Greg Shove on Why Most Companies Are Not Seeing ROI On AI (yet)

20:55Greg Shove:I think it might be the new normal to get started. Let's say at the same time, we're going to need the basics done well, right? You can't be playing in five different games and probably winning all of them at once. So I think maybe at a certain stage, the new normal is you're not bound by capability boundaries. I do think one of AI's superpowers is it allows us to jump our capability boundaries. And we use capability boundaries to keep everything working, keep the systems working, right? Keeps people in place in org charts. Oh, you do that job. You can't do that job. Can I challenge you on that specific one?

21:33Don't you think that one of the issues with that statement is that we are so used to think of a world of scarcity. We don't have time. We don't have people. We don't have money. And suddenly the issue is that we need to learn how to think completely in abundance terms. We have endless people and we have endless time because it's literally, if you can spin up 35 agents and the agent to manage them agent, you can do 35 people's job, which is now something that you couldn't do just like a year ago. I don't know if I believe this, but could the statement be that the issue is that we have not learned how to work like a NVIDIA processors yet?

22:10We can't have all these systems running at the same time. We're used to parallel process. And it's like for us to unlock this new technology, we have to unlock ourselves.

22:20Greg Shove:Yeah, no, I'm agreeing with you. I'm saying that AI superpowers allow us to jump capability boundaries, but it's going to be hard for the system to accommodate that. because the systems are pretty rigid. And this idea that you're not bound by your time, you're not bound by your intellectual capacity, you're not bound by your capabilities, both individually and organizationally. I think what's really going to happen is organizations will jump these capability boundaries, some of them faster. And so to your point - Not just individuals. Yeah, and education can become a software company pretty much overnight, right?

22:51Greg Shove:A designer can become a marketer and we can all start coding even and building disposable software. There's one word for all this. chaos. We're just entering into an era of extreme chaos. And organizations are designed basically to reduce risk, reduce variation, reduce chaos. Manage chaos. Yeah, because the organizations are designed to deliver earnings on a quarterly basis. Right. Predictability. Yeah. So I want to go back to Henrik's sort of question or hypothesis. I think it's very provocative, which is, you know, How much of this is going to be sort of more, not serendipity, but sort of managing the chaos and sort of not being held in place or not having one business or sort of not chasing just one opportunity, but maybe three.

23:38Greg Shove:I think that feels right to me, Henrik. But at some point, I think you're going to have to pick one and go back to the basics of just like execute really well, grow the business with margins, keep customers happy, kick ass, take names, deliver on time. Just the basics. I hear sometimes it's, well, you know, it's time to like, don't be a leader, be a steward. You're stewarding the change. Yeah, sort of, you know, but no, I think you're going to need to lead. I think you're going to need to like make decisions. I'm still torn though on that. I mean, like I, I think all logic has always been, you know, I've done incubation for a long time, right, as well.

24:15And you do portfolio entrepreneurship until something starts to kind of pop off and then you just chase that down the rabbit hole, right? But I'm just inspired by this. thinking that that might not be what you do in the future in the same way that you know and i think maybe because we've been talking to a lot of the folks that were in the early days of ai and they basically had to rethink what artificial intelligence was right and we all have these in the past you know we had these systems ai systems that basically thought like we kind of put a rationale towards the problem and suddenly they were like no we have these processors now where we literally just throw it everything.

24:51And that's what we do. And so I don't know, maybe it's just because that is how my mind works. You know what it reminds me of, Henrik? It reminds me of what Brian said to us just the other day from U, that keep the GPUs full. It's a totally different paradigm. Greg, this is an early researcher at Salesforce. He's now at U.com. He's one of the co-founders. But he said his whole mindset is keep the GPUs full. And that is, to Henrik, to your point, That's like, it's a totally, it is an abundance mentality. Yeah. But most people, most people aren't thinking like Greg, Brian told us this episode isn't released.

25:28We're kind of talking shop, but hopefully it will be by the time yours is. But he talks about how every day his goal is to get to the point that he has something meaningful to hand off to the GPU so that when he arrives in the morning, that the experiment, like you think about like working in pharma, the experiment is done. Right. But Jeremy, first I'm giving you an example. I've started this new thing where I write like basically a to-do list for myself and then write to-do list what I think an agent can do. And so if I have, when I look at my like to-do list, I kind of like, I put one on one list of the other.

