Simone Cicero 

Hello everybody. Welcome back to the Boundaryless Conversations podcast with our second episode of season six. On this podcast, we explore the future of business models, organizations, markets and society in our rapidly changing world. Today I’m with my usual co-host, Shruthi. 

 

Shruthi Prakash 

Hello everyone.

 

Simone Cicero 

Thank you for coming. And we are joined by Philippe De Ridder De Ridder, the co-founder and CEO of Boards of Innovation, a globally renowned innovation consultancy. Philippe is a visionary leader who has helped major organizations around the world from Fortune 500 to innovative startups develop quite bold strategies to rethink and launch their products and business models.

 

Nowadays, Philippe is pioneering what he calls the autonomous age or the age of creative AI, a shift in organizational capabilities powered by AI. And he claims it will deliver the biggest productivity increase ever in history, striking 50 % in just a few years and across industries, starting from the knowledge work economy. Philippe, it’s fantastic to have you here with us today.

 

Philippe De Ridder 

Well, thank you so much for having me, Shruthi and Simone. Super nice to be here and hello to the audience as well.

Simone Cicero

Thank you so much. So, Philippe, we always have a quite open opening question on this podcast. So the one that I have been thinking about for you is this. And, you know, it’s really focused on some of the key points that you are making, which is – can innovation, which is the dearest child, let’s say, and treasure of management gurus, really be automated?

 

Is this the case?

 

Philippe De Ridder 

That’s a great question. And the short answer for me would be largely yes. But let me maybe elaborate on that a little bit. First of all, starting with what innovation really is, because it’s obviously a buzzword that’s used for many things. So let’s simplify it as the act of imagining, building and launching successful new products or solutions to problems out there.

 

So in a corporate context, that’s new product development, new product introduction, et cetera. In a scientific context, that would be new scientific discoveries, et cetera. So what we’ve been seeing is that that act of innovation and new product development can indeed largely be automated. If we were to break it up and for example, think about consumer goods, typically that would start from gathering insights on consumer behavior and what the unmet needs are in the market. So we’ve seen that large language models and AI models are quite good at distilling those insights from, for example, social listening data, sales data, et cetera, that then you can feed it into an ID generator. 

 

And we’ve seen studies over the last months that effectively LLMs come up with novel ideas and that they are on par with human generated product ideas. And then it moves into consumer testing, which we’ve also seen by now countless studies that LLMs are actually quite good at representing specific groups of consumers so that you can synthetically test the hundreds of ideas that you’ve generated and so on and so on. So definitely for the front end of innovation and obviously we’ve seen application use cases in more scientific fields as well with alpha fold in protein discovery in drug discovery, which has been, which is being accelerated quite exponentially.

 

And we have been testing some of those AI engines and we’ve been building some with some of the world’s largest organizations over the last year. And also the products that have been innovated, if you want, or have been conceived. We’ve taken them through blinded consumer tests and they actually come out as at least on par or superior compared to traditionally generated new products.

 

With that difference is that they are generated in minutes rather than typically in 6 to 12 months projects. So you get to a model of real-time innovation if you want.

 

Simone Cicero 

I was listening to your recent podcast on this topic and in the meantime I was thinking to my friends in UX and research and I thought they would have really reacted quite strongly to this idea that you can use synthetic customers, let’s say, in the process of creating new products and services. 

 

To what extent is this really kind of possible? So, in your actual work with companies, how much, you also spoke, for example, of this idea of the role of the human as a curator. So for example, is this also something that happens in research? you have, you kind of need, you know, research curators that can a little bit like in a similar way that software engineers now use co-pilots.

 

It’s more like a research co-pilot or is really something that can be autonomous to some extent and kind of end up in saying, you know, this is the new product that you have to build or is maybe something that where UX research architects or something like that curate and organize this set of synthetic agents and customers and researchers.

 

Philippe De Ridder 

Yeah, great question. And there’s a couple of alternatives in terms of leveraging AI for consumer research. So maybe trying to give a bit of the overview so you can deploy AI in actual human consumer research. So for example, outset.ai is one of those platforms that’s leading in that space. 

 

With outset, we ran a test couple of weeks ago for one project, we ran over 200 interviews. So with actual human users over the weekends. And when I say “we”, actually an AI chatbot or interviewer that would run those interviews based on the prompts and scripts that we gave it. And it kind of operates semi autonomously and can go off script depending on the answers that it gets. 

