#194 – GST XX: High Tech, High Touch w/ Professor Julian Birkinshaw

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Full episode transcript: 

​Please note that transcription is done by AI and may contain errors.

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George: Hi everyone. George here, the editor of the Sales Transformation Podcast. This week we have a recording of another talk from Global Sales Transformation 20 for You. And this time it's from Professor Julian Birkinshaw, Anyone who's been through Consalia's executive master's program will be familiar with Julian.

He's authored 16 books and 130 articles, and many of them have appeared on our reading list for students. Julian is an expert on topics like innovation, digital transformation, and strategic agility. And in his GST Talk he discussed how large companies can adapt to the new AI powered world and why you might not need to panic quite so much as you've been led to believe.

as always, there are slides used in this talk, so you can head over to the Consalia YouTube channel if you want to see the visual elements. With that said, please enjoy Professor Julian Birkinshaw's presentation.

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Phil: Right. So the final, uh, session before we take a break is, um, is, uh,

to welcome Professor Julian Birkinshaw, um, to us. Hi, Julian.

Julian: Hi there. Can you hear me okay?

Phil: Yeah, we can. Uh, Julian, I don't think you realize, um, how well known you are to this group. Yeah, we did an exercise.

Julian: I did not realize that.

Phil: Yeah. Yeah.

We did an exercise early on to see how many people in the group, we've got, quite a few master students had cited you, uh, in their work. Okay. So you've been well cited by a lot of people in the audience, so they're really looking forward to your presentation. Uh, so Jillian, I think over to you.

Julian: Thank you very much, Philip.

Um, and it's a great pleasure to be with you. I wish I were there in person, but I'm, I'm currently in London, Ontario. Most of you haven't even heard of London, Ontario. It's a, it has its own River Thames. It has its own Oxford Street. It's a, a miniature version of the one that you are all in. Um, and I, I retain a dual affiliation.

I, I'm still affiliated with London Business School, but I'm also the dean of the Ivy Business School. In Canada. Um, and this is where I did my PhD all those years ago. So, uh, I have a split allegiance these days. I've been listening into the last couple of presentations, and you're gonna hear some common themes from what I say, but.

I also want to position my remarks on a, on a broader template. Um, and I want to kind of take a little bit of a step back. We're gonna get back to generative ai. Uh, every conference going on in the world today eventually talks about ai, but I want to, to, to take my comments, um, in the following way. Um. The narrative that we hear in the business world today of, uh, you might talk about the, uh, the magnificent seven, or the hyperscalers, the big Googles and Amazons and, and, and Facebooks.

Uh, you might talk about unicorns. You see the, the beautiful AI generated image of the unicorn there. Um, in this narrative, we have unicorns and hyperscalers that are dominating the business landscape, and they are. Essentially making life extremely difficult for old, traditional, established companies who are, as the image suggests, uh, going the way of the dinosaurs.

That's the narrative that we hear about. Uh, and people will cite Nokia and Kodak and Blockbuster as like evidence that big established companies are being killed off. But it's, it's more complicated than that. It is much more nuanced than that. Here's a. A quick quote. Uh, there's ample evidence that today's technologies will tear apart banking as we know it and create an entirely new financial system that could have been written yesterday.

It could have been written when the blockchain first came out. It was actually written, uh, 30 years ago, almost 30 years ago, uh, when the internet first emerged. And, you know, most of you in the room were absolutely were. Be old enough to remember the internet revolution. Uh, and it was absolutely phenomenal in terms of the changes it made to the world.

But I use this quote to, to remind us of a couple of things. One is that we've had big technology revolutions before and. Always those revolutions made some things change, but a lot of things actually stayed the same, and we won't have time to kind of debate this question. Did the internet revolution actually tear apart banking?

My view is it did not tear apart banking. What it did was it changed the experience and indeed the efficiency of banking for particularly for, you know, you and I as users of those services. Um, particularly in things like international payments, it has been genuinely transformed. But if you say to yourself was the kind of fabric of traditional banking companies torn apart.