25:57I, it's basically in a business, a markdown note. And then in the morning, you go to clock code and say, Hey, look at this to-do list and just start, like, you just figure out as much as you can on this list. That's kind of like for you. And the, the crazy thing is of course, like 25 minutes later is and it goes like I'm done. and then you look at this list with 10 different to-dos and it's answered pretty well enough for me to have to do the work right but then you do that and then you're like okay now like an hour and a half have gone during the day and this was basically what i have attempted to be like my day's work right and so it's kind of fatiguing because you did then you just have to feed the beast right and then you look at all these to-do lists you've had forever and you're like ah there's onslaught and it's also it's fatiguing but it's super inspiring right because it's just this fire holes of productivity.

26:44Yeah.

26:45Greg Shove:All I'm saying, Henrik, is at some point that fire hose of productivity has to be directed at, I'm not saying in your case, it's not happening, but at economically valuable activity that someone will pay for on a regular basis. You mean not building software for how to seat people at my Thanksgiving dinner? As hypothetical, as hypothetical. As hypothetical. Yeah. And that eventually investors want their capital back with a return, right? Honestly, I think you see this tension playing out right now at OpenAI. The Sam Altman memo that was leaked about, hey, we're code red to respond to the threat from Gemini.

27:17Greg Shove:So maybe we shouldn't put ads into chat GPT and instead we're going to, not yet anyway, and we'll focus on making the product better and better, better. I think there is that real tension, right? How much are we sort of keeping the GPOs full in order to deliver an amazing customer experience? And how much do we have to start to really think about, you know, all this money we've raised and investors at some point are going to ask for, uh, you know, a return on that investment. So I do think that tension is, is real and is real for all of us, whether it's a five person services firm or a fortune 500.

27:49Okay. We have to go back now because at the start you said, and I quote 10 to 15 % of enterprises are getting an A plus. The enterprise grade is a C. And then we, we kind of went down the rabbit hole of leaky ROI and individuals reaping gains themselves. Is that the case at A-plus organizations or can you say what's different in the 10 to 15 % versus the norm?

28:11Greg Shove:Yeah, I actually said 10 to 50 % of every organization was getting ROI, but the employee was keeping it because there's 10 to 15 % of the organization that are really about - Not 10 to 15 % of organizations, but 10 to 15 % of people everywhere. Yeah. Yeah. I would say the A-grade, it's probably 5 % or less. I think it's a small number of of organizations that are actually getting, you know, sustained consistent value. And our research are, yeah, I think it's a small number. And our research confirms that we just finished our biannual, you know, AI survey, benchmark survey. And that's what the data said, surveying 5 ,000 organizations.

28:45Greg Shove:So listen, I think what people are doing well, if they're doing it well is, and we've talked about this before, it's not rocket science, but you got to do it every day, kind of, you know, consistently, which is why are we doing AI? Why have AI an AI manifesto? You have to start with that building block. Why are we doing this? And how will we do it as an organization? Like what's our operating culture around AI? Will we celebrate it? Will we tell people it's not cheating? Will we actually do hackathons? Will we encourage people to build GPTs? Even if they're disposable and we throw them away, that's okay.

29:16Greg Shove:Some of those GPTs or automations or agents will be good and we'll get benefit from them and so on. So that sort of, I think that building block is just unleashing employees. Second of all, giving them great AI. Thirdly, give everyone great AI. I still meet so many organizations that are giving only a part of the organization the good AI. And maybe everyone else doesn't get it yet or they get sort of the free version. I mean, this is nonsense. I was talking to an organization just yesterday, like a global pharmaceutical company. I said, yeah, everybody has Copilot. I said, is this free version or the paid?

29:55He said, well, about 10 % of people have the premium version, but everybody, I said, well, is it dumb AI or smart AI? And he said, well, I kid you not. He said, the problem is we want to tell people the difference because even if they choose smart AI, the next time they open Copilot, it defaults back to the dumb one. And we think it's too much work. So the implication is therefore we're going to continue to allow people to use the dumb AI. It's like, what? I'm literally on this call and I think I had to turn off my camera because it's like my things.

30:27Greg Shove:This is what's going on in corporate America, right? And there's cost reasons for that, like the good AI costs more money and they don't trust their employees to use it the right way or get the value from the good AI. So just give them the free AI. It's the basics. That's why most employees, and in our survey, this is what the data said, are using AI to summarize emails, basic, basic use cases. Yeah. Listen, as a parent, as a parent of two kids, would you give one kid AI and one kid not? And say, hey, both do well. We should do that. An AP test. Do you think my sons would enjoy that? On your own kid.