 

So it exponentially well, increases the speed and the size of human consumer research that you can do. So that’s one branch, basically accelerating the traditional way of working if you want. And then you have the branch of not interviewing or researching actual human users, but synthetic alternatives to it. So that’s what you refer to as synthetic users or synthetic consumers and syntheticusers.com is for example, one of the leading platforms in that space. And basically what that does is is that it asks LLMs to impersonate specific personas or specific target audiences. So you have some where you can individually interview specific synthetic users or it creates entire panels so that you interview 200 synthetic users with each that have their own preferences. And I would say within that one step further is where you start creating actual digital twins of users. 

 

And for example, Food pairing AI is a good example of that specifically for food and beverage. they’ve surveyed over 10,000 people globally, according to specific demographics, etc. on their flavor profile. And it actually creates a digital twin of Shruthi, Simone and Philippe that then it would interview and test against. 

 

So it’s a step beyond instructing an LLM to act as a certain persona to actually feed it with real user data, if you want, which makes it a richer synthetic consumer panel to test against. So that’s kind of the different alternatives that we’re seeing at the moment and that we are working with. We each have their own value prop and then to your question of what is the human role in terms of doing the research. So our point of view, indeed, as you mentioned, is that the role of humans in general with AI will evolve more from creators to curators or editors. If we apply that, for example, in the design space, rather than starting from a blank page or a blank screen, with first designs is that you would work with an AI design system and instruct it. It would give you a first 10-100 of different alternatives. And you would basically curate those results, edit those results, go for a next iteration. And I think in a lot of domains, that’s how we will see the role of humans evolve from creators doing everything from scratch towards curators and in general, we definitely advocate to keep humans in the loop, even in semi-autonomous systems. And in general, we, we are working towards making humans the hero in the whole AI transformation of our society, because there are obviously alternative paths where technology would become the hero. And maybe if we look back in 10 years from now, we wouldn’t be so happy with the whole AI transformation.

 

Simone Cicero 

I mean the image that I get from this is more than an actual editor – it’s more the role of the pilot of the plane that oversees the systems, the autonomous systems as they go, which is interesting and fascinating. And at the same time, of course, opens up quite a Pandora box in terms of impact. And we’ll get to this later on.I wanted to rhyme with what you said a little bit, because yesterday I was, well, a few days ago, I was preparing for a training and as part of the training, there is this exercise where people have to kind of work on a fictional company.

 

And it was fun because I actually asked GPT to make project works. And part of the project work was fake interviews with managers and VPs talking about their problems. And it was really surprisingly good. It sounded very credible. So I think that’s a testament to the fact that you write on this synthetic customer. So in general, this capability that AI models have to create world models, which is fascinating.

 

Shruthi Prakash

I’m curious to understand, right? Like, let’s say, taking the food example, which is an extremely niche preference in terms of how the customer sort of address this or participate with the product itself. 

 

So how does, let’s say, AI creativity in that sense adapt to qualitative aspects of the interviews itself, for example, and have you already seen the impact of this in terms of how the customers respond to it once the product is made? And why I’m asking this also, like, if you take, let’s say, design thinking principles of maybe like shadowing or being, let’s say, a fly on the wall and listening to the conversations, right, a lot of that is driven by an empathy forward approach. And therefore, are these models mimicking existing practices or therefore creating new ones which are a step ahead?

 

Philippe De Ridder

I would say at the moment they are mimicking existing approaches, which is typically in general what you see with the new technology that comes up. If we think, for example, when digital and mobile came up and the first newspapers that we saw were just PDF versions of paper newspapers and only years after it was reimagined how we could actually consume news way more bite-sized, way more personalized, et cetera. And I think that’s in general what we’re seeing with AI right now as well. It’s, GenAI specifically and LLMs is that they’re being applied to the current way of working. And it will typically take a couple of years before entirely new ways of working emerge that are native to the new technology and we typically refer to it as wave one, which is spot applications applying it to the current way of working and then wave two, which is the real systemic transformation. And I’m sure we will start seeing that specifically in user research as well. I think one of the things that it really enables is that you can go really exhaustive and exponential both in the ID generation as well as in the testing – which is for example what we’ve seen in protein folding with alpha fold as referred to earlier but also DeepMind’s model that discovered millions of new materials that otherwise would have taken us 800 years as humans to come up with. But it also in product development allows us to generate 10,000 new for example ingredient combinations for a new food product and to test all 10 ,000 with synthetic consumer panels. 