I would say, no, it wasn't. Uh, the same big five or six banks today in the UK are exactly the same ones. They sometimes they change their badging a bit, uh, as 30 years ago, uh, the business model of banking has not changed. They still make money, lending money and selling money. I mean, there's a, the basic spread between buying and selling of money is how they make money.

And the regulatory system, of course, has ensured that we haven't actually seen huge changes. To who's allowed to actually do banking. Now, you might say that that's going to change. My point is, is very simple, which is that the, the amount of change we anticipate whenever there's a big generation, uh, technological revolution is often overstated.

And just to put a little bit of sub. Behind that. Um, I'd often, I won't have time today and perhaps the fact that I'm not in the room makes it really difficult anyway. But, um, there's a little quiz I will often do with an audience and it's to do with what's happened since the internet took off. The internet took off roughly 30 years ago, and I will ask my audience, if you take today's Fortune 500 list.

So this is the US companies the biggest in the world by sales revenue. And you say to yourself, how many of those companies actually did not exist at all in 1995? So if the kind of unicorns and dinosaurs metaphor were true, we would see huge numbers of unicorns coming through having not existed 30 years ago and be a big part of the business landscape.

So when I ask this question, by all means make a mental sort of note to yourself of the number you've got in mind. Typically, when I do this exercise, people will say, maybe it's 100, maybe it's 200. Uh, did not exist. The true answer is only 27 of these companies on the list today did not exist 30 years ago.

And as I say, that's a surprise. To most people, uh, the chart on the, the right shows exactly how to break it down. I mean, about 200 of them have been around, you know, forever. Uh, this is the Forge, the boxer and gambles the, you know, the, uh, the Citi Banks and so forth. There's a bunch of spinouts and there's a bunch who've been gradually promoted up through the ranks, but have been around for much more than 30 years.

You've only got 27 companies. On that list that really didn't exist at all 30 years ago. And these, of course, the point is these are the companies that we talk about, the Facebooks, the Teslas, the Googles. The sales forces and so forth, they are big. They are growing massively. They are taking a disproportionate share of the new opportunities.

All of that is true, but the other 440 to 473 companies on the Fortune 500 have all been around, uh, preexisting the internet revolution. They have found ways. Of adapting. So this is my first big point. Uh, many of you work in big established companies. Many of you feel you are, you are a little bit under pressure, uh, and perhaps your share price is hurting accordingly.

Uh, the chances are actually you are gonna find your way through this revolution as you have found your way through every other one. A much more useful metaphor if we're gonna stay with animals is the metaphor of the dancing elephant. In fact, Lou Gerner, the pre previous chief executive, IBM, he wrote this memoir called, who says Elephants can't dance.

IBM back in that era was able to, to reinvent itself. IBM is still trying to reinvent itself. It will survive, perhaps not quite where it once was, but it will survive. And so for me, the whole purpose of, of the book, which I've written, it's called Resurgent, um. This book just came out a couple of months ago, is to try to tell the story of big established companies figuring out, out a way to reinvent themselves in the light of whatever digital revolution is coming along.

We wrote the book, my, myself, and a guy called John Fallon. He was the chief exec at Pearson Corporation. Some of you might even know him. Um, we wrote this book almost to celebrate the, the ways in which big established companies are adapting to this changing world. Basically the bottom line is they do a much better job than most people give them credit for.

So that is my kind of opening framing and I've got a bunch of, of examples of the ways in which companies do that. Let me just start with a generic one and then I'm gonna move into the kind of the specifics of how we might be. More effective at responding to the generative AI revolution. So my starting point, and this is as I say, research I did three or four years ago before Gen AI literally existed, um, was to say to myself, what are the right strategies when.

A new startup comes along with a new business model or a new technology that is out there trying to kind of eat your lunch, trying to kind of have a go at you in terms of your core of your operations. You've got the classic sort of fight back strategy, which is to say we wanna out innovate. Innovators.