31:00Yeah. Good luck with that.

31:01Greg Shove:See if you're - What a great question. I mean, how, by the way, I mean, seriously, everybody can relate to that. That's painful. You ever do that? Like as a CEO, you think this is the right thing to do? Give some of your organization good AI? Like you're special. And by the way, those people with the good AI are going to work with people who have the dumb AI. Like this is going to be in the meeting, they're going to figure this out. Oh, you give marketing good AI and give sales the dumb AI. Well, I think they're going to, those teams work together all the time. I think they're going to figure out at some point what's going on.

31:29Greg Shove:And, you know, it's just... What do you think is the best advice to the folks that are getting to the point where they would like to give people access to what's called N8N or Replit or Lovable or like something that is a little bit more meaty than your co-pilot? And I was going to stop by your question of the technology officer just getting panicked about this idea that somebody could sit and code internally in the organization with real data. Is that an experimentation you would dare or how do you think about it? Well, if you've got 75 % weekly active usage on Copilot, sure. If you've built all your, you know, Copilot studios or all your automations and you're kind of running out of gas with your existing sort of investments and you have employees wanting more, Yeah, sure.

32:18Greg Shove:You don't need to buy more AI. We routinely talk to prospects, companies that have bought three, four, five, seven, nine different enterprise AI tools, have deployed them, air quotation marks, which means they turn them on and did a CEO email and maybe one lunch and learn, and no one's using any of it. But let's lay a really solid foundation. And a really solid foundation is getting most of the organization using AI from more than summarizing your email and doing that on a regular basis, which in my mind is weekly and should, of course, become daily. This is the standard we're aiming for. If you want to be a super company, which is really the only companies that will attract investor capital in the next decade are super companies.

33:05Greg Shove:And this is how super companies behave. Most super companies are startups because it's so much easier to build a super company from day one. It's so much harder to take a company, a legacy firm, an existing organization and turn it into a super company. But it's clear super companies will win. Super companies will attract all the capital and their market caps will reflect the fact they're super companies. So that's what we have to become. And that's how super companies behave. Everybody gets great AI. There's no discrimination inside the organization. They're encouraged to use it. And they lay that very solid foundation.

33:41Greg Shove:Because before giving them the tools to build agents, let them understand their workflows and which workflows can actually leverage an agent. And so in my mind, a little bit more crawling before you run. But listen, I get it. It's easy to buy software. If you're a CEO...

34:26might use your system, but they could also just kind of take the learning and use it for themselves.

34:30Greg Shove:First of all, the data is clear. The data says that even if you learn how to prompt at work, you're uncertain or unclear about how to deploy AI in your own workflows. At home, we don't have any doubt. Like at home, we know right away, right? We can talk to AI, use it for parenting advice, healthcare advice, relationship, and so on. For some reason, we go to the office and we kind of freeze around, okay, I know how to use AI. I use GPT at home, but how should I use it at work? So this idea of use case discovery and use case coaching became so clear to us about a year ago. So Prof. AI now has a new agent and it's a use case coach.

35:03Greg Shove:Basically, Prof. AI, our system knows who you are, knows where you work and knows what job you're in. So once you know that and you have an AI powered system or coach, you can do a lot because AI is so performant and so capable. So Prof. AI will coach you on use cases and you can do that a couple different ways. It'll suggest use cases to you. Prof. AI will just serve up. Here, try this, try this. We know you're a content marketer and you work for a CPG and you live in Brazil, you work in Brazil. So here are the use cases we think make sense for you. Or you can start by just chatting with Prof.

35:35Greg Shove:AI and saying, what do you do every day? And or what are you doing this week? And what are the tasks that you need to get done so you can clock off Friday at noon? Is that the best way to discover different workflows? Is that just to do a calendar mapping? I think that's one way. I think for most people, they need some help. Again, for that 10 % or 15%, those early adopters, those growth mindset, they can probably natively on the AI figure out this stuff, just by trial and error, like we all have. But I think for a lot of people in larger organizations, they also want to know what's safe. and so Prof.

