Greg Shove, CEO of Section and Prof AI, joins Beyond the Prompt for the third time to discuss why most companies are not seeing meaningful ROI from AI and what enterprise AI adoption actually looks like today. While a small group of employees are already using AI to become more productive, organizations struggle to capture that value due to culture, incentives, and workflows that have not yet adapted. Greg describes how AI is breaking traditional capability boundaries, allowing individuals to take on new types of work across roles, while companies remain structured around older ways of operating. The conversation explores why ROI is “leaking” to employees, how uneven access to AI tools limits adoption, and what leaders must do to turn individual productivity gains into real organizational impact.
Greg Shove describes a growing gap between individual and organizational AI adoption. A small group of employees are already using AI effectively, while most companies are still early. AI is generating real productivity gains, but those gains are not being captured at the company level. Instead, they are absorbed by individuals who use AI to work faster, often without changing team outputs or structures — raising a central question: if AI creates time, where does that time go?
The conversation explores why enterprise AI adoption remains uneven. Many organizations lack a clear point of view on AI, and workflows take time to adapt, making it difficult to turn individual gains into coordinated results. At the same time, AI is breaking capability boundaries, allowing people to take on work across roles while companies remain structured around existing ways of operating.
From a leadership perspective, Greg emphasizes that the challenge is not just efficiency. AI creates capacity, but without clear direction on how to use it, that capacity disappears. Leaders must decide how to reinvest the time AI creates if they want to capture real business value.
Key Takeaways:
Greg's LinkedIn: linkedin/gregshove
Section LinkedIn: linkedin/company/sectionai
Section AI: sectionai.com
Prof AI: prof.ai
00:00 Intro: Entering the Era of AI Chaos
00:31 Meet Greg Shove
01:32 Enterprise AI Is a C Minus
01:51 AI’s ROI Is “Leaking” to Employees
03:04 When Individuals Outrun the Organization
05:44 When AI Breaks Workflows
06:47 Disposable Software and New Ways of Building
09:10 Cut vs Create
12:01 Using the Calendar as a Lever
16:24 Why Enterprises Don’t Move
17:32 When Customers Force Change
21:31 AI Breaks Capability Boundaries
25:44 The Productivity Firehose
27:49 Who Actually Captures the Value
28:45 Why Everyone Needs Good AI
32:00 Adoption Beats Buying More Tools
40:17 Teaching the 90 Percent
43:48 Where Humans Still Matter
48:09 The Debrief
📜 Read the transcript for this episode: greg-shove-on-why-most-companies-are-not-seeing-roi-on-ai-yet/transcript
[00:00:00] Greg Foldes: there's one word for all this chaos.
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.
And education can become a software company pretty much overnight. Right. A designer can become a marketer and, and, and we can all start coding even and building disposable software, like all the, there's one word for all this chaos.
We're just entering into an era of extreme chaos
My name is Greg Shove. I'm the CEO of two AI companies, and I spend my life Monday to Thursday in corporate America, where it's one tale of ai, which is like, Hey, this is sort of useful, but not great. And then Friday to Sunday, I live in San Francisco where everybody can't live or work without ai. So we're gonna talk today about the Tale of two ais.
[00:00:51] Henrik Werdelin: Greg, thank you for coming back for the third time. You are now our resident expert in how, what, what, what is the level of how well corporations are integrating AI into the organization? So what is the current scorecard and what can they do to become better?
[00:01:09] Greg Foldes: First of all, thank you for inviting me back for the third time. I'm not sure I'm an expert. I don't think any of us are yet.
[00:01:17] Jeremy Utley: Mm-hmm.
[00:01:17] Greg Foldes: I think it, we will all know who the experts are in about 10 years. Hopefully by that point, all the AI influencers that are in my LinkedIn feed are gone, and it will, will, we'll actually have some experts, right? Uh, those who have actually built and transformed with ai.
Listen, here's what we're seeing. The grade for enterprise AI adoptions, probably C minus at best, but for 10 to 15% of the organization, it's a plus. I mean, the reality is there's all kinds of ROI from ai. It's not that there isn't any, it's leaking.
[00:01:50] Jeremy Utley: Say more
[00:01:50] Greg Foldes: about that. Leaking. ROI. Yeah, the ROI is being kept by the employee.
[00:01:55] Henrik Werdelin: Mm-hmm. I think that's very true.
[00:01:56] Greg Foldes: 10 to 15% of every organization are the growth mindset. Are they ambitious? Are those that are curious? Are those that listen to this podcast? They figured out ai, whether their employer wanted them to or not, they figured out AI quickly and they're using it on their, you know, either the official AI that the company's paying for, or their own AI that they're paying for, or maybe they're not even paying for it 'cause you get great ai, get great AI for free, as you know, and they're keeping the gains.
And of course they should.
[00:02:26] Henrik Werdelin: Do they keep it because they want to? Or is it, lemme give you an example. We have designers, for example, now that obviously use AI to kind of come up with ideas and also to render and stuff like that. But they also now can write marketing copy for these dog toys, for example, for bar Box.
Now, the issue is of course, that that's not normally their job. It's the marketing teams job. And so you have this kind of released energy, but it's in the design team, not necessarily in the marketing team. And so we don't see like any improvement, for example, in FTE reduction because yes, you have people doing somebody else's job, but you don't necessarily have them overlaid neatly in the organizational design that we currently have.
[00:03:04] Greg Foldes: Yeah, that's that's exactly part of the problem, right? That I think that's the sort, the second stage problem. The first stage problem is I'm getting some time back, allows me to do other things. Should I do more work and make my job potentially less secure? Or should I go walk the dog and take a yoga class?
Like e every knowledge worker knows how much work they have to do each week in order to be considered a decent or good performer, or even a superstar performer, like every engineer knows how much code to write in order to be considered a good engineer. We, we, like, we all know this, whether intuitively or, or, or even sort of in direct numbers, like we all know this and so if AI can help us get that work done sooner, we're gonna use ai.
At least the ambitious of those are, and the ones that kind of configure this out. We're gonna use AI to get that job done sooner. Basically, we're, listen, remote work gave us Friday afternoons off. AI gives us Friday mornings off.