And so the classic example there would be the New York Times. You could have the financial times there if you prefer. Um, which is to say that when news became free, thanks to the internet for a while, uh, the big traditional, um, newspapers. Were under huge pressure, um, because of course they were competing with a free service over many, many years.

Um, new the New York Times, uh, tried, failed, and ultimately succeeded in creating a paywall based business model that we all know today. Uh, the New York Times now has 11 million subscribers, far more subscribers than it ever had when it was a print product. It has fought back successfully and indeed the entire.

News industry has done a terrific job. Now, uh, it's really annoying for you and I as consumers. Every time we see an article that we wanna read, unless we paid for the subscription, we can't actually access it. There's one or two exceptions, the B, B, C, the Guardian. But for the vast majority of high quality news, particularly in financial areas, we may need to pay for it, which is, you know, kudos two these companies for managing to figure out a new business model.

But, but my point is that's just the most obvious. Strategy, and it's in fact not always the right strategy. I'll just give you a very, very well-known, but very different example of what I'm talking about when put yourself back in the shoes of Disney in 2008, when Netflix Started streaming movies and indeed shows live, um, to your home.

Did Disney see that as a threat? Absolutely they did because suddenly they were losing control of the distribution of their own products. Did they fight back? With Net two Netflix, they did not, they explicitly did not create a streaming service in 2008. Uh, as you'll know, it was 2019, 11 years later when they finally launched Disney Plus.

What did they do in the intervening 11 years? They doubled down on or not? What actually is Disney's core strength? Disney's core strength is making high quality movies. So they bought out Pixar, they bought Marvel, they bought Lucas films with Star Wars, and that doubling down on making high quality movies was actually the right response.

I would argue to the streaming revolution. The. I look at my business in business schools, you look at yourselves in terms of your business models, what makes you successful. In many cases, I would argue even most cases, you look at what's changing in the world and you realize that your core assets, whether it's existing customers, whether it's to do with your, your upstream capabilities, your sales capabilities, whether it's to do with your ability to, to manage government regulation.

Those capabilities are likely to be useful. Whatever happens in that new technology and doubling down on those core strengths is actually the thing which is gonna help you to endure. That doesn't mean ignoring what's happening in the technology world, but it often means actually, you know, going back to what you are really good at.

Because customers, in many, if not most cases, continue to value that. Um, there's a few other strategies, less attractive, but in situations where. The new technology really is encroaching in a nasty way. On your core business, uh, there's a few defensive options. You've got, you can retrench into a, into a corner in order to survive.

K emerged with Minolta. They still make cameras, uh, or you can move away. You can actually say to yourself. Right now, the, in the case of Fuji who survived the digital revolution in film, when Kodak did not, we can see that, that that revolution is gonna damage our core business in selling traditional photo film.

So we're gonna move away. Fuji actually moved into cosmetics. They moved. Into, uh, active ingredients in pharmaceutical products. They found new colonies, if you like, places where they could go in order to make money rather than out, rather than trying to stay in what had traditionally been their core area.

Much more to say on that, but I'm gonna summarize. With the following kind of three pieces of advice. I mean, I'm just gonna skip quite quickly through this 'cause there's a story behind each one. But whenever I'm talking to a senior executive group about any new technology, uh, my starting point is do not believe the hype.

Every new technology, gen AI is no exception, gets hyped up above the point where it really should be. It's not to say that the hyping is completely wrong, it's just to say that we overdo it. So keep that in mind. Do not fall into those false analogies. Do your own analysis. On how that technology is going to affect you.

I've got a specific example coming up around generative ai and I would say proceed with caution. Um, the most, you know, the, the most sort of overused sort of concept and often in incorrectly used is the first mover advantage. This idea that somehow because a new technology is gonna come along and change our industry, we have to be the first ones.

