Why Are We Still Organizing Like It's 1850s?

By this point, I feel that we've all kind of figured out that the problem with AI implementation isn't really technical. It's more organizational. The hard part is getting your organization to actually unlock the real potential value in ai. And here I'm not talking about slapping AI onto some legacy process to get some 10% efficiency gain that will be just priced into the market in six months.

Jonathan Brill, welcome.

It's amazing to be here.

For those who don't know your work, can you kind of elaborate?

So, my name is Jonathan Brill. I am a business futurist. I do a lot of keynote speaking. I write books, uh, and I advise C-Suites and, um, security services around the world. My job is to help you understand what is that world that you're gonna be operating in five years from now?

Your latest book, the Octopus Organization, you begin with an extinction event 66 million years ago, and, and you're not the first innovator that I've, uh, spoken to.

So I recently wrote a book called the AI and the Octopus Organization with someone named Steve Wonker.

Yeah, that's interesting. And you can quite clearly see kind of the link to, to the industrial age organization being very much top down.

Yeah, so we've been organizing businesses the same way since the 1850s. The first organizational chart was printed in 1855 by the New York and Erie Railroad, and there were several assumptions in 1855 that AI makes untrue.

Yeah.

Well, we've been talking about it, right? We've been talking about it for 20 years in academia. We've been showing the potential of these things. We've been talking about how to build psychologically safe organizations so that everybody can be more innovative.

Why is

. If you go back 25 years, you know, we had strategy and then we had execution. We had freeze of thaw. Last 25 years, it's been about this idea of strategy execution. We do both at the same time. Hmm. In a world where your person can do what would be three days of work today in 45 minutes.

Is strategy obsolete or, or what? What is the definition of strategy in that world?

Well,

Okay. Capabilities,

almost the capabilities that you can reorganize. And how do you think through that ability to reorganize the structure?

How does this look in practice? I say that we fundamentally run a very fluid innovation focused distri distributed in decision power organization.

So, uh, when you think about the middle manager today, the primary role is quality assurance, right? And process control. I think that continues, but it's a very different situation where it's not about so much designing the processes as dealing, uh, with the edge cases, right?

And how do you achieve it? What, what's the, what's the everyday work day of, um, middle manager of the future?

Sure. I, I think it is making, like I said, you know, making sure that those edge cases get bubbled up. I think they have a lot more, uh. They're dealing with a lot more process complexity, you know?

Yeah. It's fundamentally interesting. So if we assume that the employee level has to intelligence of a genius, that role changes a lot. Uh, and the capabilities of that role, and especially if you provide a lot of context as you said, I think one of the things that's interesting with strategy is, is how can we leverage our.

I think it's probably different for, for every organization.

Yeah. You talked about a, a rapid sensing system in the book.

One of the reasons why senior management holds on to control is because middle management doesn't pass the information through.

If you've been listening to this podcast for some time, you know what I think about ai. I'm deeply excited about it, but I also see companies struggle with it, and you know that I think it's not primarily due to technical reasons compared to. Previous revolutions, let's call it the internet wave. Part of why we struggled initiative initially was that, well, the infrastructure wasn't built out.

It's, it's a, it's a bit of a challenge to say, but, you know, I think there's this conversation about, well, AI hasn't paid out. Yeah, exactly. 95% of pilots, et cetera, et cetera. Yeah. Yeah. But, but like a, that study that we're talking about from MIT, there's, there's methodological issues with it.

It's also exciting because it makes, fundamentally what are, what are the problems that we could tackle? Because I see a lot of, of companies mostly slapping AI onto existing legacy processes and, and win some five, 10% productivity gain within a specific department. But you fundamentally do the same thing that you did yesterday, just more efficiently.

Yeah. And I, I think that's the, the, the fascinating thing that, you know. We're gonna see, I think at the back half of 20, 26, some, some economic value. There's gonna be, not, not like Klarna goes out there and has some edge case, like we're getting all ai, but, but like larger organizations start to see some success.