[00:03:53] Jeremy Utley: How do you think, how do organizations, is it a lost cause for organizations to
[00:03:57] Greg Foldes: try to, no, it's not a lost cause, lose those gains. No. Just be patient, you know? Be patient first of all. Second of all, don't have your CEO run around bragging about layoffs and don't have your CEO running around blaming AI for layoffs. This is such bullshit, frankly. That, that these large organizations are talking about AI layoffs already. It's not related to ai.
They overhired, their business is changing, right? They need less people in certain areas. The fact that they're blaming AI or, or, or you know, accrediting AI for the fact that they can lay off as Amazon. Did you know thousands of people in head office? No. They have too many people at Amazon Head office.
There's 325,000 people trying to optimize amazon.com. I think that's a few too many. AI is not so well adopted inside of Amazon that they can identify with precision where the layoffs are gonna be. That's just fantasy. What's going on is, yeah, they've got too many people, and certainly in some teams the team is being made more productive by ai.
But I would argue the employees keeping the gain primarily because the organization, first of all, doesn't have a point of view about ai. Like is it good to be using ai, and is it good to be stepping out of your boundaries in doing some other work? Are, are you gonna be basically messing up the organization, messing up the workflow, and so on?
So I think part of this, first of all, is sort of cultural and a concern about layoffs and a concern about how relevant will I be and how, you know, how secure is my economic livelihood. That's natural. Employees are acting rationally in this, in this moment, I think. And the second is what you said, Henry.
Like it takes a while to reorganize the workflow. It takes a while to figure out. How the team will now get stuff done and, you know, why are we expecting that to happen after a year? It's gonna take in some cases, you know, two or three years.
[00:05:43] Henrik Werdelin: I stumbled into this, uh, use case the other day that I'm now obsessed about because I think's one of the first kind of good examples of AI really taking over a, a workflow that was meant for humans.
And so the example we use is that students that are trying to get a job, they send a thousand applicants now instead of 10. It used to be effort being something that you could use to actually figure out who was the good applicant. Obviously now you have AI just reading all these applicants, and so this human to human workflow is replaced by an agent to agent workflow and therefore it doesn't work anymore.
Have you seen other examples of that? Because it, that seemed to be like such a clear one, and I would imagine that this is just the first of many that we're seeing as we're putting agents into our workflow. Then actually the workflow itself will break down.
[00:06:26] Greg Foldes: I think it, it's happening all over the place.
I mean, I think this is kind of AI work slot, right? I think, I think we're writing more marketing copy. 'cause we can, and we're writing more code because we can, and some of it's good and some of it's gonna be thrown away. We're building more, you know, automations and GPTs or, you know, Gemini gems and we probably need, and hundreds of thousands of those will just kind of fall by the wayside and not be used.
So I, I just think
[00:06:47] Henrik Werdelin: that, can I actually on one thing on that actually, do you think it's, because we think about it in the wrong way, we've kind of taken the SaaS software, I'll give you an example. A birthday, uh, last weekend, uh, I had a bunch of people coming over for dinner. I needed something to basically put all the people around the table.
Now I googled for a second of like, you know, tables, seating software, and like a thousand different things came out. I was like, oh. So I just went into web website and saying, Hey, I need this. And then wrote this thing, had a, you know, made the table plan. Had a few times where I needed something for the agent to change.
Like for example, I went from three tables to six tables and then I asked to reconfigure. I did it brilliantly right now, obviously I'll never use the software again. Likely like it's not, um, I'm not productizing it and trying to make a business out of it. So it's single
[00:07:27] Jeremy Utley: use software.
[00:07:29] Henrik Werdelin: Disposable software is composite disposable software, right?
And so we thought that SaaS soft, so we would talk about, I think last time that we were unbundling basically SaaS in the same way that the music industry unbundled the album, right? Mm-hmm. So first it became, we went from albums to singles, but now we're not even having the singles anymore. Now we're just basically writing the tunes as we need them, and then we're throwing away.
[00:07:50] Greg Foldes: Yeah, sure. Listen,
[00:07:51] Jeremy Utley: their live, their live performances. Yeah.
[00:07:53] Greg Foldes: Yeah. First of all, you're kind of a nerd, right? Uh, let, let's just be clear about that. The year writing and disposable software to figure out who should sit at, at, at dinner. How many tables was it? Was it that hard? There
[00:08:03] Henrik Werdelin: was 115 people, there was
[00:08:05] Greg Foldes: six tables and so wasn't
[00:08:06] Henrik Werdelin: Alright.
Two patrol cards. It wasn't like eight people.
[00:08:09] Greg Foldes: Okay.
[00:08:10] Henrik Werdelin: We're full
[00:08:10] Greg Foldes: people. I thought it, I thought it was Thanksgiving dinner. I'm like, in our house we just wrote little name cards and walked around and dropped 'em on the table. I don't know. No, no,
[00:08:17] Henrik Werdelin: not here. I wouldn't put put, it would've put it on me not to do that for full people.
[00:08:23] Greg Foldes: Yeah, listen, be
[00:08:24] Henrik Werdelin: asset version.
[00:08:26] Greg Foldes: That's absolutely what's going on in for that particular sort of opportunity. We also need a new mindset because we do think of it as software going through a product management life cycle. You know, we, we were at a, a dinner recently in San Francisco. We hosted a dinner recently in San Francisco, and we had a, the CIO of a major tech company.
I can't say which one at the table. And his point of view was, this is chaos for me. This idea of, you know, unleashing employees, not just to use, you know, GPT or copilot, but actually to let them build, you know, uh, custom GPTs or automations, like from his perspective. Just absolute chaos, right? Uh, disposable software like what CIR wants disposable software inside the organization running around connected to corporate data, right?
So there is so much change that has to happen. I wanna go back to the original, your first question, Eric, though, there's one last piece, phase three of this. I think when you think about, uh, sort of capturing the, the gain, what I'm also not seeing is that managers leaders of these teams, and these teams are somewhat or maybe fully AI enabled, but even if they're somewhat AI enabled.
