Episode web page: https://bit.ly/4jHDYyu ----------------------- Got a question? Want to recommend a guest? Or do you want to tell me how the show can be better? Send me a voice message via email at [email protected] ----------------------- PROMO CODE for this episode with Section's Greg Shove: USERTESTING30 The code is good for Section courses and memberships. ----------------------- In this episode of Insights Unlocked, Michael Domanic, Head of AI at UserTesting, sits down with Greg Shove, CEO of Section, to unpack what it truly means for businesses to embrace AI transformation. Greg shares his personal “aha” moment with generative AI, how it led him to pivot Section into an AI-centric business school, and why every executive should view AI as a strategic thought partner—not just a tool for marketers and engineers. From experimenting with AI as a boardroom simulator to identifying organizational resistance, Greg gets real about what’s holding companies back from adopting AI effectively. He also offers practical advice for leaders navigating internal fears, outlines how businesses can build impactful AI pilots, and explains why creativity and experimentation are critical to unlocking AI’s full potential. What you’ll learn in this episode: Why Greg believes AI is the new cognitive edge for leaders The story behind Section’s pivot to AI education Barriers to AI adoption, including fear, poor training, and restrictive data policies The difference between deploying AI tools and truly transforming workflows Why language-intensive roles are leading the charge in AI adoption The power of autonomous agents and what they mean for the future of customer experiences How to structure internal AI pilots that actually move the needle Who should lead AI transformation inside your organization—and the creative mindset they need Resources & Links: Connect with Greg Shove on LinkedIn Connect with Michael Domanic on LinkedIn Section School Greg’s website Learn more about Insights Unlocked: usertesting.com/podcast
Chapter 1: Who are the hosts and guest introduced in this episode?
Welcome to the Insights Unlocked podcast. I'm Nathan Isaacs, Senior Manager for Content Production and User Testing. And joining us today as host is Michael Dominick, User Testing's Head of AI. Welcome, Michael.
Hi, everybody.
And our guest today is Greg Shove. Greg is the CEO of Section, an online business school for the age of AI. He is a six-time founder, investor, and AI thought leader. He helps executives leverage AI as a strategic partner, driving innovation and decision-making. Welcome to the show, Greg.
Thanks, guys. Great to be here.
Chapter 2: What was Greg Shove’s 'aha' moment with generative AI?
Fantastic, Greg. It's great to have you. So look, you've been a founder multiple times and have seen major tech shifts firsthand. So what was the moment that made you realize generative AI wasn't just another trend, but something that could fundamentally change how businesses operate?
Yeah, well, Michael, first of all, let's go back to February the 1st, 2023. That was the moment I was playing with ChatGPT+, and I was like, wow, this could be what keeps me working. I want to keep working. I live and work in Silicon Valley, the most ageist work environment in the world. If you're not 28 in a hoodie, you're an idiot. I'm 63. I type with two fingers.
And in fact, I've started seven companies because I started one more last year. And I just thought, okay, this was going to be my cognitive edge, the way that I would sort of keep me sharp and keep working. And it was kind of that hour, actually, that day, that hour that I decided to pivot my company section. which I'm the CEO of, to become an AI school for the age of AI.
And so kind of all in from that moment on.
So Greg, what were you doing? What did you say, February 1st of 2023? What was your prompt and what was the output? Yeah, great question. I'm not sure I remember.
Probably a bit of both, like work and personal. So I can imagine I was impressed in the early days with kind of thought partnership with AI, asking medical questions or travel questions, things like that. So, you know, life at home, right, and then life at work. One of the early use cases that we used at work was we asked AI to pretend to be a board member.
And we sent our board deck, the deck that we sent to our human board members, we would also provide that. We still do. We've done this every quarter, actually, since then. We provide the board deck to ChatGPT, Claude, Copilot, Gemini, and basically ask the AI to adopt the persona of an aggressive board member, of a conservative board member.
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Chapter 3: How is AI being used as a boardroom simulator?
you know and really kind of get us ready for board meetings and as i said we've done it every board meeting since the ais score about 85 to 90 percent of the humans meaning we compare what the humans tell us in the actual board meeting to what the ais told us before the board meeting And AI is getting most of what the humans are telling us.
Not everything, and by the way, AIs don't write checks yet. You still need board members, at least if you want the money, if you're a startup. But that to me was a pretty eye-opening use case, particularly for leaders. I think a lot of leaders think that they don't use AI, AIs for the content marketers or whatever.
ai's for the software engineers you know that other people you know do that kind of hands-on work that needs ai but i that's not my point of view my point of view is any medium to high stakes decision every executive every leader in any industry should be using ai at work as a thought partner and frankly at home as well in terms of you know medium medium to high stakes personal decisions
So I've heard you tell that story before about using AI in a board meeting. And I've also heard you talk a lot about how executives should be using AI a lot more, but maybe they're not, not as much as we would like to see. So what are the barriers? What's stopping those individuals from fully embracing and integrating this?
