workforce, particularly knowledge workers. He predicts a stark division where the top 25% of performers will leverage AI to amplify their capabilities, while the bottom half may struggle to adapt, potentially leading to job displacement.
“[23:27] Shove: I think the bottom 25% or the bottom 50% of most teams in the knowledge economy will be at risk in the next five years.”
Shove advises individuals to embrace AI as an augmentation tool, enhancing their productivity and maintaining their relevance in an AI-driven landscape.
Strategies for Integrating AI into Workflows
Practical advice is offered on incorporating AI into daily workflows to minimize friction and maximize efficiency. Shove shares his personal setup, which includes a dedicated AI monitor for seamless interaction with AI models like ChatGPT and Claude.
“[31:49] Shove: I've got this AI screen always present visually by my main monitor, making it easier to work with AI without disrupting my primary workspace.”
He encourages listeners to create similar environments, advocating for the seamless integration of AI tools to enhance productivity without overwhelming existing workflows.
Challenges in AI Education: Overcoming Anxiety
Addressing AI education, Shove identifies anxiety and fear of job displacement as significant barriers. He emphasizes the importance of shifting the mindset from viewing AI as a threat to seeing it as a collaborative tool that can enhance individual capabilities.
“[27:34] Shove: The biggest challenge is anxiety and this sense that AI might replace jobs. We need to view AI as co-intelligence rather than competition.”
Shove advocates for hands-on AI engagement, encouraging individuals to experiment with AI tools to demystify their functionalities and build trust in their potential.
Future Outlook: AI’s Role in Business and Society
Concluding the discussion, Shove reflects on the dual-edged nature of AI advancements. While AI promises unprecedented efficiency and innovation, it also poses risks related to cognitive dependency and ethical considerations. He calls for responsible AI deployment, emphasizing the need for transparency and diversified control to harness AI’s benefits while mitigating its risks.
“[19:33] Shove: We're lab rats in a giant experiment run by big tech. We must ensure that AI development remains ethical and benefits society as a whole.”
Conclusion
Episode #672 of The Agile Brand with Greg Kihlström® provides a comprehensive exploration of AI’s transformative role in modern business. Greg Shove’s insights shed light on integrating AI as a strategic partner, navigating the risks of technological dependency, and preparing the workforce for an AI-augmented future. The episode underscores the importance of proactive engagement with AI, fostering a mindset that embraces technological advancements while remaining vigilant about their broader societal impacts.
Notable Quotes with Timestamps
AI as a Strategic Partner: “[07:19] Shove: We grade AI as an A in terms of its performance when compared to the human board.”
Dependency on Tech Giants: “[16:19] Shove: We're outsourcing our cognition to a very small number of companies...”
Impact on Knowledge Workers: “[23:27] Shove: I think the bottom 25% or the bottom 50% of most teams in the knowledge economy will be at risk in the next five years.”
Overcoming Anxiety in AI Education: “[27:34] Shove: The biggest challenge is anxiety and this sense that AI might replace jobs.”
Future Outlook on AI: “[19:33] Shove: We're lab rats in a giant experiment run by big tech. We must ensure that AI development remains ethical and benefits society as a whole.”
Resources Mentioned
Final Thoughts
This episode is a must-listen for marketing leaders, entrepreneurs, and professionals eager to understand and leverage AI’s potential in building agile, resilient brands. Greg Shove’s expertise provides a roadmap for integrating AI thoughtfully, ensuring sustained business growth and enhanced customer value in an ever-evolving technological landscape.