To put it into practice. You know, my, my response when people kind of challenge me on this is, was Google the first search engine? No, it wasn't. Was Facebook the first, um, social, social network? No, it wasn't. Was Amazon even the first online bookseller? No, it wasn't. I mean, in all these cases, the ultimate winners were not.

The first movers. Now, I'm not saying ignore these new technologies. My advice is always to be paranoid and pragmatic at the same time. In other words, a little bit paranoid that this new technology is going to shake things up in a fundamental way, but PMA pragmatism usually should actually win out because.

If you've seen enough examples of new technologies coming along and some succeeding and some not succeeding, you can actually be a little bit more thoughtful about how you adapt. So don't get me wrong, you have to say, here is our generative AI strategy, but that doesn't mean betting the farm on some new technology, which might well be premature and might well fail.

Dabbling and, and experimenting with new technologies is appropriate. But just make sure that you don't overdo it. That's my kind of, albeit sort of simple advice, but actually my kind of reasoned advice to executives about dealing with any new technology. So I'm gonna. Shift gears a little bit and now talk specifically about generative ai.

As I say, I, I listened to the, the, the part of the Lenovo presentation. I listened to the brief presentation on Halo as an agentic AI tool. Uh, and I got a little bit of, uh, you know, in insight out, I think outta outta what I saw there. And I think you're gonna see some parallels to what I'm talking about. But let me, let me answer three questions.

There's many, many questions, but three. Crop up all the time. When we talk about gen ai, first of all, is it going to be disruptive to established companies? Uh, you can already tell that my answer probably is no, but I'm just gonna say a little bit more about it. Then I'm gonna dig a bit deeper into two important questions.

One is the extent to which that to actually really delivering on productivity benefits. Um, and thirdly, what's gonna happen to your job? My job in this world? Again, this is stuff that's been touched on earlier today, but I've got some particular thoughts on it and I'm gonna fi finish up. Going back to the, to the theme of my talk with what I think of as the leadership imperatives, the things that leaders of organizations of sales functions have to keep in mind throughout these conversations as the things that will make a difference to them in the long term.

So. Three questions, only two minutes on the first one. Is AI going to be disruptive? Um, I like to occasionally go back to, you know, my childhood as it were. Uh, you all remember Dr. Seuss? Uh, this is one of the books I had learned. There's troubles of more than one kind. Some come from the head, some come from behind.

What I mean by that is. That a little bit of thoughtfulness about the way generative AI is affecting your industry is really vital. Uh, and a very simple way of characterizing the difference in across industries is sometimes AI is affecting what I'm gonna call the supply side, how your product or services made.

And some affect the demand side, how the product or services consumed. And so if you go back to the internet 30 years ago, you know a lot of B2C companies, the internet was a demand side disruption. 'cause it literally changed the way that you interfaced with your user. And a lot of your users attempted to disintermediate some of your relationships with them.

Whereas if you think about the, the, the business to business world, think about the internet of. Things, the ways that the internet was used in factories and supply chain systems, that was changes in how your product or service was made. And to cut, long story short, um, the demand side changes are always much more disruptive.

Then supply side changes. So we take generative AI as the, as the story of the day. You know, if you are in the business of, you know, language translation, uh, you are in deep, deep trouble because, you know, the AI is now doing your job in terms of re how your customers were used to use your language translation services for you.

And those companies who used to, you know, sell language translation services are scrambling to survive. The vast majority of your companies, though, are on the left hand side. In other words, AI is being really helpful for many, many functions within a a, a value chain. Each one of which is helping to create your product, and to the extent that it's helping each of the pieces within that system, but is not actually changing your relationship with your customer.

You are well placed to figure out a way of harnessing the AI to help you. Perhaps that's an obvious point. Perhaps it's not, but I do think it's worth just reiterating that the place where the AI hits is going to have an impact. So I do believe that the overall threat level. In terms of disruption, of course, AI is affecting everything, but if you are worried about disruption and going the way of Kodak or Blockbuster, I think the vast majority of you can be assured that it probably will not hit you in that way.