Yeah, I think a lot of things, Michael. I think that maybe not executives, but maybe. But most of us have a fair degree of anxiety and sort of concern about AI, understandably, right? And all the research, and there was some new research just this past week from Pew Research about the levels of anxiety, about job loss, about... you know, job degradation and so on.
And so again, not surprising if you get your news about AI from the media, the media's job is to outrage us and scare us and get us to click. And so really the narrative about AI has been this AGI, this superpower, You know, this sort of this coming agent that's going to take our job. And by the way, you and I were both at the AI conference last week in Las Vegas.
Human X, you know, might have noticed that one AI vendor on the conference floor, you know, stop hiring humans was their sort of tagline, right? Right across the front of the booth. You know, and Mark Benioff at Salesforce is talking about agent force all the time as a replacement. to humans. So not surprising. People are anxious. That's one. They're not getting properly trained. It's clear.
And again, we've looked at research and we've done our own research at Section about employee satisfaction with training about AI. And there is no satisfaction about the training, meaning most employees aren't getting trained properly. I think most companies, Michael, deploy this thinking it's software. I think it gets bought by the head of IT or the CTO or the head of technology.
And I think there's this misconception that AI is like software, like an ERP or a CRM or, you know, some sort of marketing automation software. And it's nothing like software. It doesn't behave like software. We don't interact with it like software. You know, it hallucinates. It gives us different answers to the same question and so on. So I think that just slows adoption.
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Chapter 4: What are the main barriers to AI adoption in organizations?
Yeah, I agree with you on all of that. And at Section, so you're offering businesses content courses that are going to help their employees upskill and move through this transformation. And I should mention that user testing and full disclosure is a customer of Section. We are using your content for the same purpose, right? To help us enable that transformation.
Absolutely.
Kind of putting the focus on your courses, what are those in-demand AI-related courses that your students are enrolling in? What do you see resonating with businesses with the content that you're offering them?
Yeah, I think it's probably what you would expect, Michael. And I'm sure what most of the employees at user testing will take advantage of as well, which is if you're new to AI, you want to get the basics. So, you know, basic prompting and how to get the most out of your conversations with AI. And then, of course, the advanced version of that course. So basic and advanced.
Pretty quickly after that. employees want to make it relevant to themselves. So they want to take the course about how to build your own use cases, how to kind of do your own workflow audit, if you will, on yourself or on your team, and then find the use cases where there's the highest return to be using AI. And that means basically functional courses. So AI for marketers, AI for
finance people, AI for HR and so on. So we have a growing catalog of functional classes as well. And then finally, some of those leadership and strategy classes. So if you're leading a team that's implementing AI, how do you do that? And how do you change the workflows of the team? How do you get the team ready to adopt and deploy AI? And then how do you set AI strategy?
So we have one class that's really sort of a classic strategy class. for leaders so they can figure out a framework to prioritize and greenlight AI initiatives.
Yeah, so you have a pretty good look at what businesses are doing and where this is being adopted within businesses. So is there a specific role type that you're finding is leaning in more than others? Is there a specific part of businesses like marketing or sales or, you know, engineers that are leaning in more towards this transformation and the content through section? Yeah.
Yeah, yes, yes, and yes. I mean, it's all the language intensive functions, right? So we know it started with software engineers, and I consider them, Michael, the canaries in the coal mine. I think as leaders, we should all be studying carefully how software engineering teams are using AI.
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Chapter 5: What types of AI training courses does Section offer businesses?
So I do think part of this is being intentional around the pace that you want to go as a leader with your organization. I'm okay if people say intentionally I'm going slow versus I'm putting my head in the sand and not worrying about it. Be thoughtful about it. For many of us, we're going to have to move fast.
Certainly in my business, which is education, online education, content development, as you said, we're moving very quickly. I don't expect Michael to be creating courses in a couple of years. I really don't. meaning it'll be AI coaches.
And we're releasing a product next month called ProfAI that will really be the way I think almost all learning is delivered in the future will be through AI coaches and AI tutors.
So I think the right way to talk about it as a leader is honestly, and this is what I say to Section, and in fact, I said this on Monday at our all hands, we are adopting AI even faster at Section, both in our internal workflows and in our product roadmap. And that will do one of three things to each team.
Some teams will get bigger because they get such leverage from AI and they have such an impact on the business that, in fact, putting more humans into that team with AI is good for the business. You can imagine that scenario happening in all kinds of different teams in different industries.
Salespeople, for example, if they're more capable with AI, you're going to want more salespeople likely because they drive revenue. Some teams will stay the same size. And they'll get more done with AI, depending on the team. And some teams will be smaller. I don't think dramatically smaller, but I think in some cases they will be smaller. And I'm not sure what's going to happen to each team.
And that's what you have to say as a leader. We're not sure, but let's do this together. And sort of be driving that change versus being forced into that change and kind of playing catch up. So I think that's my advice to leaders. My advice to employees is similar. Like adopt it yourself sooner and really get comfortable and really get good at knowing where AI can help and where AI doesn't help.
You know, expose AI's weaknesses. And so you know where it's worth working with AI and where AI is not going to give you an assist. And just be at that edge, just a little closer to that edge, I guess, as an individual. So you'll see what's happening. Again, don't put your head in the sand. I think this is coming faster than we realize.