 

Whereas if you do it in the traditional way of working, you’re limited by a couple of 10 of concepts that you can test. So that’s one of the things that the new technology enables to be exponential and almost exhaustive in the amount of variations, the amount of solutions that you generate as well as can test synthetically.

 

Simone Cicero

So let’s switch into another kind of chapter of the conversation, which is something that is really important for our audience in general. So in terms of how do you integrate these inside the organization? this new, you speak about new organizational capability, which is, guess, largely these kind of autonomous innovation core. How do you see this to be integrated in the organization first? And then what are the impacts that such capabilities have in kind of changing radically the structure of the rest of the organization. So, you know, of course you need a new capability, but what else, what happens to the rest of the organization as a consequence of integrating this new capability?

 

Philippe De Ridder 

Yeah, a couple of different perspectives to that – If we specifically look at autonomous innovation, which is just one field of applying it, but obviously also looking at marketing or supply chain or finance, I think the same principles are at play. How I look at it is that I think a common pitfall is that AI is too much deployed on existing use cases and that happens typically when you crowdsource bottom up like a whole roadmap of AI transformation that starts from existing functions, existing processes and we will deploy AI to do one step in that process a bit faster. So what I’m advocating for is a future back approach where you start from – Where will we be in five years from now? How will society have changed? How will consumer or client behavior have changed? How will our industry change? And what role do we want to play within that as a business? And then from that, what needs to be true in order for us to be successful at that? And what that leads to is that you rather than starting from how can we do the current thing more efficient, which is where a lot of the current AI investment is going into. You start from re -imagining a whole workflow end to end. And for example, if we apply it to innovation and product development, which we’ve been talking about, it’s not just about then building the new technology or AI platform that will do all of those things semi autonomously, taking in those insights, generating new product ideas, prototyping them, testing them with consumers, getting marketing campaigns ready, et cetera. But also thinking about how do we need to evolve the organizational structure for that? 

 

And if we stay in the realm of consumer goods companies, they’re typically organized in separate departments with an insights function and innovation function, an R &D function, a go to market function, and they obviously have different names, but largely cut into those type of functions. And if you reimagine the whole workflow and going from that typically being a 12 month process to it being a process that spans only days or hours, you can’t be organized in the same silos and functions because that wouldn’t work. 

 

So my point of view is that actually the hardest part of the transformation won’t be the technology, but it will be evolving and transforming your operating model and your organizational model around it. And that will be the true unlock. And I also think there will be more competitive advantage to be built by the right combination of the new technology and then the operating model rather than just the technology because the technology in itself is a general purpose technology like electricity was and all of the other technologies that we kind of all have access to or most organizations have. So the technology in itself is is not to be expected to generate a competitive advantage in itself. And it’s really going to be the interlock of the technology and the operating model in my mind.

 

Simone Cicero 

And we already see a kind of transition from functional models, which are very old into, I mean, we have seen in the last decade, couple of decades, the emergence of matrix models. So what is the, how are these organizational structures changing according to your experience? 

 

What we see from our perspective, in general, this shifts towards what we call the platform organization. So an organization essentially powered by more autonomous teams, more autonomous units, let’s say, that maybe manage their own P &L and are more customer -oriented and more autonomous in setting their product and service strategy, maybe with the company kind of exercising control through enabling constraints and ensuring certain coherence of brand, but in general giving a bit more autonomy and independence to the product units. So what are the things that you are seeing in terms of how the structural operational models are changing, resonating, integrating this new capability?

 

Philippe De Ridder

I think the short answer is that I’m not seeing organizational change yet. So I think with the uptake of AI and GenAI, a lot of it has been focused on, as I mentioned, applying the technology on existing use cases and existing ways of working. And we’re not in that second wave of systemic transformation yet. 

 

If we look at an example in history, for example, when another general-purpose technology like electricity was introduced on factory floors. So before that, you had steam engines, which was a central steam engine in a factory floor that then mechanically would be powering all the different parts of the factory floor. 

 

The first years when electricity generation was there, it would still have that same central model where there was electricity coming in and then mechanically being distributed across the whole factory floor. And it took us over a decade for the first factories to be designed in a fully electricity native way if you want, where electricity itself was decentralized and distributed and could power all the decentral units. 