Okay, question two of of productivity. So I heard as I said that the Lenovo talk and, and a lot of the conversation there was, was about the way that you are using ai, uh, as of often as a compliment to you as individuals. And I, I'm an academic at heart. I love data. I mean, I love stories as well, don't get me wrong, but I am spending a lot of time these days making sure that I'm up to date on what proper.

Evidence tells us about productivity improvements. So the, the, the bottom line here is that we are seeing demonstrable improvements in individual productivity. Of course, you would expect that to be the case 'cause you are all using AI in your own day-to-day work. Uh, there's one study recently which. It approved 12% more tasks completed, 25% faster, 40% higher quality.

Um, there's another study which I'm just, um, if I can just look on the chart on the right, uh, it may not be completely obvious what that says, but what you've got there is a baseline of an individual doing a, doing a piece of work without any AI help. The Blue Bar, the middle bar is a team. People working together without any AI help.

And then the yellow and the red bars on the right hand side are the individual and the team using AI help and performing to an even higher level than the team. So that's good news. For those of you who are using ai, it's kind of bad news actually. For the old adage that a team beats an individual, 'cause an individual working now with AI forms a sort of a human technology team actually is going to outperform or perform to the same level as as many, many teams.

So that's the good news if you like. We know that productivity benefits are coming. It's better in creative activities than actually coming to decisions. Uh, generally it helps lower performers more than high performers, but even that point is a little bit nuanced. However, if you then move from the individual to the organization, um, this is, there is no evidence and I, that's a strong statement, but there is no hard evidence of organizations seeing significant productivity improvements through AI yet, and I don't doubt that it's going to come, but we are still at a point.

In the, kind of the rollout of this new technology where companies are very shy about actually laying people off, uh, because of ai, they certainly aren't talking about it. Um, and if you think about it, the only real way you're gonna get massive productivity improvements is in fact through fewer workers.

And the, the, what the point I want to make is, is really quite straightforward, which is that. Every single new technology goes through this sort of scur sort of process. You've got the old S curve at the bottom, the new S curve at the top. Uh, the new Scur supplant the old S curve. The new technology supplant the old one, but it does it sort of step by step.

And the way I like to think about it is there are three ways in which a new technology changes things. Think about this in terms of the internet. Think about it in terms of the, the mobile phone revolution. Think of it now, in terms of generative ai, the first thing we do when we get a new technology is we basically just do existing things better.

We figure out that it's a way of cussing a little bit of, uh, giving us a little bit of a time saving on a task. Then we find there's new things we can do with this technology and, and I don't need to tell you what all those kind of fun new things are that we are suddenly able to do using gen AI that we couldn't do before, but, and this is the point.

It's only as you come through the sort of the first experimental pieces that organizations start to actually then redesign their entire systems around the technology. And the hard reality is that we aren't quite there yet. In other words, and I'm looking very closely for good examples, if you've got one, I'd love you to share it with me afterwards because I see a lot of people talking about redesigning their systems around new technologies using Ag agentic ai.

In order to certainly streamline entire processes. But if I push somebody not on what they say the technology can do, but what the technology is already doing and giving them demonstrable improvements in their system efficiency, uh, they will typically say, well, we're still working on it. We're still at the pilot stage.

And I think we're just at that point where we're gonna start to see some of these productivity improvements. But it hasn't happened yet. If I just. Turn it specifically to your world of sales and marketing. I mean, I, I realize you're mostly in the world of sales, but for whatever reason, sales and marketing get grouped together in these analysis.

Analysis. Um, this is a McKinsey study and what they were essentially looking at was. The impact of use cases across a wide sample of companies and what you can see, you can read these words, lead identification, marketing optimization, personalized outreach, and a lot of this is actually more marketing than sales, I would say.

Um, and a lot of it is, is, is slightly technical stuff. Um, there's huge changes underway, as you know, the world of, of sort of search engine optimization is in fact being challenged as we, as we speak. We used to talk about SEO and now we talk about GEO or a EO as. The new ways of doing engine optimization for essentially chat GPT based search activities.