36:12Greg Shove:AI is built in a way that can sort of suggest and coach kind of safer use cases and then we can begin to share them which is really cool once you've figured out. That's where exponential gains come from right? You got it yeah. So Greg I get the use case coach that makes perfect sense to me. I'm reminded of something you said in your first visit to the show now two years ago which is crazy. You said in regards to section generally, and I think we kind of shared some cynicism around how much people want to learn. You said, I think the direct quote is, people don't want to learn product strategy.

36:50They want a product strategy. I would be curious to know with the use case coach, one thing I heard you just say is I'm curious if there are implications of that insight about product strategy on use cases. And specifically what I'm curious about is, does the use case coach merely suggest use case or does the use case coach just do the thing for you i.e. give the product strategy and why or why not yeah great question it does not do the thing so the the use case coach and prof.ai is a

37:21Greg Shove:coach it's a it's a 24-7 ai coach so it is there to help you understand you know what the use case could be how you could construct it if you will it'll it'll create the prompt for you which you You can then cut and paste and then go work with your AI, whichever AI you prefer or that your company's paying for. So I'd say it takes you two thirds of the way there much faster. So the time to value, we need to shorten the time to value for employees from their first moment of kind of exposure or playing around with AI at work. Again, they get the time to value at home really quick. I think at work, there's too much of a lag.

38:01Greg Shove:And so the whole point of the use case coach is to get people's time to value to within hours or minutes, right? In terms of play around with the Prof. AI agent and you'll have three or four or five use cases immediately identified and then go try them, see if it works. Knowing what you uniquely know about people's desire to learn and they call it friction, why did you make that design decision as far as what the product would do and what it would not do? Because we want people to join the AI class and benefit from AI as an accelerant. So we want them really proficient in these technologies and tools to get the gains versus, frankly, eliminated.

38:51Greg Shove:And I think the more you're just doing it, you're building agents that replace humans. And that's not our mission. Whereas by, it's almost one way to think of it as almost the Ikea effect that if the person has to turn the screws themselves, they'll take it the last mile, so to speak. One, you get enormous drop off in the last mile. So that's, which is kind of the argument against, but the argument for is that actually becomes the means of discovery. The person who's willing to invest that last turn of the screw is going to be way more likely to share, going to be way more likely to enthusiastically engage, right?

39:27because it required part of their investment. Is that right?

39:31Greg Shove:I think that's right. And I think it keeps the human more relevant for longer. I think that's a good thing, frankly. Can I ask you, we have this, I have this thing called autos, which basically helps entrepreneurs build a startup using AI, right? One of the things that we're learning is that the models are now so capable that we now have to design the system. And when we design the system, we have to think about, Should we just let the agent do this work or should we purposeful kind of say that the user have to do it? And we know, of course, that then to Jeremy's point, there's going to be a drop off, but you also want the entrepreneur to feel invested in this idea and having to do this.

40:11And you talked about the 10 % people that know how to use it and then the others, right? Where are you? And Jeremy and I had this conversation the other day. Where are you on the teachability of the 90 % versus the Iron Man suit that we're now handing to the 10%. And what's going to happen? Is this going to be a place where these people that you talk about, the new staff members that you talked about earlier, are they just going to be those 10 %ers? And then the 90 %ers right now won't learn it? Or some of them might make great effort. How should we think about this dynamic?

40:47Greg Shove:Yeah, I think we should think about it like any change, that we will have people that stay on the sidelines as long as possible, right? The laggards and the skeptics. I think most people, you know, will want to make the change. I mean, they're not stupid and they will begin to see this future and they want to be in it. They need to pay their bills and if they work in the knowledge economy. So I just think that we are, we need to be, again, we need to be more patient here and be more supportive. Yeah, we can use occasionally the stick if you're a CEO, Joe, like if you don't make this change, you know, you're not going to have a job here.

41:23Greg Shove:Yeah. In some, in some places and some moments that might work, but we have to do a lot more. I think this is the, is this the leaders now having the social media moment where there is the point where we owe it to each other, community, society, morality, to have more patience with people and help everybody understand how to use these tools. Yeah. Because you were like a, you're a capitalist, right? You know, I remind you for our last conversation, like, so where, where should we, how should we compute this at this point as leaders? I think we should be impatient, but supportive. I think we should be demanding, but supportive.