 

And I think now with AI we’re seeing the same thing, but in terms of organizational structures is that right now it’s just being deployed in the existing organizational structure. And it won’t take us over a decade because now the speed of change is obviously faster, but it will take us a couple of years for organizations to evolve their op model around the new technology. 

 

So for now, like I haven’t seen it have a substantial impact in the way organizations are organized or structured. If we separate it out from AI and the transformation that that drives, then I have seen similar evolutions to what you’ve been describing towards more autonomous nodes, autonomous teams, et cetera. But I wouldn’t say it’s been impacted that much yet with or by AI so far.

 

Simone Cicero

I mean, before Shruthi jumps in, I think it’s interesting to make a connection between this idea of autonomous units and autonomous products that you speak about. So essentially at some point we can imagine that leadership doesn’t just have to let go some control and let the autonomous units go ahead, but even sometimes they will have to let go control and oversee an autonomous

product doing evolution on its own, even without a team or just a team of co-pilots, human co-pilots actually, that would be a fascinating point. So Shruthi, please go ahead.

 

Shruthi Prakash

Yeah, I mean, it’s relating to what Simone is sort of edging at as well, right? Like a lot of this organizational transformation starts with leadership transformation. therefore, do you see a lot of these traditional executive decision making reducing? And where does, let’s say, AI systems play a role in guiding long term strategy? And you can also maybe if there were examples from your previous experience, right? 

 

Like where the leadership had a different vision from maybe what the AI driven evidence indicated and how do you sort of go about tackling that and getting there by in.

 

Philippe De Ridder 

Yeah, good question. And maybe shortly responding to what Simone said as well on the word autonomous, because it’s maybe interesting to depict that a little bit. when I talk about autonomous, it’s for us the next wave of transformation powered by AI. 

 

And if you were to put it simply for us, it’s the evolution from an analog world towards a digital world, which we’ve all lived through in the last two decades to now, a more autonomous world. That’s our articulation of what the future would look like. So think about autonomous products, autonomous assistance that help us all personally on booking our travel or buying products for us according to what we like and don’t like. 

 

But also we will start seeing fully autonomous businesses that go all the way to that model or autonomous workflows, etc. So for us, that’s the articulation of the next wave of transformation. 

 

And to your point, Simone, it’s interesting to think about, will it also give humans more autonomy? And will that go hand in hand? Because that’s the other use of the word is to talk about autonomy on a human level or a team level, decentralized decision making in organizations, etc. And I definitely think that systems could enable that more and that they could go hand in hand, but obviously to be seen in the coming years. 

 

And I think it also ties back to the intent, as I said earlier, like I really think the intention should be to make humans the hero in the story rather than let’s say the slaves of the AI system if you go all the way to another extreme. Then Shruthi to your point on leadership and strategy, I would say strategy is probably one of the fields where I’ve seen AI play less so far. If you compare it to almost any other process in a business from manufacturing to supply chain to innovation to marketing, finance, like I’ve seen AI use cases on almost any company’s roadmap in all of those fields, but actually not that much on strategy itself, because I think at least we have a mental model probably as humans that that is a more human activity.

 

which I guess ties back to our expectation that it’s a very well probably related to two things on the one hand because we think it’s a very complex thing because it takes in so many different variables and inputs so it’s not standardized at all in a way and obviously you could think about it in a way more standardized way but typically it isn’t – strategic decision making on an executive level. 

 

And then the the other reason why I think it’s it’s not high on the current roadmaps. It’s because it’s it’s not that repetitive. It’s not an activity that happens every day of the year, obviously, some strategic decisions, maybe but not like your annual strategic planning exercise or a quarterly one. 

 

Whereas for example, another activity like booking invoices or writing blog posts or making commercials is something that happens every day. So there is a bigger need to automate it or look at more autonomous ways of doing that versus strategy and leadership topics. One application that we have seen and that we’ve ran with a couple of clients as well is strategic wargaming, if you want. what if you if you model not consumers, but basically your competitors and you create a digital twin of your markets and your competitors. 

 

And then what if you could run strategic scenarios or options that you have as a company and then see how competitors would respond to that, et cetera. So I’ve seen experiments in that space, but nothing that I would say is at a mature enough level yet to say that that’s validated way of deploying it.

 

Shruthi Prakash

It gives a very gamified approach to strategy to me at least as a listener and that’s extremely new.

