From SCratch #264 AI is not the transformation, learning is [00:00:00] From scratch, from scratch. From scratch, from scratch. From scraaaatch Welcome to the From Scratch podcast. I'm Martin Couzins, and... My name is Nigel Paine. Now, if I had a drum and I could play it, I would do a drum roll. But we don't have that, so- We don't ... Nigel, you just before we came on air, you just shared a statement and I, and we both then suddenly thought, "That would be a good way to kick off this episode." So what's the statement? S- the statement..., we don't have any special effects, Martin. I think we're very s- low on the special effects front., The statement is, "AI is not the transformation, learning is." In other words, if you really want to build great organizations for the future and for coping with all the change, [00:01:00] it's fundamentally building learning organizations. AI informs it, underpins it, supports it, whatever, but the transformation is actually in the building of learning networks, learning communities and, my little obsession, the learning brain. That was, uh, the simple point that, I wanted to make. Something, I'd written for Norway. What do you think? Do you agree? Yeah, so it's funny because I consider... And this is all kind of forming in my mind. I, I really like that, and I was thinking of AI as really, a lever for cultural change in organizations. It's not... I think what you're saying there is,, AI's, we're missing the point if we're just focusing on the technology, right? Exactly. It's- Yes ... and, and I think actually it's a technology that's gonna have far greater impact than previous digital [00:02:00] transformations that we've gone through over the last 20 years, yeah? Yes. I think it... , And I think that's the point, isn't it? It's it's... It... , what does it really represent to organizations and to individuals? What does it really mean? And if you work that through, what's the, the, the most useful lens to look at what the implications would be and what that, what we have to do as a, a, a response. And for me, it just feels like it's a catalyst for innovation, which is learning. Yes. And, and we can't really harness this unless you have a very broad perspective on where, what this technology could do. And- Yeah ... start to then get our hands dirty, and experiment, and really- go with that, and explore it because we have to have the exploration before we land on the thing that's going to really work in our organizations, I would have thought. So it makes, , total sense to me [00:03:00] It... And if we don't do that,, then we're missing the chance for transformation. All we'll be doing is the same things faster or the same things with fewer people. We won't actually be building and developing the organization. And that's, to me, that's really important because you need organizations that are fit for purpose , in the coming world. And doing the same thing by adding in AI, is absolutely not going to help ultimately deliver the productivity, the change, the innovation that we need. And AI doesn't deliver innovation. And AI helps us towards solving problems, but it's the acceptance of the problem a- and the delivery of the solution which makes the difference. And that is- Yeah ... more pe- more people centered for the most part. Not entirely, but more people centered, I would say. Yeah. I think what's interesting, I... And I need to be able to [00:04:00] reference this, but I saw some, one... I saw some discussions and that this could be right or wrong, right? So but I'm... The... I saw something that was talking about the fact that,, if you just use AI to do what you would do more efficiently, there are certain gains to be had from doing that, but they're limited. Yeah. And you get greater gains from what else you do outside of that. And what else you do outside of that is the new stuff, right? Yes. Yes. And that is the learning bit. Is that the... , that's the space that you're talking about. And I think that's quite... That's really interesting because,, at that point then you need to have, , great leadership and a kind of set out, set of principles and a vision that says we're actually really interested in that bit. We're... Yes, we've got... , you've got tools that can make things more efficient, but actually the r- the real change for us in the [00:05:00] organization is gonna come from what we do new or that's new and different. And actually, how do we enable that to happen in the organization? , What kind of leadership do we have for that? What kind of- Exactly ... , mindset do we need? What, you know- Exactly ... how do we need people to be, thinking and what moti- , what would the motivators be for people to want to do something new , and what does that look like in terms of with being rewarded, and what does that look like in terms of, the culture within teams? And also, what does that mean for skills? , It... That- Seems to me to be the challenge right now. Not, the tech- you know, just looking at the technology to, to basically make things that we've always done more efficient. I think that's one small part of it. I think it's actually the other stuff that you're gonna do that's new. And that's where the learning bit comes. Yeah. I [00:06:00] think that's right. Uh, and I just, it... just think humans have to stay in control because they will look forward, they will shape, but they need data, they need ideas, they need processing. All sorts of different skill sets to manage that, those processes that can be delivered by AI. And a data-driven future doesn't mean that there's, there's no humans involved. It's all about focusing on that world that we're trying to build with the agency a- and the support of, of different tools, one of which is AI. So, and my prediction is that AI will cease to be hugely visible. It will disappear into , the toolbox, basically. It'll be just one other thing. And remember , when... I remember, you won't, Martin, when IT personal computing started to be manifest in organizations. And it was all anyone talked about. "Oh, we've [00:07:00] got this number of word processors. We've got all these machines, and got all this linked to this number of printers. It's amazing. We can pass documents around." And then all of a sudden it went incredibly silent because that became the way we work. And I haven't heard anyone say, "This is miraculous. I, I've got Microsoft Word on my laptop, and I can share a file with the person next door, or even in the next, in, in the next country." No one cares. And I think AI will just be in the background doing the work, and we'll all be familiar with it. And the real innovation, the real issues, will be in the discussions and the views and the analysis and w- what we pull together as human beings. And, it's fascinating, and it's a really important discussion, I think. And now my final point would be actually for all the technology that we've had over the last 20 to 30 years, we still have a product... We still talk about productivity problems and challenges, right? Yes. [00:08:00] That people don't have enough time in the day to do the work., The technology has promised to fix those problems for 20-plus years, right? Yes. And we have, and we ha- and it hasn't. So my caution in all of this excitement and hype is, will it? Will it make working life better for us? It could. It, yeah- But it won't do it on its own. - But that's always been the promise of technology, right? And it hasn't so far. So- That will be interesting because I think- Very that's something else we need to consider. When we look at all this, what new stuff, you know, how will it help people with their wellbeing? How will it give jobs that have more meaning? How will it connect people to their communities to the bigger issues of sustainability? How will... Exactly how is all that going to work? Because that stuff really matters.- It does ... we need to really ground our thinking and our approach in all of that [00:09:00] as well, not just, "Oh, it's AI, it can do this. Isn't it great?" Yeah. Because we could end up with exactly the same problems we've already got with technology that we might- But coming faster. Coming at us faster. Well, exactly, and that causes problems, you know- It does ... even more problems, and it's stressful. So- This is a, big topic for next discussion maybe, Martin. Yeah. Just, how you can leverage AI to be more, to build a more human-centered organization. Yeah. And, I think you can, but we need to talk about it. So let's do that next time, Martin- Yeah ... and call it a day today. Yes. I enjoyed that, so that's definitely a chewing over a provocation that we hadn't really thought about until 10 seconds before we started. So I enjoyed that. This is true. I hope our listeners found that- Yeah ..., Interesting. Don't give away all our secrets, Martin. Always always good to talk. Thanks, Nigel. From scratch