You as a manager have an obligation, a responsibility to come up with what is the new work we're all gonna do? All we're talking about is, you know, let's go optimize everything with ai. I, I call it cut and create. Let's cut workflows and tasks and. Potentially vendors and data source. Like you can cut a lot if you are good at AI and you, but that's just
[00:09:48] Henrik Werdelin: gonna baseline, right? Like I think you said that last time that the 30% is just basically like the baseline Yeah. Of what we have to find in ebit.
[00:09:54] Greg Foldes: What about the crate? And, and, and really more importantly, like come up with more interesting and higher value work for your team to do actually get them excited about. Okay. We did cut.
Hopefully not many people, if any, but in some teams obviously that will happen. But kind of more importantly in this, in this space, we now have. In our day. Yeah. You know, as a manager come up with some good, I'm
[00:10:16] Henrik Werdelin: not sure if this is a question to you, Greg, or or to you Jeremy. I totally agree with you. We do the, all these workflow, we make them ent and suddenly we find way of getting more optimized that doesn't grow the business right.
Now we also talk about that this is AI is like electricity and not just like the internet. And so instead of just getting like an electric horse where you have to think about factories and working at night and all these kind of very kind of fund foundational, different kind of approach to work. When you're somebody who is tasked with being a manager in an organization, how the hell do you go about, even if you're the CEO, how do you go about thinking about what this future's gonna look like?
When you're basically saying that you probably have to completely redesign your organizational structure, you have to reimagine what you do as a business and all these features in between that can now be enabled through AI can become something completely different.
[00:11:05] Greg Foldes: I think the first thing a great, obviously a great question and maybe the hardest question to answer.
Particularly for incumbents, right? People have existing businesses and managers who have existing day jobs. I think the first thing you gotta do is find some time in your own day. And I think that kind of Google 80 20 rule probably works here. I think you've gotta figure out how do you run your business?
You know your team, you know your set of tasks and responsibilities in 80% of your week or something like that. And actually carve out real time to think about this and frankly, turn on your strategic chops, which I think. It's probably atrophied for a lot of people. This is something we don't probably talk enough about, but to affect this transformation that you just described, Henrik, it's not easy.
And it takes quite a bit of thinking and figuring out, you know, what should we do? And yeah, you can go hire McKenzie, I guess, but rather you don't do that.
[00:11:54] Jeremy Utley: Can I say one thing there? I I, I don't wanna slow your roll and I don't wanna detract.
[00:11:57] Greg Foldes: That's
[00:11:58] Jeremy Utley: all right. I just want to interject here that I think maybe what we have to do.
Is specify before we experience the gains that that's how we're going to use the found time. Because there's this thing, I dunno if you're familiar with, so I'm somewhat obsessed with it recently called Parkinson's Law, which is the phenomenon that work will expand or contract to fill the time we get it.
And the challenge with productivity gains is if there's not something new to fill the game time, the work just keeps expanding. Right. So I think perhaps, I mean, it's one thing I love what you said about a leader's responsibility to say what's new, but part of the challenge, as you're mentioning is they can't think of what's new.
So therefore they have to carve out the time. And it strikes me that one of the most wonderful and inspiring ways to redeploy the time that we've now gained through efficiency or that we, or the promise of time gained. Is to create the space that we've been saying we don't have. We don't have time to think strategically.
We don't. It's like, so what does that mean? Practically block the two day offsite. Block the hackathon, right? Like pre block before your team gains the productivity before they get there. 20% back. Say preemptively, here's it's not, you're not walking your dog. We're in La Jolla together as a team, right? Yeah,
[00:13:16] Greg Foldes: sure.
[00:13:17] Jeremy Utley: Yeah. You don't block that yoga class because we've got the weekly brainstorming session, right. But you have to, so I think wield the calendar as a weapon. That's my, yeah, that's my thought.
[00:13:26] Greg Foldes: Yeah. No, I love it. I listen, I, we all see it for ourselves, right? I mean, I've got focus sprints blocked on my calendar each week.
They always end up being slack and email time. You know, it's, they're so, it's so hard to protect your calendar. To your point, Jeremy, uh, that I made that p Mike, lemme ask you
[00:13:43] Henrik Werdelin: about this. 'cause you obviously think a lot about this. You are, you know, ahead on the curve of all this AI stuff. I would imagine that even for you finding the time, energy, and maybe even like team around you to say, okay, let's just wait for a second.
Let's just figure out what distance are we in? And as AI makes it easy and easier to teach people stuff, for example, then not necessarily like what do we do, but who do we serve and what is the problem that we're trying to solve for them? Do you actually find time to do that?
[00:14:16] Greg Foldes: Yeah, I'd say mostly, I mean, I, I wouldn't give ourselves or myself, you know, an a plus grade either.
It is exhausting. It reminds me of a pivot. Like I, you know, I've been an entrepreneur long enough to have done a lot of pivots, and if you've done a pivot in a business of any size, you know, for me, startups, so organizations under a hundred employees. They're hard. They're really hard, and they take a lot of mental and physical energy and resilience and so on.
It feels like that to me now. Mm-hmm. Meaning we're not necessarily, I sympathize that pivoting your business, but that level of effort to sort of rethink and maybe redirect right. May maybe pivot some part of the business, maybe the business model or the product model or the service model, you know, whatever it might be.
Yeah, I we're pretty good at it. Meaning every six months we take a hard look at are we doing the right thing and, and. What are the metrics actually showing us? And are these metrics or signals valid or we need to be more patient? And wait. I do worry sometimes that we're moving too quickly. We need a, we need more data and a little more sort of market validation.
Um, sort of yes or no kind of thing. But yeah, it, it feels like this is what we want leaders to be doing in this moment, particularly if you're in sort of deep in these industries that are so impacted, obviously by ai, language intensive, knowledge intensive, um, uh, work. Yeah, but who, I mean, average manager doesn't really wanna do this.
You know, systems it requires, wanna require, they wanna go home and feed the kids, you
[00:15:42] Henrik Werdelin: know, I think the issue is also that I, people are asking these questions as their AI questions, but very fast. They become non AI questions, they become geo point strategy questions and so there's this kinda weird vacuum where.