42:04Greg Shove:Like, particularly if we're in a company or industry that is in the crosshairs of AI, then the clock is ticking. It never happens as fast as, as sort of, you know, the media might suggest in terms of the disruption. But then when it does happen, it happens, it feels like suddenly and but more dramatically. So if you are in the crosshairs, whether, again, you're a legal firm or a management consultant or a data services firm, this is coming and it's probably accelerating at this point. And then when you get caught by surprise, you have a hard time recovering. So I think as a CEO, we need to be demanding and patient and sort of ambitious, but we need to put in the support required.

42:44Greg Shove:Yeah, I think it's okay to say this is a shared responsibility. I, as a CEO of the organization, can't do everything. You have to show up with a level of your own ambition and your own effort to turn the corner on this AI thing. But we have to do it together and we have to do it relatively quickly. But we'll support you. We'll provide the coaching. We'll provide the best tools. We'll provide the managers with the training they need to actually get their teams to be AI enabled and then use that time in a better way. And so a lot has to happen here. And again, it's just so much easier doing it with a new company, with a new organization versus applying it to an existing world.

43:23Greg Shove:But I think we need to be impatient, but supportive. And I think employees own this responsibility. I believe it's shared. We got to get our head in this game though. Otherwise, I think we won't know how to react. To your point, we won't know how to react and work with these AIs where we maintain our value add. As humans. And maybe it's just that we will have to change. I mean, Nicholas, my business partner, he made this point yesterday that sometimes there is elements in the body, like the spleen, that doesn't really do anything. And until that it breaks and then you have to go and operate it out.

44:03But when it goes wrong, you have to operate it real fast, right? And so maybe increasingly it is okay to think of us as an architect for these agents. And then our job is to sit there and be ready for something that doesn't work. The code kind of like is crazy because at this point we don't know how it's written because all these agents have been reading it all. The marketing copy is just spitting out and it's an automatic system. And at one point it spits out something out that's vile that we have to stop. And so back to the other point about thinking about scarcity versus abundance, maybe also that increasingly there will be a different motives for us humans on how we conduct our work every day.

44:43Greg Shove:Yeah, I think that's right. But I think, Henrik, that where we will insert ourselves is not just to catch the mistakes and solve the problems. I think it's going to be earlier. And I think I want my AI to tell me, okay, now be human and inject your opinion and brilliance into this decision. Otherwise, Henrik, all these startups are going to be the same. If we're using AI to start all of our companies and do all this work, we're not going to have any differentiation in these products and services. And so no one's going to win. I'm not that bullish on AI is going to come up with all these ideas and start all these companies for us without these moments of where the human needs to come in and make a call.

45:24Bring your humanity. Bring your humanity.

45:28Greg Shove:Yeah, bring a point of view that's differentiated. To your point around job searching, now there's no friction in job searches. And so people can apply for a thousand jobs and every application looks like it's personalized. And that's what the data says is happening, right? And that whole market's basically no longer functioning. There's so much congestion in that system, in that marketplace of knowledge, work, jobs. It's basically not functioning right now. And I think we'll see the same in entrepreneurship. If all these entrepreneurs are relying on AI to come up with these ideas and execute their go-to-market plans, we're going to have a sea of sameness.

46:01Greg Shove:I agree with that. So I want the AI, Henrik, to say, hey, I'm doing all this work for you, but here's five moments where you need to come in and actually steer me. You do you, buddy. You do you. Yeah, we do you because if you don't, you're going to get my startup idea number 495. You're going to get Greg's stuff. You're going to get Greg's stuff unless you interject right now. And I gave this business idea to a thousand other people last night because they're all using AI. That's what I'm hopeful or that's what I want from my AI. I want, hey, I'll do a lot of heavy lifting, but we need some brilliance here.

46:38Greg Shove:We need some human brilliance. What's the pricing going to be of this product or service? If what I do, I have all the same prices. We've got to hear your short details on how folks can try out Prof. AI. So I think we've kind of teed it up nicely. If folks want to get in there and start to kind of play and find use cases, how do they find it? Yeah, go to Prof. AI. And the consumer version is free. If you want up your team, then you got to call me and we'll charge you for it. No, go to Prof. AI. It's great. And we want as many people as possible to join the AI class as fast as possible. As I said, there's no charge for consumers.