 

Simone Cicero 

Yeah, actually, was essentially thinking that once you trust an autonomous system to talk to customers or to simulate customers, so in general to take care of the customer connection and customer insights, which, know, if we think about the corporate culture versus the startup culture, there’s always been this big topic of, know, corporate don’t talk to customers. Instead, startups are very much customer focused and customer connection and zero distance to customers has been heralded as the, you know, holy grail of innovation. So I was thinking that maybe once you integrate AI and allow AI to talk to customer or to simulate customer insights and so on it can do anything else. 

 

And essentially strategy, when I think about autonomous products and AI is talking to customers, strategy looks like really kind of a game that you can play, but it doesn’t really have that relevance that it has in an old style organization. it’s like, for example. 

 

Simone Cicero

In an old interview we had with Kevin Nolan, who is the CEO of General Electric Appliances, we were talking about adopting the Rendenhaeyi platform organization model with micro enterprises. And he said, we don’t have strategy the micro enterprises have. So there is this decentralization of strategy into the product units. 

 

And so we have really have we’re really evolving towards an organization where there are lots of autonomous units, potentially autonomous products. And then you look into strategy as this AI-powered landscaping and forecasting and foresight exercise. It really looks like boys playing D&D, something like that. It sounds very much less relevant than it used to be in companies where maybe resources were more limited and you had to be more kind of driven by strategic choices, reduction of options and so on. But that’s kind of impression. What do you think about it?

 

Philippe De Ridder 

That’s a great point. And I think that in itself is a strategic decision, like how autonomous do you want your systems to be versus how directive do you want to be as the human leaders of that organization? And I think where we already see, for example, a lot of autonomous decision making is, for example, in trading – in the stock markets, think by now around 60 % of all stock trades happen by autonomous systems, which is a crazy number if you think about like all the money that that represents. But obviously those systems, are still largely instructed or modeled by humans that wanted to operate according to certain principles. 

 

But obviously you could also instruct those models to evolve on their own based on what it learns on what was successful, what was not successful, et cetera. And obviously some of those systems do. So I think we will start seeing that on all other types of autonomous systems that will come to be in terms of autonomous marketing, autonomous innovation, autonomous almost any function in an enterprise. And it will get come down to that choice on how much autonomy do we want to give to that system? And there are, for example, there’s that story at Google when their AI model started speaking in its own language, so humans couldn’t understand it anymore. And then they kind of pulled the plug from that. So it’s obviously a scary thing that at some point we wouldn’t be able to understand anymore what the autonomous system is actually doing. And it will be a choice if we’re okay with that, as long as it stays within certain boundaries, or if we’re not okay with that. 

 

And that’s going to be a very strategic decision for each organization, if you want in terms of what’s our ambition, in terms of how autonomous do we want things to be. And maybe one other perspective to add to it, like when we are building those engines right now, for example, product development engines, it makes everything more programmable in a way. And I think there’s actually a very large role to set a strategy for the engine in itself. For example, you can instruct the engine that every new product needs to meet certain sustainability criteria, which then means that if you’re an organization with over 100,000 people globally, that all of the products that are being created will meet those sustainability criteria. 

 

Whereas in a pure human organization, it’s always less centrally organized in a way because as humans, kind of go off script quite a bit. So it makes, on the one hand, it gives you a lever to get to better outcomes, but at the same time, it also comes with great responsibility because the engine that you program that will come up with all of our future products if you want. Yeah, small variations in what principles you give it to work from or what criteria it works against will have exponential impacts as well. I still see an important role for strategic decision-making in the future is probably my conclusion.

 

Simone Cicero 

A little bit like a strategic prompt engineer CO.

 

Philippe De Ridder

Yes, on a macro level, if you want. Yes. Yeah.

 

Simone Cicero

Like a CEO sitting there and prompting her own agents. And that’s very scary and by the way, that’s a massive leadership challenge, right? And it goes even beyond that, you know, because we are talking about one person unicorns where I don’t even know if it makes sense to talk about leadership anymore, not because it’s leadership towards agents or something like that. 

 

Simone Cicero 

So all these evolutions pointed towards a much more abundant niche and options, option-based economy. You speak about, in an interview you spoke about the fact that it’s probably going to be AI talking to AIs, like on the consumer side, you need to have some kind of filter AI that can evaluate all the options for you and reduce the burden on the consumer to choose or to ponder options that are presenting. 