Everybody's like, okay, let's get more AI into the organization. And then we, you know, learn how to prompt and we start to do agentic workflows. And then I think a lot of people are like, yeah, but to what avail? Like, you know, naturally soon everybody will be able to do this, so what are we actually doing?
And then there isn't really kind like, I think a terminology of like, we're doing the AI pivot because we kind of have to, right? Or we doing
[00:16:18] Jeremy Utley: AI costs. I feel like I've gotta, I've gotta introduce this quote because I just love it. It's been something I've been thinking about a lot. I heard Simon Sinek say, who.
By the way, I largely disagree with on the topic of ai, let's just let the record reflect. I don't agree with him, but one thing I do really, I really resonated with, and I know you two will, but I think it has implications on the enterprise question. He said The difference between a startup and an enterprise is a startup's ambitions lie beyond its grasp, and an enterprise's ambitions lie within its reach.
I think we fundamentally, we have an ambition problem. The reason managers are going home is because they aren't inspired by a new vision that's so unattainable. They can't afford to go home.
[00:17:01] Greg Foldes: Yeah. Uh, first of all, I love the quote, wish I'd come up with that. And, and they're not rewarded, right? They're not incented to, to, to think that way, Jeremy.
[00:17:07] Jeremy Utley: They, they, they aren't aligned in creating that long-term value
[00:17:11] Greg Foldes: that just creates risk for them. Like whoever said, go experiment and fail. Uh, and, and sort of adopt or accept a lot of failure is inside of a large organization. No one and a startup, that's all you do. Mm-hmm. Otherwise, you don't survive. You don't.
Mm-hmm. You don't make it to the next month, right? Mm-hmm. So, yeah, I, I think the reality is for large organizations or mid-sized organizations. Something's gonna have to break for them. And it, it's usually something like your largest customer calls. This is what we're seeing and hearing. For example, in the media, kind of advertising agency, creative services, all that part of the, of industry.
What we're hearing more and more is clients saying to their vendors, their suppliers, we're gonna pre-negotiate now, by the way, like, like has happened in manufacturing for 25 years. We're gonna pre-negotiate our discounts every year. 'cause we know you're getting cost savings from ai. So we want those cost savings built into our contract.
'cause you want us to sign a three to five year contract. So we're gonna see prices drop every year, let's say by 10%. 'cause you're gonna get those gains on your side. 'cause you're gonna effectively deploy ai. That's what, for example, advertising
[00:18:14] Jeremy Utley: That's forcing
[00:18:14] Greg Foldes: Yeah, they're forcing. Right? And all of a sudden the, it's like, oh shit.
Right. Like my, my, my best customers are starting to pre-negotiate. Law firms will start to see this from their largest clients. They're gonna start to see their largest clients saying, no, we want built-in price decreases, just like General Motors has done for the last 20 years with all their, uh, you know, component suppliers.
'cause the assumption was you'll deploy automation on the manufacturing floor and, and get these advantages in terms of cost. You're gonna pass 'em on to us. 'cause we're a long-term customer. We're signing a long-term agreement so that basically supply chain behavior is coming to knowledge work. So we're, we're gonna need shocks like that.
The loss of these customers, basically, it's gotta hit the EPS. It's gotta hit the, the income statement in some way. Opportunity's not enough typically for incumbents to move. Sometimes it is, but it's more the cost, right?
[00:19:05] Jeremy Utley: Why is that? I
[00:19:06] Greg Foldes: just beyond that for for a second. Because of the risk, right? Just because.
To, to go chase that opportunity is tough. You've gotta build a team that behaves like a, an entrepreneurial team, right? Behaves like a starter. You've gotta provide capital more than you ever want
[00:19:19] Henrik Werdelin: it.
[00:19:19] Greg Foldes: Do
[00:19:19] Henrik Werdelin: you think that's just how the future is for organizations, that they need these, you know, SEAL teams rather than these omni divisions?
Yeah.
[00:19:26] Greg Foldes: Yeah, I think that's right. And even then, are you willing to stick with the SEAL team? Long enough, uh, and tolerate their failure. Look at, you know, Mary Borrower, Jenna Motors, you've probably talked about her before, like the fact that she bought crews and then poured in billions of dollars, and the thing was a dry hole, right?
It was a bust. The good news is she didn't lose her job, and I think that the worst thing. For innovation in corporate America would've been that she got fired, right? Because it would've just told every other CEO that your board won't tolerate you taking those kinds of risks, right? To me, it felt like a risk worth taking.
Meaning look at Waymo, look at zoos. This feels like it's gonna be a big business. They just didn't have the right startup, you know, in that race. You know, they backed the wrong horse that that happens sometimes, right? Obviously it happens most of the time if you're a venture capitalist. So this idea of inside innovation that's
[00:20:12] Henrik Werdelin: tough on innovation and on what you can build.
We had Dan shipper on at one point and obviously, you know, having been part of, of a kind of like spinning out that company from pre-op, um, you know, track it quite a lot. And what's interesting was Dan is doing is that he's kind of like untethered to what he makes. Right. You know, he creates software, he creates podcasts, he's a little bit, do you think that we're seeing these multimodal companies kind of emerge.
Will some of these bigger Es also need, like you are the same thing, right? You know, you do education, but you do software and you have, you know, this new thing that help you figure out what to do and it's quote unquote all over the place. Is that the new normal?
[00:20:55] Greg Foldes: I think it may be the new normal to get started, let's say.
At the same time, we're gonna need. Like the basics done well, right? You can't be playing in five different games and probably winning all of 'em at once. So I, I, I think maybe at a certain stage. The new normal is you're not bound by capability boundaries. I do think ai, 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
[00:21:30] Henrik Werdelin: IC challenge you on that specific one? Yeah. Don'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. Mm-hmm. We have endless people and we have endless time. 'cause 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, I don't know if I believe this, but like could the statement be that the issue is that we have not learned how to work like a NVIDIA processors yet? We can't have all these systems running at the same time. We used to parallel process and it's like a, for us to unlock this new technology Yes, ourselves.