So we're seeing use cases, but when you actually look for the positive return on investment of those applications. We are not seeing huge effect yet. Again, this is McKinsey data. They're looking for the cost decreases within business units. And at the top you can see that the, the little blue bar on the left hand side is a decrease in cost by over 20%.

Um. There's very, very few organizations which are claiming that, and even those claims are probably overstated. Um, so we're seeing some evidence of cost improvements, but they're actually quite small. Decreased by less than 10% is actually more common. And of course, you know, the, the rest of the, of the responses, not the, the 56% at the top are people who, who are seeing no return.

And then if you look at the other side of return on investment, which is of course, uh, revenue generation, again, we are seeing relatively small improvements increased by over 10%. Well, only 10% of the respondents said that in marketing sales, so that they're getting, uh, a result. So. My, my point is, I think quite straightforward, which is we are on the cusp.

We are at the point where there are gonna be some killer applications coming out. Um, and maybe you are starting to use them, but we cannot sort of demonstrably prove that those effects are actually working out. The previous it revolution, the whole internet revolution. Never actually ended up having the impact on productivity as it's classically measured that people anticipated.

It's actually called the productivity paradox, which is that we don't see the returns, uh, that people anticipate. And maybe the same is gonna happen again. Let me just spend, um, five minutes on what's gonna happen to your jobs. The good news is, uh, you and, and I, for that matter are in job categories. Which are likely to survive.

And let me just give you one insight from history. This is the invention of the spreadsheet, so think Excel. But actually the original event spreadsheet was called VisiCalc. And this is data from, I think the Wall Street Journal, um, looking at the number of employees in America. In three categories of jobs over the period of time following the invention of the spreadsheet.

And so what happened, of course, was that the number of people. Who were bookkeepers or accountants, auditing clerks, a number of people in those jobs dropped precipitously. But the good news is the number of people in management, Ana analysts, analysts and financial jobs, the green line, the people who were actually making sense of the numbers, the number of jobs there quickly took off and grew dramatically.

And we even saw a significant increase over this period of the people who were checking up on the numbers, the accountants, and the auditors. So that may be. A story you've heard before, but let's not lose the lessons of history, which is that every time a new technology comes along, there is a process of creative destruction.

You do see certain jobs going away, and we are absolutely seeing a contraction, particularly for young employees, for new entrant into the labor force in areas such as computer coding, some of the creative work, uh, some even of the banking type. Jobs, uh, that my students are trying to get. Um, but gradually over the years, new jobs emerge and this list is not in any way definitive.

It's, it's partly for fun because the whole point is that you don't know what the new jobs are going to be. All you know is that the whole process of capitalism. When some jobs go away, opens up opportunities for new jobs and some of these are jobs which already have existed for a number of years. Some are are starting to emerge and we know some of these things will take off, but we just dunno quite when there will be a bit of a lag, new jobs will emerge.

And I am an optimist on this. I know there are some people who claim that that gen AI is gonna kill jobs across the board, but I actually personally believe that history hasn't sort of, you know, disappeared. We should be learning the lessons of history and trying to draw conclusions, which link to what's happened before.

So, which job is the least at risk? Well, first of all, remember that substitution by AI happens at the level of the task, not the job. I think there was a point made by, it was Fiona and Trevor a bit earlier, was of course the AI is complimenting, uh, the individual. Um, but if you then sort of look at the specific skills that are going to be needed, um, I mean, I see three broad categories.

One is the kind of the whole notion of, of of, of practical wisdom or judgment or responsibility that any senior executive takes AI cannot make good decisions for us yet. Uh, then there's the whole empathy, connection, relationship, building. You know, anybody who has a sales relationship, uh, job. Is very, very likely to be quite secure in terms of maintaining that because ai, you know, AI is quite good at giving you the words around empathy, but it doesn't have an empath empathetic, uh, style.