I met them when I was in San Francisco when I was trying to have this conversation live with you when you ended up going to Mexico. But, uh, yeah, it's super exciting. They fundamentally play a different game, but it's also interesting because they've built it from the ground up in this new logic, like most of, at least this audience that we're speaking to are not in that position.

And, and this is the challenge, right? Yeah. Is it's, is it's a, it's a heart transplant.

Nobody who's gone through the transformation of bringing on SAP

and they're like, you're being conservative. Um, the shift of a culture though, there are people like Benham Re who say, Hey, you can do this in 90 days or six months. My experience has been that you need to. Raise up or put out every single leader in the organization.

Hmm. What's the first step? Say, say that you are the, the CEO of a, a mid-market company to billion dollar revenue. What are the, the steps that you actually begin with?

I, I think, like I said, it, it starts with the culture side and in the economy we've kind of come up with a number of things that, that innovative organizations tend to do more of. We did a study of 2.7 million managers, million about why some are more lucky and times have changed than others. Mm-hmm. It turns out it's not chance.

There's an interesting opportunity to develop if you're a, a leadership training kind or if you're a large company, to develop your own kind of training agents for this.

Yeah. I, I think it's the only way to do it because the reality, you know, the reason, one of the reasons why we don't superpower.

It's funny, this idea actually came from, I have a sales director friend, he came up with this original idea based on the concept. I want to be less in meetings, but how can I kind of provide the value that I would normally do in a meeting, but more automated?

Right. Well, when I was a middle manager, I was spending 65% of my time in alignment meetings. Yeah. And like that's, just think about that. It wasn't even my, my job description.

Hmm.

Absolutely.

What do you see the, the kind of big consultancy firms, obviously they're building up massive AI transformation offices and so forth, uh, the, the McKinsey and so forth, what are they doing right at this moment and, and what's kind of missing in the market?

I, I think it's about, you know, the first thing is the culture change, right? Yeah's, a piece that you can do yourself is the piece that requires someone to come in from the outside.

Yeah, I think it's a continuing patterns. What we saw, I feel a lot around the digital transformations is that you approach it as a technical problem. Where it's fundamentally mostly a human problem, and it's just an amplified effect. Now with ai, I see the same thing.

Yeah. I, I think that's, that's absolutely, uh, absolutely right. This isn't a technological problem, it's a sociological problem.

I completely agree. And if we assume it's correct, and I, I completely agree with that. I think it's correct. It's a human problem.

Yeah. And I, I think it, and, and what, like you said, like what role do you play?

Yeah. I, I've talked to innovators in the past that, that has brought up an interesting kind of intersection between the value of play and innovation. Have you looked at this?

Tell, tell me more.

So, uh, the, the core idea is that.

I, I, I completely agree with everything you're saying, and it, it's, as a manager, it's really easy to, to look at like, okay, well how do we make sure that all of this experimentation rolls up into anything bigger?

It was so Russian. Interesting. Russian,

So this, there's this, uh, Russian, um, Russian, uh, engineer, I think mathematician engineer who came up with this, that he, he basically came up with every way to have a new idea and, and like every pattern for solving problems.

Yeah. And that's, and that's so interesting. I, I read that in your book and I, I highlighted it when I read it through, because that's really at the epicenter, what I tend to do with my AI anyway, help me work, work through problems and so forth.

For, for me, that's been really powerful. The other thing is to ask it to look for metaphors or similar things in deep history, right? Mm-hmm. I want, how, how is this, how, how is situations like this played out, uh, in the Ottoman Empire, right? Like, because there's, there's all of that knowledge is there.

Yeah, I agree. Uh, who are do you think gonna be the real winners from a financial perspective of within the coming five years, let's say, is it gonna be the opening eyes and the, and the Claudes and or philanthropics, or is it more the, your average company?

So I think everyone's gonna have to play the game and I don't know, because the transformation's gonna be so quick that you gain massive strategic advantage. Right? I think it'll be highly tactical advantage in many cases. Um, the. In terms of like, does open AI ever make money?