[00:22:20] Greg Foldes: No, I'm agreeing with you. I'm saying that AI superpowers allow us to jump capability boundaries, but it's gonna 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 know you're not bound by your capabilities both individually and organizationally.
Like, I think what's really gonna happen is. Organizations will jump these capability boundaries, some of them faster. And so to your point, I mentioned not just
[00:22:47] Jeremy Utley: individuals. Yeah,
[00:22:48] Greg Foldes: yeah. And education can become a software company pretty much overnight. Right. A designer can become a marketer and, and, and we can all start coding even and building disposable software, like all the, there's one word for all this chaos.
[00:23:00] Jeremy Utley: Hmm.
[00:23:01] Greg Foldes: We're just entering into an era. Of extreme chaos
[00:23:05] Jeremy Utley: and organizations are designed basically to reduce risk. Reduce, reduce, reduce. Reduce variation. Reduce, reduce
[00:23:10] Greg Foldes: chaos. Manage chaos. Yeah. 'cause, 'cause the organizations are designed to deliver earnings on a quarterly basis.
Mm-hmm.
[00:23:17] Jeremy Utley: Right. Predictability.
[00:23:19] Greg Foldes: Yeah. So I wanna go back to Henrik's sort of, uh, question or hypothesis. I think it's very provocative, which is, you know, how much of this is gonna be sort of more, not serendipity, but sort of, uh, you know, managing the chaos. Not being held in place or, or not having one business or sort of not chasing just one opportunity, but maybe three.
I think that feels right to me, Henrik, but at some point I think you're gonna have to like pick one and go back to the basics of just like execute really well. Grow the business with margins, keep customers happy, you know, kick ass, take names, deliver on time. I just, the basics I, I hear sometimes as well, you know, it's, it's time to hike.
Don't be a leader, be a steward. You're stewarding the change. Yeah. Sorta, you know, but no, I think you're gonna need to lead. I think you're gonna need to, like, make decisions.
[00:24:07] Henrik Werdelin: I'm still toned though on that. I mean, like, I, I, I think all logic has always been, you know, I've done incubation for a long time Right.
As well. And you do portfolio entrepreneurship until something start 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 it may be 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 had these in the past. You know, we had these systems, AI systems that basically thought like, we kind of put a rationale tool, it's the problem. And suddenly they were like, no, we have these processors now where we literally just throw at everything. And that's what we do. And so I don't know, like I, maybe it's just because that that is how my mind works.
That,
[00:24:58] Jeremy Utley: you know what? It reminds me of Henrik. It reminds me of what Brian said to us just the other day from you that keep the GPUs full. It's a totally different paradigm. Greg. This is a early researcher at Salesforce who's now@u.com. He's one of the co-founders, but he said his whole mindset is keep the GPUs full.
And that is to, to Henry. To your point, that's like. It's a totally, it is an abundance mentality.
[00:25:22] Greg Foldes: Yeah, yeah, yeah.
[00:25:23] Jeremy Utley: But most people, most people aren't thinking like Greg. Brian told us this episode isn't released. We're kind of talking shot, 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.
[00:25:43] Henrik Werdelin: But Jeremy, for example, I'll give 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 up my like to-do list, I kinda like, I put one on one list to the other. I, it's basically in a business, a markdown note.
And then in the morning I 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 kinda like for you. And the, the craziest 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 the, it's entered 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 had attempted to be like, my day's work, right. So it's kind of fatiguing. 'cause 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, it's fatiguing, but it's super inspiring, right? Yeah. Because it's just this fire holes of productivity.
[00:26:44] Greg Foldes: Yeah. 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 return.
[00:26:55] Henrik Werdelin: You
[00:26:55] Greg Foldes: mean not
[00:26:56] Henrik Werdelin: building software for how to seat people at my Thanksgiving dinner?
[00:26:59] Jeremy Utley: Just as it As hypothetical. As hypothetical.
[00:27:02] Greg Foldes: Right. Hypothetically. Yeah. And that eventually investors want their capital back with the return. Right. Um, honestly, I think you see this tension playing out right now at Open ai.
You know, the, the Sam Altman memo that was leaked about, Hey, we're, we're code red to respond to the threat from Gemini, so maybe we shouldn't put ads into chat GPT, and instead we're gonna, you know, not yet anyway, and we'll focus on making the product better and better, better. You know, I think there is that real tension, right?
How, how much are we sort of, uh, keeping the GPUs 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 gonna ask for. You know, a return on that investment. So I, I just 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.
[00:27:49] Jeremy Utley: Okay. 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?
[00:28:11] Greg Foldes: Yeah, I actually, I actually said 10 to 50% of every organization was getting ROI, but the employee was keeping it. 'cause there's 10 to 15% of the organization that our early adopt, not 10 to
[00:28:20] Jeremy Utley: 15% of organizations.
[00:28:21] Greg Foldes: I would percent of people
[00:28:23] Jeremy Utley: everywhere.
[00:28:23] Greg Foldes: Yeah. Yeah. I would say the A grade it's probably 5% or something or less.
Like I think it's a small number of, of organizations that are actually getting. Um, you know, sustain consistent value. And our, our Okay. Research are, yeah, I think it's a small number. And our research confirms that we just finished our biannual, um, you know, AI survey, benchmark survey, and that's what the data center, uh, surveying 5,000 organizations.
So, so listen, I think what's, what, what people are doing well, if they're doing it well is, and we've talked about this before, the, it's not rocket science, but you gotta do it every day, kind of, you know, consistently, which is why are we doing AI now? Why have AI and the 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.
Some of those gpt are automations or agents will be good and we'll get benefit from them and so on. So that's sort of that. I think that building block is, is this unleashing employees, second of all, giving them great ai. Thirdly. Give everyone great ai. I still so many 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.
[00:29:47] Jeremy Utley: I was talking, no, I was talking to an organization just yesterday, like Global pharmaceutical company said, yeah, everybody has copilot. I said, is this free version or the paid? He said, well, about 10% of people have the premium version, but everybody, I said, well, is it dumb AI or smart ai?
And, and he said, well, I kid you not. He said, the problem is we wanna 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, 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, I'm literally on this call and I think I had to turn off my camera 'cause it's like my face.