And I know some people are arguing with me on that, but I really just don't buy it in the business world. That, that somehow a computer is going to, to replace me in terms of, of empathy and relationship building. And then there's a whole manual dexterity thing, plumbers and, and. Electricians, um, gardeners, many, many jobs actually require some level of judgment combined with strong manual dexterity.

Okay. Um, so there's a bunch of recommendations that, that follow from this analysis in terms of upskilling our employees in terms of redesigning their jobs so that we're combining things in new ways so that we can always have a sort of a, a human element on top of the, the AI elements. And there is a need for some proactive.

Workforce planning as well. Let me, in my final, sort of seven or eight minutes or so, um, turn to the, the imperatives that we have as leaders of others and whether that means you are a chief executive of company or leader, just of a sales team of 20 or 50 people, it doesn't matter. I think of you as leaders because you are influencing, you know, in a sort of social personal way what they do and how they do it.

I see a huge threat to the way that organizations operate from AI in the following sense. Um, yes, it's helping us to do things better. Yes, it's somehow enabling. Individual and potentially organizational level productivity improvements, but it's also forcing or en enabling a convergence. What do I mean by that?

I mean, first of all, you are already under pressure just because of the way that competition works, uh, to, to sort of replicate best practices and still, you know. Key talent from competitors and then sort of learning to do what your industry leaders are doing. Um, that's been happening for years.

Generative AI is now actually pushing a convergence almost in how we think because of these large language models, how they are trained. Um, we're all asking them similar questions and they don't give identical answers, but they absolutely. Tend to converge on a certain sort of worldview. And I get this all the time with my students.

I used to have good conversations with 'em in the class study about case studies, and now they've all used gen gen AI to prepare for the case study discussion. And they all come in with basically the same answer. And that makes my life difficult. But in your world, there is this risk that we are all, as I say, converging on very similar solutions.

So for me, the thing we've just gotta keep remembering. This has always been the case, which is that the essence of a successful company is always that it stands out from the pack, that it's got some sort of unique differentiated, uh, identity or, or sort of view of the world. That allows it to get essentially, a better position in the market against its competitors and the, the famous cases of the, of the, of the Apples and the Harley Davidsons, whatever your favorite example is of companies, which always sort of did things a little bit differently.

So we have this pressure to, to try to maintain distinctness in the face of. Ai, and I wanna just offer three antidotes, if you want to call them that, to these convergent pressures. Uh, antidote number one is human imagination. Now, AI can be reasonably creative, but of course, by definition it is creative on the basis of what it's been trained on, which is by definition retrospective.

Um. Human imagination allows us to do things that actually are forward-looking, that are a little bit crazy sometimes. Uh, beautiful quote from this guy. Um. Giles Hedges, his name. I don't actually know Giles, but I, I saw this quote from him a few years back and I loved it. He said, marketing will never be about reductive com computation.

It will never owe as much as the computer as it does to the expansive power of ideas. It's a test of the imagination, and there's no algorithm or. For that. So it's perhaps a, a fairly straightforward point, but never lose sight of the opportunity to, to bring people together, to come up with those crazy off the wall ideas.

You can use AI to help you in that process. But Don't somehow allow AI to drive that process. So a bit of human imagination is, will work wonders. Let me go to my second attitude, antidote rather, which I call unreasonableness. Um, and this comes from George Bernard Shaw. The, the reasonable person adapts himself to the world, the unreasonable person, persistent, adapting the world to themselves.

Therefore progress depends on the unreasonable person. And if you do any investing of your pension or whatever, um, you will know that the world of Roboadvisors computers, ais, which make stock selections for you, is gathering pace. And this is just one example. I mean, there are thousands out there. I dunno anything about this particular company.

Roboadvisors are on the march. If you want a stock portfolio or indeed an investment portfolio that kind of tracks the market, you're probably best advise to use a RoboAdvisor because they're very good at mimicking what the market is doing. But if you wanna beat the market, and this is a beautiful quote from the Financial Times a few years ago.