I think the research lab analogy, because one thing that's really interesting is that we have started to see junior roles not necessarily disappearing, but not being recruited that much because that's the first level stuff that's easy to automate.

Well, look, the people think is easy to automate. We'll see if it's.

It's easy to automate the, the what, 80% of, of the time where you don't have an exception and the other staff can do the exceptions. I think it's the primary bet, and you still do the exceptions through some type of human in the loop, uh, uh, design.

they, they fill a creative role, right? So they're, they're, they're having new and different ideas in a lot of cases. It depends on the type of laboratory. Um, but you know, a lot of times their job is to, to have the crazy ideas because they don't understand what won't work.

Oh, okay.

And that's highly valuable in a world where new things will work every week because new technology Yeah.

Yeah. That's super interesting. And if we go to the other side of the spectrum, could we argue that the, the old Grisled experienced, uh, executives that we expect them more to, to. Move towards almost like being the guardians of the wisdom, being guardians of values and long-term thinking and so forth. Or is that not a, a argument to make?

I think that they need to open up the innovation, you know, they need to make possible. Um, I, I, I do think that I, you know, I'm certainly starting to be of an age where I'm the, the gristle one. So I, I have, uh, I have an interest in this argument. Uh, but, you know, I think that the, the most effective innovation executives, right there are people like Mickey McManus, who, who I really enjoy.

have

you tried that? It sounds interesting.

How do you personally work with your, uh, shots? Like, what are the things that you find yourself coming back to? A lot.

there, there are a couple of things, right? One, one, we have this tool called Deep Invent that, uh, helps it's, we're automating the research lab. And what we, what it does is it has a conversation with you. It helps you identify the, the, the shape of that invention that you're interested in. Market opportunities, collaborators looks at all of the, the intellectual property that's ever been filed, all the scientific literature that's been written, and then says, Hey, here are 10 ideas.

What's the role of patents moving forward?

The, in the US you know, the concepts, you know, and this is where, where things break down, right? The concept is that it's not about sweat of the brow, it's about, it's about the quality of the, and that's what we, what we patent for.

You would assume that there's, I'm, I'm almost exclusively speaking about like moral issues here. Not really the practicality, but you would then. Almost want to force you to do something about it, because we don't want to create pockets of innovation that are protected by patents, but are not realized because we have so many ideas and we can patent so easily.

Hmm. Well, it is still effort that goes into realizing it, that the issue is, we, we have a concept called first to file. Okay? So the first person to file intellectual property has priority on it. That doesn't mean you pursue it later stages in the patent process, get more expenses. Um, but it gives you, it gives you something to, to, to, to stake a claim in if you wanna go further.

But I would assume that the patent offenses would be really good customers for deep invent as well, but just from applied from, from the other direction.

Ah, yes, indeed.

That's fantastic. Part of the, absolutely. Part of the game plan. What excites you the most if you're looking into the next, let's say two years? Let,

I, I think this is a slightly different shift, but I think it's what's happening around AI, across Asia. Okay. That, you know, US and Europe, we have this US Europe perspective, right? But what's actually happening on the. Size of the US European middle class is like increasing by 50% in the next decade or so, and that's not happening in Italy and it's not happening in California.

Hmm. I know that Mo Gda, the, uh, the ex-chief Google X officers wrote a lot about AI as well. He, he has this mental image of, in a few years time, where we're, uh, at a beach somewhere, uh, either hiding from the robots or, or completely set free by the robots.

Slower than everybody says and faster than we can imagine. Hmm. Um, I think, you know, foundationally

Yeah.

I think that is our moral obligation as a species. Uh, and AI is the single best tool we have to find efficiencies in every business process, every production process, every service process on the planet.

It's interesting 'cause we're only really talking about AI a lot right now, but we also have this convergence of a lot of other technologies that are equally potentially impactful if we talk about new sources of energy.

Yeah, that's a big question. Um, I mean, I, I think there are two questions within that. One is, what are the rich world problems? And, you know, precision medicine, blah, blah, blah, blah, blah. Very exciting. On the other hand, I think it's, there's one brain surgeon for every 400,000 Indians, 4 million Indians like that.