47:15Greg Shove:Companies pay. We just announced our agreement with OpenAI. We're about to announce our agreement with OpenAI this week. So we're one of their service partners to help their enterprise clients drive higher levels of adoption with GPT Enterprise. Good for you guys. Well done. Yeah. I think we're all seeing the same challenge, which these technologies offer so much upside, but the anxiety and the skills are not... Anxiety is too high and skills are too low to actually take advantage of these capabilities. As we've talked about before, this is not software. AI is not software. And when it's deployed like software, it fails.

47:56Greg Shove:And this is the key mistake that every leader is making. They're deploying AI like they deploy other software. and this is not software. And so we've got to really do this differently if it's going to work. Brought it home. I mean, what a treat to have the first three-peat in Greg's show. I mean, of all people we've talked to, he's a worthy three-peater, right? He's such an interesting person. You know, I mean, I think a lot of us, we work a lot with how do we get AI into the organizations. And there is this kind of like almost camaraderie of people that are on the front line. and they're like, well, you know, what does work?

48:32What doesn't work? We've touched the orb. Yeah. Right, yeah. I think we all, like, I think this is all this raise for the holy grail of figuring out how do we best take this new technology and put it to good use. And we're all just trying all these different ways. And so, I mean, for me, I'm very an agenda talking to a person like him. Definitely comrades in arms, that's for sure. I thought, I'm just rattling through a bunch of stuff because I know we've got a bunch of things on our mind, But I mean, the insights per minute, you know, one of the highest, I think, of any guest, because Greg just has so much experience.

49:06He has so much exposure across some of the different areas. One of the things that struck me was his comment. Can you imagine giving one of your children a smart AI and one of your children a dumb AI? I think it's so obviously wrong and no parent would do it. And yet we see it all the time in organizations. This department can have good AI. This department, we're not going to give any access at all to. And it's so, I realize there's dangers to treating companies like families, companies aren't families. But to Greg's point, marketing's working with sales, you know, operations and product development, they're going to know if one department has dumb AI, they know it.

49:48And that will create a class system in the organization. And furthermore, you almost negate the value of smart AI. If a team working with smart AI is collaborating with a team that works with dumb AI, the cumulative outputs, I don't think, are going to rise to the level of the smart AI. I think they're going to fall to the level of the dumb AI. What do you think? I think that's true. And I think the other thing that he pointed out that resonated with me is that 10, 15 % of everybody in an organization are pretty good at it. And they kind of super users. And then you have, like, the rest. And what the rest does not need, which I think you guys both picked on, was they don't need to learn how to prompt better or to learn to do these more generic things.

50:34What they need to learn is how to do their job better with AI. And so they are looking to not kind of go from the abstract understanding of how do you use this tool in a generic way and then apply it myself to my job. they almost need much more specific to say, if you sit in this type of job and you're doing this type of function, here's like a use case that is very useful for a lot of other people. Now try to train on that. And so I think a lot of us, we want to give people the fishing rod and teach them to fish generically. But I think maybe an unlock for a lot of organization is that you're just going to go much more specific.

51:13I say as a statement, but I mean as a question. Start to do this here. Yeah, I think that's right. And I really like your comment. I don't know if you realize you're making it, but the comment that the goal isn't to learn AI. The goal is to be even more effective in your work. And I've started kind of using that language in some of my training programs and things like that. My goal is not to help you learn AI. That's, you know, it's the means. The end is you more effective, more enabled, more quality, more joy, right? and learning how to collaborate with AI is a means to that end. But the end can't be working with AI.

51:52The end is actually doing whatever you do better. And then I think the second thing which I'm stuck on, and I think you mentioned it also in one of the other episodes, but it is interesting is when people are starting to become more efficient or even a little bit better doing their job with AI, where does that extra time, energy, where does that go? And you were talking about the, Parkinson's law. I mean, to me, it was very pointed when you said what you ask your BARC team. That's incredible. That's evidence right there of Parkinson's. I don't know if it's Parkinson's law necessarily, but to me, that was a great story.

52:27But anyway, you were saying about Parkinson's law, please. No, but I do think that I think a lot of us are now trying to figure out where does this extra time go and how do we, and I think what he was saying, which I think is an interesting point is that that is not necessarily the company's time i realize it's on their dime but maybe you know we pushed organizations so hot that what you really need is to give that time back to people to think about how do we get into growth mode again in a lot of these organizations that the time shouldn't just be sucked away and then yielded into kind of like higher ebit it should be how do you become like a better organization a more robust organization, one that grows faster?