Uh, you need to be a little bit unreasonable. This article says that when it comes to investing, human stupidity beats ai. And what this guy Mars Johnson means by that is, um, you have to deliberately be a contrarian to have a point of view, which goes against the grain. In order to have any chance of beating what the market as a whole is going to, to, to give you.

Now, sometimes you're gonna be spectacularly wrong, and sometimes you're gonna be spectacularly right, but unless you are a little bit deliberately going against the grain, you have no hope of beating the market. So I think you see the point, um, a little bit of stubbornness, a little bit of tenacity and pushing ideas that.

Everybody else thinks they're a little bit crazy, can actually be the heart of your, uh, of your distinctiveness. Steve Jobs was famously, you know, seen as a little bit of a maverick who saw the world very different, and he kept on pushing through thick and thin, and obviously Apple benefited enormously and a result.

And then finally, I want to, to look into the notion of imperfection. As, as a way forward and, and there are many, many ways of introducing this concept. I'm just gonna introduce it for fun, through the notion of seeing wild animals. If you've ever been on safari, you know that we're trying to see the big five animals when you go to South Africa or whatever.

And you pay a fortune to go on a safari and you get driven around in Jeeps, and if you're lucky, you get to see all of the big five animals and you see 'em in their natural habitat. Is the objective here to actually see all the big five animals? Well, not really, because if you just wanna see the big five animals go to a zoo.

And you can see guaranteed all five of those animals in half an hour flat because they have been locked up and put into cages. I'm not endorsing zoos, as you can see. My point is that you deliberately are happy to pay a premium. For a product which may or may not actually deliver what you thought you wanted.

Uh, what you really want when you go on a safari is to see the animals in their natural habitat. And in fact, you know, the more money you pay, the more natural the habitat is and the less likely you are actually to, to be guaranteed to see them. Because obviously a lot of safaris are actually glorified safari parks, if you see what I mean.

So my point is. This really gives me up to my conclusion, which is. In a high tech world, we are often prepared to pay a premium for a product or service and experience, which is actually authentic and in some ways imperfect. Do you want, when you next go flying on a premium airline, do you want the air host or the air hostess to be almost robot-like in terms of serving you?

Or do you want them to actually. Portray a little bit of a human personality, a little bit of fun having a bit of a joke with you or whatever. I mean, I, not everybody wants that, but my, my view is that in this increasingly high tech world, we're prepared to pay a premium for an authenticity, uh, and personal touch, which often is, is actually increasingly absent.

So I'm gonna wrap up. Um, I want to just, again, play the role of, you know, there's nothing new under the sun here. Uh, a gentleman by name of John, name of John Nesbitt wrote a book you see on the left, it was called Mega Trends, and he wrote this book in 1980. So that is what, 45 years ago, uh, before some people in the audience were even born.

And the first of his 10 megatrend, he was the first orig, the original futurist, if you see what I mean, the first of his 10 megatrends things shaping society was exactly this term, high tech. High touch, and I'm gonna quote from his book because it's actually relevant as relevant today as it was back in 1980 whenever a new technology is introduced.

Remember this is before computers as we know it, were created. You know, the original IBM personal computer was 1981. Whenever a new technology is introduced into society, there must be a counterbalancing human response that is high touch, or the technology is rejected. We must learn to balance the material wonders of technology with the spiritual demands of our human nature.

Um, what's he saying? He's saying a version of what I just said, but the point is he said it 45 years ago, he was anticipating, obviously a continuing, uh, set of computer revolutions. Uh, he couldn't have possibly predicted where we'd end up, but the point is. That over the 40, 50 years since this book was written, we've had no end of revolutions.

And in each case, this high touch, high touch response has actually been a vital part. Of helping us to succeed. So I'm gonna stop there. Very happy to take a couple of questions. I hope this was either, you know, provoking or assuring, whichever it was. That's, that's my, my mission complete. So thank you very much for your time.

Phil: So thank you. Thank you. Okay.

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