[00:30:27] Greg Foldes: This is what's going on in corporate America. Right? And, and there there's cost reasons for that. Like the, like the good AI costs more money and they, 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, would you, if as a parent of two kids, would you give one kid AI and one kid not and say, Hey, both. Great question.
[00:30:55] Henrik Werdelin: We should do that an test. Do you think my sons would enjoy
[00:30:59] Greg Foldes: your own life? Yeah. On your own kid? Yeah. Good luck with that. See if you're,
[00:31:01] Jeremy Utley: what a great question. I mean, how, how, by the way, I mean seriously, everybody can relate to that.
[00:31:06] Greg Foldes: That's, would you ever do that? Like as a CEO, you think this is the right thing to do?
Give some organization good ai, like you're special. And by the way, those people with the good AI are gonna work with people who have the dumb ai. Like this is gonna be in the meeting. They're gonna figure this out. Oh, you give marketing good AI and give sales the dumb ai. Well, I think they're gonna, those teams work together all the time.
I think they're gonna figure out at some point what's going on. And you know, it's just. So what
[00:31:31] Henrik Werdelin: 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 innate N or um, rep or lovable or like something that is a little bit more meaty than your co-pilot and, yeah.
I was gonna stop by your question of the, the TV technology officer just getting panicked about this idea that somebody could sit there and code internally organization with real data. Is that an experimentation you would dare, or how, how do, what do you think about it?
[00:31:59] Greg Foldes: 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, you're kind of running outta gas with your existing sort of investments and you have employees wanting more, yeah, sure. We don't need that. You don't need to buy more ai. We routinely. Talk to prospects, uh, companies that have bought 3, 4, 5, 7, 9 different enterprise AI tools have deployed them air quotation marks, which means they turned them on and did a, you know, and a CEO email and maybe one lunch and learn, and no one's using any of it.
Like, 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, we're, we're aiming for If you wanna be a super company, which is really the only, the only companies that will attract investor capital in the next decade are super companies.
This is how super companies behave. Most super companies are startups 'cause 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, you know, there's no discrimination inside the organization. They're encouraged to use it, and they lay that very solid foundation. 'cause before giving them the tools to build agents, let them understand their workflows and which workflows can actually leverage an agent.
And, and so in, in my mind. A little bit more crawling before you run and, but listen, I, I get it. It's easy to buy software if you're a ceo. And can I just, uh,
[00:33:57] Henrik Werdelin: being of buying software, um, you had a new feature come out, which I was fascinating about, and as I understood, understand it, you are trying to solve the problem that a lot of people go, Hey, I have all these workflows in my life, but I don't really know how to make them ent.
I don't know how to add AI to it.
[00:34:12] Jeremy Utley: Sure,
[00:34:12] Henrik Werdelin: yeah. Could you walk me through a little bit, what is the diagnostics that you found out, did you do on people that come in with that problem? What solution did you codify into your system so that people might use your system, but they could also just kind of take the learning and and use it for themself?
[00:34:30] Greg Foldes: 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 use, I use GPT at home, but how should I use it at work? So this idea of, you know, use case discovery and use case coaching became so clear to us about a year ago. And so pro AI now has a new agent and it's a use case coach.
Basically pro ai, our, 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. 'cause AI is so, you know, AI is so performant and so capable. So pro AI will coach you on use cases and you can do that a couple different ways.
It'll suggest use cases to you. Pro AI will just serve up. Try this, try this. We know what, you know, we know you're a content marketer and you work for A CPG, and, and you live in Brazil, and you work in Brazil so that, you know, here are the use cases we think makes sense for you. Or you can start by just chatting with profit AI and saying, you know, what do you do every day and or what are you doing this week and what, you know, what are the tasks that you need to get done so you can clock off Friday at noon?
Uh, and so is that
[00:35:46] Henrik Werdelin: the best way to, to discover different workflows? Is that just to do a calendar mapping? I
[00:35:52] Greg Foldes: think for, 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.
Uh, but I think for a lot of people in, in larger organizations, they also wanna know what's safe.
[00:36:11] Jeremy Utley: Yeah.
[00:36:11] Greg Foldes: And so pro AI is, 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
[00:36:23] Jeremy Utley: that's, 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, I'm reminded of something you said in your first visit to the show now, uh, two years ago, which is crazy. Um, you said in regards to section generally, and I think we kinda 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. They want a product strategy.
[00:36:52] Henrik Werdelin: Mm-hmm.
[00:36:53] Jeremy Utley: I would be curious to know with the use case coach, one thing I heard you just say, so I'm, I'm curious how, 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? IE give the product strategy. And why or why not? Yeah.
[00:37:15] Greg Foldes: Yeah. Great question. It does not do the thing. So the, the use case coach and pro AI is a 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 can then cut and paste. And, and, and then go work with your ai, whichever ai you prefer, or that your, you know, 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 that, that there's too much of a lag. And so the whole point of the use case coach.
Is to get people's time to value, you know, to within hours or minutes, right? In terms of play around with these, with the profit ai, uh, agent. And you'll have three or four or five use cases immediately identified and then go, go try 'em, you know, see if it works.
[00:38:18] Jeremy Utley: Knowing what you, 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,
[00:38:31] Greg Foldes: 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. And uh, I think the more you're just doing it, you're building agents that replace humans.
And that's not our mantra.
[00:39:00] Jeremy Utley: Whereas by, it's almost one way to think about, it's almost the IKEA effect that if the person has to turn the screws themselves, they'll take it the last mile, so to speak. Mm-hmm. Yeah. One, you get enormous drop off in the last mile. So that's, which is kind of the argument against.
But the argument four is that actually becomes the means of discovery. The person who's willing to invest that last turn of the screw is gonna be way more likely to share, gonna be way more likely to enthusiastically engage. Right? Because it required part of their investment. Is that right?
[00:39:31] Greg Foldes: I think that, I think that's right and I think it, it keeps the human more relevant for longer.