 

For me, this kind of calls in the idea of the metaverse. Let me explain why, because essentially, if we think about all these products, abundance, this is really something that I don’t see playing out in reality, because there are some major, you spoke about, for example, prompting for sustainability constraints, but sustainability constraints exist. It’s not just something that you can prompt for. So they actually constrain production. 

 

So you can have multiple ideas, but then if you have to produce something, have to have adaptive supply chains and then you have circularity and whatever. So there is a certain limit where our production capability at the moment, and maybe with autonomous systems, it will be easier, but essentially, there are constraints in the physicality of the world. So my point is, can we perceive this shift towards autonomous products as a point that tells us, you know, we need a simulated environment where we can consume infinite products, we can propose infinite products and enjoy it, but it needs to be somehow detached from reality. 

 

What’s your perception? How these two things connect? The metaverse has been a topic for business for the last couple of years and nobody has really understood how to use it. But maybe is this really the the Nexus that brings us into the metaverse.

 

Philippe De Ridder

I think in general, you’re making a really interesting point about whether this is gonna embark us on an age of abundance in general, abundance of products, for example, and I’ve talked about what I call a product proliferation before that we will see a proliferation of new products, which is going to be a complete overload for us. You are very right that in the physical world, there are constraints in terms of or actually producing those products. Or for example, when we talked about food and beverage earlier, it’s not that as humans we’re gonna consume more drinks or food items per capita or maybe incrementally, but maybe hopefully less. 

 

But that abundance will definitely exist in the digital world where you don’t have those constraints. let’s maybe take an example like music. Yeah, I don’t know if you’ve played around with AI music generators like Suno and others, but they’re actually pretty good. I’m not a music expert at all. So forgive me if I say something that you wouldn’t agree with, but.

 

That’s what experts tell me. That it’s actually pretty good. So that means that the cost and the time to create a new song is reduced to almost zero right now, which means that we will probably see an abundance of, for example, new music songs. You could imagine that every day there’s a million new songs that are being generated and tried out in the Spotify algorithm that each presents it to a cohort of users and only picks up the 1 % that people seem to like and don’t click to go to the next song or whatever. And we will see that I think in all kinds of digital products. The same for movies, for example, we will start seeing AI generated movies, which for example, Showrunners is one of the front runners in that space experimenting with that. So we will see an abundance of video formats, etc. And I do think it’s gonna be a bit of an overload for us. So that’s what I described. think in the earlier conversation you’re referring to that on the consumer side or the user side we will have AI assistants that basically curate out of all of that abundance, what the options or the items might be that are of most interest to us. So we will probably not see that abundance of offering out there, but just the selection that our AI companion thinks is most interesting for us. 

 

But fully agree with you on the limitations in terms of physical products – but I do think we will have that abundance in digital products. Yeah, so that’s my main perspective on the matter.

 

Shruthi Prakash 

I was sort of going back on that itself, which you mentioned, I think there will be some sort of decision analysis paralysis or overload in terms of decision making. And there was this one article which we shared, Simone, I’m not sure of who the writer was, but it said something on the lines of how there are so many articles being published, but who even is reading these. So it’s extreme sort of it’s crossed the point of over consumption. Anyway, so that is a point I wanted to make, right? 

 

But do you also see a lot of participation in these autonomous product development essentially from a customer point of view? Are they becoming passive in the sense that there is so much data that’s coming to them? So in that way becoming sort of passive or because they now have the opportunity to closely participate and sort of real time get changes in their products? Is that a good or bad thing that’s sort of happening from a consumer point of view?

 

Philippe De Ridder

Think it could go both ways. I think in some instances, it will give tools to consumers to be more involved in the product development process. I refer to Showrunner as an example. So that will be a platform where we as users can create our own episode of South Park based on what we would love to see. And then obviously you could share it with others. So we will see consumer co-creation at platforms, but I think in general, they will be fairly niche. 

 

Because a lot of people just like to get ready made stuff like we are living in an age of convenience as well. So I think that’s going to be the mainstream, where we consume digital physical products, etc. That are ready made. 

 

And I think in terms of time spent, I guess we will see a similar evolution to previous technologies or inventions that have saved time for us. think in general, it will save us time on stuff that we do right now. For example, if you think in a household back in the day when dishwashers or washing machines, laundry machines were introduced, it saved us time there that then we would spend elsewhere.