53:07Well, it is, it's an age old problem. I mean, this, this was true long before AI that people tend, it's a lot easier to make improvements than it is to do something new. You know, I like what he said about cut versus create. And you think about cutting as it's six sigma, it's process, it's standardization. and folks will, that's a kind of a known area. And solving a known problem is a lot harder than identifying a new problem and creating from whole cloth. It's a very different challenge. And so this, in a way, AI is bringing to a fine point the classic challenge of explore and exploit. Organizations, I mean, that's like Jim March's theory from the 70s.

53:58Organizations are designed to exploit. That's their job. to exploit an existing market, existing capabilities, existing resources, et cetera, then that's at odds with exploration. And the way you deploy resources when you're exploring is different. And I love March's kind of classic line. He says, the organization that only exploits generally suffers obsolescence. It's to say they go bankrupt, right? But it's really hard. I mean, that's where maybe, you know, we talked about having experts on the pod. Maybe an interesting expert, Henrik, for I'm just riffing real time here. not to make any promises to our audience, but my good friend and hero, Charles O 'Reilly, he's the author of Organizational Ambidexterity.

54:40I mean, it's the kind of the quote unquote solution to the innovator's dilemma, so to speak. But he's a really interesting thought leader. And he and I have created new AI courses, Stanford, which is probably coming out in February-ish. But he was being an interesting expert, not because of his knowledge of AI, but because of his deep understanding of this fundamental tension. And the AI moment is bringing that tension to a fine point. And it's exposing, I would say, maybe to come back to our conversation with Greg, it's exposing how little tooling individuals and organizations have around exploration.

55:17I think that's a super interesting point. And I think very, very good observation that is probably the in it's kind of like the thing that people are not seeing yet which is all these tools makes basically the factory work and all this factory work that people have been doing can increasingly be done with agents and so what is left and that is the exploration but the exploration doesn't really have a rule book i realize there's innovation experts like yourself soft but most of the time that's not what most of the organizations spend any time on but now right maybe they can now you can't and if you don't i mean it it's a race to the bottom right you can only exploit become more so much more efficient before you're basically at razor thin margins and like you're and you're cutting into bone like there's nothing left there's no more fat to trim and so if your expertise is trimming the fat eventually that's you're putting yourself out of business.

56:17I would be remiss if we didn't also mention one of the other things Greg mentioned to us, his emphasis on manifestos. He mentioned, you know, super companies. I wrote down three things. They have a manifesto. Why AI? They give people access to great AI. And then 30 said, everyone has access. And on that point around manifestos, I just as a simple data point, because I really wanted to validate that statement. I was at a retreat of maybe 50 private equity CEOs a couple weeks ago. I did a similar, by the way, I've seen these findings on about share replicated. I had a similar retreat among a bunch of CFOs and COOs.

56:54And at each of those three environments, I gave them, I call it my 26 point diagnostic. What are the key elements that need to be of heart of an effective gen AI powered transformation? And two of those elements are relevant to this conversation. One is, has the CEO written an AI manifesto. And two, has the organization established clear governance guidelines regarding use? Okay. In each of these environments, both with CEOs and separately CFOs and separately COOs, a very clear pattern emerged, which is most organizations have a clear governance policy and very few organizations have a leader who's crafted a bold ambition.

57:38and all organizations are wondering why are people stalling out and I actually put the data on the slide data from the room so not like general data but actual y 'all just said this and I put it on the room and I kind of I mean I lovingly lightheartedly make fun of them like wait you guys are wondering why people are stalling out when 90 % of you said we've told people what they're not allowed to do and 10 % of you have said I've told people what I hope they do is there any wonder why people are spelling out but it's a little bit of the micro version of the same picture which is you know we know how to exploit we don't know how to explore and that is going to be such a important part of living in an ai world where exportation becomes cheaper and cheaper because the machines are very good at doing machine type work i think as always if people have listened to the whole conversation with Craig.

58:36We hope they'll share this episode with somebody else. One thing I will say, actually, just as we close is folks should listen for the one thing they can do immediately. There is something they can do immediately that I've got written down here. I'm not even going to, I'm not going to spoiler it. There is something you can do immediately and it's not used Prof. AI though. Go check it out for sure. This isn't a product marketing thing. Um, you can actually do something immediately. And I'll just say this, it involves your calendar. That's all I'll say. Okay. And with that, bye-bye. Bye-bye.