I think that's a good thing. Hmm. Uh, frankly,
[00:39:37] Henrik Werdelin: can I ask you, we have this, uh, I have this thing called autos, which basically helps, uh, 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 gonna be a drop off. But you also want the entrepreneur to feel invested in this it and having to do this. And we talk, you talked about the 10% people that know how to use it and then the others.
[00:40:15] Greg Foldes: Right?
[00:40:16] Henrik Werdelin: Where are you and, and Jeremy and I had this conversation the other day. Where are you on the teachability of the 90% versus the Ironman suit that we are now handing to the 10% and. What's gonna happen? Is this gonna be a place where these people that you talk about are the new staff members that you talked about earlier, are they just gonna be those 10 percenters and then the 90 percenters right now won't learn it?
Or some of them might make right of, oh, how should we think about this dynamic?
[00:40:47] Greg Foldes: Yeah, I think, I think we should think about like, like any change that we will have people that stay on the sidelines as long as possible, right? The laggards and the. The skeptics. I think most people, you know, will wanna make the change.
I mean, they're not stupid and they'll begin to see this future and they wanna be in it. They need to pay their bills and if they work in the knowledge economy. So I, I just think that, that we are, uh, we need to be again, we need to be more patient here and be more support. We can use occasionally the stick, if you're a CEO, like if you don't make this change, you know you're not gonna have a job here.
Yeah. In some, in some places, in, in some moments that might work, but we, we have to do a lot more.
[00:41:28] Henrik Werdelin: Do you 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.
[00:41:50] Greg Foldes: Yeah,
[00:41:50] Henrik Werdelin: because you were like a, you are a catalyst, 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,
[00:41:58] Greg Foldes: I think we should be, uh, impatient, but supportive. I think we should be demanding, but supportive. Like particularly if we're in a company or industry that is in the cross airs of ai, then the, the clock is ticking.
It, it, 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, it feels like suddenly and, but more dramatically. So if you are in the crosshairs, uh, whether you're, again, you're a legal firm or a management consultant or, or you know, a data services firm, uh, you know, this is coming and, and it's probably accelerating at this point.
And then, and then when you get caught by surprise, you, you, you can have a hard time recovering. So I think as a CEO, we need to be demanding. Im patient and sort of ambitious. We need to put in the support required. 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, uh, you know, to kind of, to turn the corner on this AI thing. But, you know, we have to do it together and we have to do a relatively quickly, but we, we will support you, we will provide the coaching, we'll provide the best tools.
We'll provide the managers with the training they need to actually, you know, get their teams to be AI enabled and then use that time in a better way. And, and so a, a lot has to happen here. And again, it's just, it's just so much easier doing it with a new company, with a new organization versus, you know, applying it to an existing org.
But I think we need to be impatient, but supportive. And I think employees own this responsibility. I, I believe it's shared. We gotta 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.
[00:43:45] Henrik Werdelin: And maybe it's just that we will have to change. I, I mean, and Nicholas, my business partner, he made this point yesterday, um, 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. But when it goes wrong, you have to operate it real fast.
Right. You know, like,
[00:44:07] Jeremy Utley: mm-hmm. Mm-hmm.
[00:44:08] Henrik Werdelin: And so maybe increasingly it is okay to think of us as 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 is crazy. 'cause at this point we don't know how it's written because all these agents have been written 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. Right. And so back to the other point about thinking about scarcity versus abundance, maybe also that increasingly there will be a different modus for us humans on how we conduct our work every day.
[00:44:43] Greg Foldes: Yeah, I think that's right. But I think Henrik, the, that where we will insert ourselves is not just to catch the mistakes and solve the problems. I think it's gonna be earlier. And I think I, I want my AI to tell me. Now be human and inject your opinion and brilliance into this decision. Otherwise, Henrik, all these startups are gonna be the same.
If we're using AI to start all of our companies and do all this work, we're not gonna have any differentiation. These products and services, and so no one's gonna win. Like I, I, I'm not that bullish on AI is gonna 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.
Bring your humanity. Yeah. Bring your
[00:45:27] Jeremy Utley: humanity.
[00:45:27] Greg Foldes: Yeah. Bring a point of view that's differentiated. Otherwise we see, I mean, to your point around job searching now, there's no friction in in job searches and so people can apply for a thousand jobs and every application looks like it's personalized. That's what the data says is happening, right?
Is and that whole market's basically no longer functioning. There's so much congestion right in that system, in that marketplace of, of knowledge, work, jobs. It's basically not functioning right now. And I think we're, we'll see the same in, in entrepreneurship. If, if all these entrepreneurs are relying on AI to come up with these ideas and execute their go to market plans, we're gonna be, we're gonna have a sea of sameness.
[00:46:01] Henrik Werdelin: I agree
[00:46:01] Greg Foldes: with that. And so I want the, 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. Because you
[00:46:10] Jeremy Utley: don't, you do you buddy. You do you?
[00:46:12] Greg Foldes: Yeah. You do you. 'cause if you don't, you're gonna get, like, you're gonna get my, you know, startup ID and number 4, 9 5, you're gonna get,
[00:46:16] Jeremy Utley: you're gonna get Greg's stuff.
You're gonna get Greg's stuff if you aren't, unless you interject right now.
[00:46:21] Greg Foldes: Right. And I gave this business idea to a thousand other people last night,
[00:46:25] Jeremy Utley: Uhhuh,
[00:46:25] Greg Foldes: you know, because they're all using AI because. So I, you know, that, that, that's what I'm hopeful or that's what I want from ai. I want, Hey, uh, I'll do, I'll do a lot of heavy lifting, but we need some brilliance here.
We need some human brilliance. Uh, like what's the pricing gonna be of this product or service? Uh, if a light I do, we'll have all the same prices.
[00:46:45] Jeremy Utley: We've gotta hear your, uh, short details on how folks can try out pro ai. So I think we've kinda 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?
[00:46:58] Greg Foldes: Yeah. Go, go to prof, AI and the consumer version is free. If you want up your team, then you gotta, you gotta call me and we'll charge you for it. Uh, 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, uh, there's no charge for consumers. Uh, companies pay.
We just announced our agreement with OpenAI, or we're about to announce our agreement with OpenAI this week. So we're one of their service partners to help, uh, their enterprise clients drive higher levels of adoption with TPT Enterprise. You guys,
[00:47:32] Henrik Werdelin: well done.