 

So I think in general, AI will save us time as well as citizens, as consumers, that then we will start spending probably in other entertainment options as well. And in that sense, it might make us more passive if you want. If you look at those past evolutions, you could also say that now in running a household, we are more passive than maybe we were 50 years ago before dishwashers, laundry machines, et cetera. And you can argue if we collectively became happier of all of that technology outsourcing, I think in general, but obviously there’s so many variables there is that collectively like happiness hasn’t been going up in developed economies. They typically go up when people are elevated out of poverty, but then they don’t rise the richer you get or the more technology support you have or the more free time you have. So I do think that’s a big societal question is like to what is the technological process leading and any collective happiness, the thing we want to optimize for or is it something else?

 

Simone Cicero

Right I mean, in general, think these, these, conversation we have, it’s kind of pointing towards, you know, from, from, from a consumer product perspective, a landscape where there’s going to be a lot of noise in the economy and, catching the signal would be very difficult. And, this is generally not a good sign. I mean, for, for the, from the social, say social -technical perspective. On the other hand, maybe as we enter the last part of the conversation, in previous podcast, you have been also very adamant on your concern for this social capability that we have to contain and manage this type of revolution and that.

 

I mean, always, when I talk about this, I always think about Marxist perspective on this, where Marx essentially said, at one point where essentially our cognitive capacity will be autonomous, basically our social knowledge will be autonomous and that’s happening with AI. Our social knowledge has become an autonomous force, it can create value in society. This really kind of challenges the very structure of capitalism. So capitalism is about, you know, capital having a relationship with certain relationship with labor and AI kind of subverts this relationship quite strongly.

 

I have a couple of questions for you. First of all, how do you feel about that? What’s your perception? And secondly, are the brands that are working with you kind of starting to think about how society will look like and what’s the, what their role will be in such a landscape besides making products, you know, that people can consume. So are they perceiving the shift in a way that it’s pushing them to think about their role in a radically changing society this way.

 

Philippe De Ridder

It’s a super important point, right? I would say in general, a lot of the thinking as I shared earlier has been about applying AI on current use cases, making it more efficient rather than the big picture thinking, I would say. So in general, maybe not as much as you would want. I think that’s going to come in the next wave of, in that second wave of systemic transformation that people will also start thinking about those more fundamental questions.

 

I think there’s obviously the big question, will it lead to more unemployment and will indeed at some point that that correlation between labor and money break further than it maybe already has in part. I think it’s very difficult to predict if you look at previous technology revolutions, there’s always been the same fear and then afterwards we actually ended up with higher employment, but just in different jobs. Obviously, you could argue that this is a different kind of technology that will lead to a different outcome, but like we haven’t seen it in in history yet. I think, to do that discussion, like there’s always the angle of talking about universal basic income as a potential solution there and us being both from Europe and I actually don’t know about the system in Italy. But for example, in Belgium, there is actually already a system of of UBI, you could argue that that is not high enough, but everyone gets an income, even if you never work in in your whole life, and you can be for or against that. But so there, there are countries where where that in ways already exists. 

 

I think an often under highlighted question, or underrated question is actually what impact will that have on our happiness and satisfaction as people, because the money is wanting. But for a lot of people, the job that you do gives you a sense of fulfillment of a role in society as well. And there’s a lot of studies that people that are unemployed and don’t enjoy a job are actually collectively unhappier. So I think that’s that’s another really important question. It’s not just about the money, but it’s also about happiness about social cohesion, a sense of fulfillment through through that. And maybe a last point on like what you said, the decision that business leaders will have. And if we just look at a simple example, let’s say that you previously needed 100 people to do a certain function or task in an enterprise and that by now with AI you only need 10 people and then the AI agents to get to the same output. And I just saw a study being published yesterday that on specific use cases actually said that it was only 3% the cost of AI agents doing something compared to the human benchmark. Let’s now take 10%, which I think is conservative, obviously, depending on the use case, but so you only need 10 people to get to the same outcome. Will you then as a business leader decide to let go of the other 90 people and produce the same output, but with 10 people and be way more cost efficient? Or will you be the company that thinks about but what if we keep all 100 people and we get to an outcome, which is a tenfold of what we previously had. 