Yeah, I think that's some helpful advice. And I would agree with you. I think that's how we talk about it here at user testing as well. So putting the focus a little bit on the folks listening to this podcast. So many of those individuals are, you know, people who are constantly exploring ways to elevate their customer experiences.
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Chapter 6: Which business roles are leading AI adoption and why?
And we're kind of just spending probably an hour or two getting to a decision around a weekend trip or something like that. And when you do that with AI, we don't yet trust AI to the extent we need to, to probably follow all the recommendations of AI. But I think we're getting close. When you do that with AI, plan your own sort of vacation, you realize how frictionless
the experience is when compared to the old way. Because you've got one conversation with one UI, with one source of knowledge or one expert. And that really, to me, for all of us who are building consumer experiences, that to me is, I think, the most dramatic change or paradigm shift for consumer experiences because of generative AI, which is interface friction will not be tolerated. Consumers
particularly younger right consumers ai the ai native generation they're growing up in a world where they won't tolerate that kind of friction they won't think about look at the amazon product page talk about a page full of friction right there's the product sure somewhere in there is the product and there's ads and they're sponsored and there's all kinds of information on that page and a lot of cognitive load is therefore pushed to the consumer
when they reach that page to make a decision. I just think that, again, in a few years, we'll look back at that product page on Amazon's website and say, what were we thinking? That's just loaded with friction and loaded with sort of cognitive burden for the consumer. And AI can really wipe that away. And I get it. I can see why Amazon's not in any rush to build that page.
I can see why Google has been rolling out these changes slowly to search results and so on, because it really does threaten their business models. As you might expect, but there's a much better consumer experience around the corner when it's generated by AI.
Yeah. So your example of vacation planning reminds me of some of the demos that we've seen from Anthropix computer use model, OpenAI's operator model. Those are kind of like the truly autonomous agentic. AI models that go out and do the things for you instead of you having to do them.
Not only is that reducing the friction of you having to sift through all the different travel websites, it's just doing it for you. There's ideally no friction there. What should businesses be thinking about right now if we are actually going to quickly enter into a world where autonomous agents are doing a lot of the things that we as humans do today?
I just think you've got to stand up a lot of pilots. I think you need to be prototyping like crazy. And I don't mean toys, meaning I don't mean like the AI-powered kiosk for Burger King or whoever it is. Forget the AI toys. That's just noise, press releases, and a waste of time.
I think what businesses ought to be doing is go in two places, internally in their internal workflows and in their customer experiences, whether they sell a product or a service. I don't think it matters.
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Chapter 7: How should leaders balance AI transformation with employee fears?
I think that no organization has kind of like... figured this out really well, or maybe, maybe a few have, but I don't know. What are your thoughts? Like if an organization comes to you and says like, we're serious about AI transformation, we want to do this in our products. We want to do this in our business. Who, who should we get to drive this for us? What would your answer be?
Yeah, my answer would be it's probably three people combined into one. If you could do that, and if you can't, then pick one. The other two support. And the three are the technologists. You need someone to buy the AI, connect it to the data sources, the company data, secure it all, and get it in the hands of employees.
So that's the technologist, CTO, head of engineering, whoever owns that responsibility inside the org. The change manager. Who is the person that is best at not just the upskilling, but the change management required? Because it's really about change management. It's about getting humans less anxious and more confident and, frankly, more willing to accept and work with the AI.
Some of the latest research about employees revealed that some employees are actively resisting. You know, they're fighting back because their perception is, you know, the AI is coming for their jobs. It kind of reminds me of, you know, people in San Francisco putting cones on the top of Waymos so the Waymos get confused and can't drive, right?
If employees start doing that, that's not a good thing, right? AI is not going to land inside your organization successfully. So you need the change manager. And the third really is the business person and the business person who understands the workflows, understands how work is done and or how products get built, depending on the kind of company you are.
So understands where AI is going to basically insert itself successfully. in those workflows or product roadmaps. I think that's the lead person. This is not a technology challenge primarily. I think there's sure some technology challenges, but I think the primary challenge here is knowing where to insert AI in the right places and then getting the humans to support that effort.
When you think about deploying an LLM specifically, I think agents are different. When you think about deploying an LLM like ChatGPT or Microsoft Copilot, It's only as good as the humans that work with it. So if they're resisting, if they're anxious, if they're not willing to learn, then the LLM will not deliver the output and therefore the productivity gain, the ROI that clients need.
I think that's why a lot of companies will struggle with their LLM deployments. is that they just haven't done the change management. They haven't done the upskilling. They haven't really got the humans ready for working with LLM. I do think some companies will skip that phase and try to go just to agents. Because when you go to agents, you're essentially trying to take the human out of the loop.
And put them maybe at the beginning or the end, but not in the middle. When you deploy an LLM, you are putting an LLM in the hands of every employee, I would assume. That's my recommendation. Give every employee access to a full featured LLM that can access company data. Maybe not all the data, but can access enough of the company data to be useful. I think every organization should do that.
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