[00:47:33] Greg Foldes: Yeah, it's it. But you know, I think, I think we're all seeing the same challenge, which these technologies are offer so much upside, but the anxiety and the skills.
Where they, you know, anxiety's too high and skills are too low to actually take advantage of these capabilities. Uh, as we've talked about before, this is not software. AI is not software. And when it's deployed like software, it fails. 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 gotta really do this differently if it's gonna work.
[00:48:07] Henrik Werdelin: Brought it home.
[00:48:09] Jeremy Utley: I mean, what a, what a treat to have the first threepeat in Greg shove. I mean, of all people we've talked to, he's a worthy three Peter. Right?
[00:48:18] Henrik Werdelin: He's such an interesting person. You know what I mean? I think a lot of us, we, 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.
I mean, they're like, well, you know, what does work? What doesn't work?
[00:48:32] Jeremy Utley: We've touched the orb. Yeah. Right. Yeah.
[00:48:36] Henrik Werdelin: I think we all, like, I think this is all this raise for the holy grail of figuring it out. How do we best take this new technology and put it to good use and, and we all just trying all these different ways and so, I mean, for me, I'm very energized talking to a person like him.
[00:48:52] Jeremy Utley: Definitely comrades in arms, that's for sure. I thought I'm just rattling through a bunch of stuff 'cause 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 of any guest, 'cause Greg just has so much experience, he has so much exposure across so many 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 gonna give any access at all to, and it's, so, I, 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 prodigy are, they're gonna know if, if one department has dumb ai, they know it. Yeah. And that will create a class system in the organization. And furthermore, you're, 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, the cumulative outputs I don't think are going to rise to the level of the smart ai. I think they're gonna be, they're gonna fall to the level of the dumb ai. What do you think? Yeah,
[00:50:10] Henrik Werdelin: I, I think that's true. I think, and I think the other thing that he pointed out that resonated with me is.
10, 15% of everybody in the organization are pretty good at it, and they the kind of super users. And, 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 thing. What they need to learn is how to do their job better with ai, right?
Mm-hmm. And so they're looking. To not kind of go from the abstract understanding of how do you use this tool in a generic way and then apply myself to my job, they almost need much more specific to say, Hey, 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, you know, train on that. And so I think a lot of us, you know, we, we want to give people a fishing rod and teach them to fish generically. But I think maybe an unlock for a lot of organization is that you just gotta go much more specific, right? I say as a statement, what I mean as a question
[00:51:15] Jeremy Utley: start to do this here.
Yeah. Yeah. I think that's right. And I really like your comment. I don't know if you realize you were 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, 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. The end is actually doing whatever you do better.
[00:51:56] Henrik Werdelin: 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? Mm-hmm. Where does that go? And you were talking about the Parkinson, was that the Parkinson? Yeah,
[00:52:16] Jeremy Utley: Parkinson's law. I mean, to me it was very pointed when you said, what you ask your bark team. That's incredible. That's evidence right there of Parkinson's law.
I don't know if it's Parkinson's law necessarily, but to me that was a great story. But anyway, you were saying about Parkinson's law priest.
[00:52:29] Henrik Werdelin: Yeah, 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 hard 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. Yeah. 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, more robust organization, one that grows faster.
[00:53:07] Jeremy Utley: Well, 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. Hmm. You know, I like what he said about cut versus create, and you think about cutting as it's six sigma, it's process.
Standardization and folks will, that's a kind of a known area. Um, 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 seventies. Organizations 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 kinda classic line. He says, the organization that. Only exploits, generally suffers obsolescence is to say they go bankrupt. Right? But it's really hard. I mean, that's where ambit maybe, you know, a a, 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 and the Dexterity.
I mean, it's the kind of the quote unquote solution to the innovators dilemma, so to speak. 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 be 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.
[00:55:17] Henrik Werdelin: I 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 mix basically the factory work. All this factory work that people have been doing can increasingly be done with agent. And so what is left? And that is the exploration, but the exploration doesn't really have a rule book.
I, I realize there's innovation experts like yourself, but most of the time that's not what most of the organizations spend any time on. But now, right. Maybe they can,
[00:55:56] Jeremy Utley: maybe they
[00:55:57] Henrik Werdelin: should. You
[00:55:57] Jeremy Utley: and maybe you need to, you don't. I mean, it, it's a race to the bottom, right? Yeah. You can only exploit, become more, so much more efficient.
Yeah. 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. Yeah. And so if your expertise is trimming the fat, eventually that's, you're putting yourself out of business. I, I would be remiss if we didn't also mention one of the other things Greg mentioned to us, his emphasis on manifestos.
Mm-hmm. Um, he mentioned, you know, super companies. I, 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, 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, I about share, replicated. I had a, a similar retreat among a bunch of CFOs and COOs. And 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 gene? AI powered transformation?
And two of those elements are relevant to this conversation. One is, has the CEO written in AI manifesto and two, has the organization established clear governance guidelines regarding use? Okay. Mm-hmm. 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.
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, I mean I lovingly lightheartedly make fun of it. I'm 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 stalling out? Yeah, no, it's
good.
[00:58:08] Henrik Werdelin: It's a little bit of the micro version of the same picture, which is, you know, we know how to explore it. We don't know how to explore.
[00:58:16] Jeremy Utley: Mm-hmm.
[00:58:16] Henrik Werdelin: Right. And that is going to be such a important part of living in an AI world where exploitation becomes cheaper and cheaper because the machines are very good at doing machine type work.
Hmm. I think as always, if people have listened to the whole conversation with Craig, uh, we hope they'll share, uh, this episode with somebody else.
[00:58:39] Jeremy Utley: 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 gonna, I'm not gonna spoiler it. There is something you can do immediately and it's not used profit AI though. Go check it out for sure. I'm not, 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.
[00:59:09] Henrik Werdelin: And with
[00:59:10] Jeremy Utley: that, we're that.
[00:59:11] Henrik Werdelin: Bye-bye.
[00:59:11] Jeremy Utley: Bye-bye.