 

If we’re obviously talking just theoretical possibility, and I think that’s gonna be a really important decision. Will you go purely for the cost efficiency, the margin optimization, or will you go for exponentially increasing your output, whatever that output is in for that function or that industry. And that’s gonna be a really important decision.

 

Shruthi Prakash 

For me, the point was on how, let’s say, like you said, right, so much of it is mimicking human behavior. And I’m just curious how this sort of impacts the social identity of a person. And I’m asking that because especially in India, as it is, let’s say the creative and innovative sort of spaces are undervalued in itself. And for it to be imitated to that degree by AI thereby even further diminish or devalue a person’s let’s say individuality is very scary to me so that is a point I wanted to make.

 

Simone Cicero

Yeah, I mean, if I can jump in, I think in general, the question that I was thinking about as I was exchanging with Shruthi is “value”. So what is the perception of value in such a landscape, which is very relevant to brands? So for example, already have put much more value into craftsmanship versus large scale production, right? 

 

So when you buy something hand-made, it has a perception of value. So have you ever been talking about these value shifts in perception a little bit with regards to creativity as Shruthi said or human contribution or personal contribution?

 

Philippe De Ridder

Yeah, I think we will value human craft in the future as well. And I think we will start valuing what I’ve called artifacts of humanity before, which could be as simple as a spelling mistake in an email, which may be in the past, like we wouldn’t have liked too much. But right now it’s a proof that that email or well, it’s a potential proof that that email was written by you rather than an AI agent, obviously you could argue you could instruct an AI agent to make one spelling mistake per email, but assuming that that’s not the case, I think in general, we will we will really value artifacts of humanity, mistakes, things that look very human. We will definitely see brands that go all the way saying we’re 100 % human built or human powered and we shy away from AI. I think there’s going to be a big cultural counter movement around that. I think that the mainstream movement long -term is going to be a large adoption of AI and that a lot of the things that we read, view, et cetera, will largely be AI generated because that is just how our economy and so far the human race and societal systems have been built. We always look for

perpetual progress for cost optimization, efficiency gains, stock market rises, GDP rises for countries, individual rises for people or families. I think the systemic model of how economies, societies, businesses, families, individuals are organized on that strive for progress. That’s also probably why homo sapiens have taken over the planet because we are somehow biologically wired for that, I guess. I’m not a biologist, but that’s my assumption around it. So I think the mainstream is going to be a large adoption of AI because of that.

 

Simone Cicero 

Yeah, a bit like buying a product from a traditionally bureaucratic, micromanaged human organization will be a luxury good in the future for just those that can afford it.

 

Philippe De Ridder

Yeah, I think so. we will see very specific branding around it. But I think that’s going to be the luxury product or the niche product in the end.

 

Simone Cicero

That’s interesting. That’s interesting. I mean, we’ve been going through very long topics and conversations, so let’s wrap it up. Last bit from you, I would like to ask you, as we do with all our guests, to share with our audience a couple of breadcrumbs, so suggestions that you want to drop to our audience for them to catch up with this topic or others.

 

Philippe De Ridder

Yeah, happy to share maybe two books that I would recommend. The first one being Autonomous Transformation by Brian Evergreen, which is someone I’ve had the pleasure of working together with over the past six months. And so he previously led Autonomous AI for Microsoft Research and has published a really great book around that next wave of transformation towards more autonomous systems and the choices to make within that. 

 

And then the second book that I would love to recommend is The Coming Wave by Mustafa Suleyman. Because it really speaks about those societal choices and it speaks about the narrow path that we will have of coming out of this transformation on the good end for humanity and the planet.

 

And so I think for everyone involved in building the future of our society and of companies with AI, I think it’s super important to have that lens and it’s a great book, The Coming Wave.

 

Simone Cicero

Thank you very much. I hope you had a good chat as well on your side and brought to you some new ideas, which is hard with people like you who have so much ideas already. So happy for our little contribution. And Shruthi, thank you so much for your questions and being with us today.

 

Shruthi Prakash 

Thank you. Thank you so much.

 

Philippe De Ridder

Thank you so much. It was great.

 

Simone Cicero

Thank you. And our listeners, as always, you will find on our website, www.boundaryless.io/resources/podcast. You will find a Philippe’s conversation with all the transcripts, all the notes. You will also see all the recommendations. And you can find more information on where to connect with Philippe’s work, and a lot is, you know, conversations, and so on. So, in the meantime, please, as always, remember to think Boundaryless.