Yeah. I had an interesting conversation with, um, uh, an AI professor here in Sweden talking about AI doesn't work that well yet in, uh. Research settings because it's a lot about correlations, but you're looking for causations.

So we've been working on artificial intelligence tools for 75 years now, something like that, right? 1956, um, was I think whether we coined the term, uh, my point being that there's a whole range of what's called symbolic reasoning, which is kinda left brain ai. So this is stuff where A always goes to B, B always goes to C If you were around in the nineties, we call them expert systems.

Yeah. How can you actually start simulating outcomes That's really interesting and getting high precision in simulation work. Uh, I don't think people really understand the concept of let's do that a million times. Just in a a, I heard like half a year ago or something like that. Just in a marketing example, what if you fundamentally could ask every single one of your customer, but they're just simulated when you're building up your new marketing campaign?

And, and this comes down to that conversation we were having at the beginning about like, what would you do if you had, you know, we, we were, I think we were talking about this before, like what would you do if you had an infinite amount of labor or an infinite amount of choices, or an infinite amount of time?

Right. I think it's such a fundamentally great way of looking at this. So I have conversations very much more practical than, than this conversation that we're having today. Like what's the first, uh, custom DPTs that I should build, like that, that type of entry level into DPT.

Mm-hmm. Mm-hmm. What did you discover?

So for me, um, so I was looking at my role as a leader. So what would be the support staff that I would love as a leader? So I found that I would love a management consultant around me that was constantly monitoring the external environment that was quality and improver of plans that I laid.

I want that.

Yeah. And it's not that difficult either, uh, to be that, that that's what's interesting right now. Again, the problem is not technological at this point.

No, it's not. It's, it's having the idea that I don't need to do that work anymore.

Yeah, exactly. And I think compared to when the internet wave came, like, I think part of the reason why we saw that play out and we had a, a few bubbles and so forth along the way, was there, there was so much infrastructure that wasn't fundamentally in place for an Amazon to work in the early stages of the internet revolution, because we didn't have smooth online payments, for example.

It's just we're moving into such a wild time, you know?

Yeah. A hundred percent. So interesting. One of the things that I've found is that when we talk about I want to optimize for things that I enjoy. I really enjoy asking questions and being curious. So that was part of the design. Like, I really love iterating with my ais or, or whatnots, and I think it's super dangerous if you're walking down the path of, of trying to automate your own thinking.

I, I, I think that there's this idea, like the thing that strikes me, and you may be in a slightly younger generation, but the thing that strikes me is as an inventor growing up, probably the most critical component was boredom.

Yeah. And the ways that we look at productivity and measure productivity is also pretty part of the problem. You measure it by, you can see that people are online on Slack, which is probably the worst way of looking at productivity, but I see a lot of companies being very stingy about that.

Yeah. And, and I think it's, it's also, you know, are you looking for base hits or home runs?

Yeah. Do you reflect on, coming back to the point that we were talking about before with mental friction, do you design and optimize your life for those periods of boredom?

Yeah. I mean, I, I, I have a, I'm, I'm today on, on a workation in, in Spain and yeah. Just making, you know, I'm hanging out with a buddy and making, you know, making time to really think about my business and think about what, what I need to do in the next year. Like, why in, in a world of such rapid growth, we, that's the most important thing Yeah, that's right.

Yeah. Taking that step back. I completely agree. And so can be, were very difficult to, to get there in, in the kind of business of all things. Right. You need to, to consciously make those choices.

Yeah. You, you can't, like you, you were saying earlier, you know, this strategy go away.

No, that's fascinating. Thank you so much, Jonathan, for, for taking the time. This has been a really interesting conversation to me.

The same to me. Thank you very much,

There we're at the end of the episode. I think it's so amazing that almost 70% of you actually listen to the end of the episodes, especially for long format. I'm, I'm so thankful for that. Like the engagement numbers is fantastic. Before we leave each other, two things, first off. This episode was sponsored by Grail and I'll make no secret about Grail is the company that I'm starting.