At the Panoramai AI Summit, Philippe Van Caenegem, partner at Evident, delivered a strategic foresight analysis examining AI's potential trajectories. Drawing on his experience as an entrepreneur and former Salesforce innovation strategist, he provided frameworks for understanding AI's transformative potential and risks.

Strategic Scenario Framework

Philippe structured his analysis around three scenarios: « I took the liberty, if you can pull up just a few visuals, to create three scenarios. Very simplistic. Typically we go much deeper, but for the nature of four minutes. And the scenario work is just centered around the good, the bad and the ugly to make it simple. »

Renaissance 3.0: The Optimistic Vision

« In the good, we're reaching Renaissance 3.0, right. We know there's a little bit of challenges in the world, but we've overcome them. And how did we overcome them? Well, we overcome them thanks to all these intelligent tools that at the same time gave us a little bit of a mirror on humanity. »

Philippe drew on economic research: « There was an economist called Gruber who made a big study around bullshit jobs. It's his statement that there would be around 60% of what is done in the economy is considered a bullshit job. Meaning if from one day to the other, it disappears, nothing changes. Right. And they're often not fun. » In this scenario, AI eliminates meaningless work while helping structure resources toward energy solutions and universal education.

The Bad: Over-Optimization Dystopia

« The bad is the other danger... So these systems have started doing that. They took away everything, they optimized everything became metrics. » Philippe referenced Drucker's warning: « the worst thing you can do for productivity is make tasks more efficient. That should not exist at all. That should not have existed to start with. »

The result: « Humanity has been managed by these systems. They took over, they gradually started to optimize everything in our living realities, including the education, including how free we were to think, including the creative sector. It became all a little bit dumb and grayish and boring and perhaps not a life worth living for many people. »

The Ugly: Systemic Collapse

« The ugly is a much bigger sudden societal collapse... So all of a sudden we find ourselves in a world where there's multi agent systems because there's this compete, right? Nobody wants to be the least good agent. And so there's an infighting of these multi agent systems. » This leads to infrastructure sabotage and system failures in energy, water, and other critical sectors.

European Strategic Positioning

Philippe outlined Europe's potential paths with characteristic nuance. In the positive scenario: « Europe found its role, Europe found its identity, we have the AI act, we embraced... it's all about the equilibrium between how fast, how speedy the new things were coming at us and how fast we could adopt to them. So the adaptation speed versus the adoption speed. »

The negative scenario positions Europe as « well meaning laggards, so our economies have massively suffered because we've over regulated. So there was no innovation, we didn't embrace, we didn't change anything, we weren't competitive with the rest of the globe. »

The worst case involves total technological divergence: « So the tool that should have freed us is all of a sudden only in the us, Perhaps also China, who knows. But we don't have any, right? And so even as consumers we're being over all the time, we're being screwed over all the time. Walmart is building negotiation agents, they're working on that now... if you don't dare to have counter, then also the consumer, the European consumer is not armed. »

Regulation and Innovation Balance

Philippe advocated for smart regulation: « So yes, of course we need regulation. Almost everything is regulated. It's just finding the right balance... something as complex as AI needs to be regulated as close as possible on the skin of the doers. The one that experiment. We need to experiment. We can't stifle innovation, we need to accelerate innovation. »

The Transparency Challenge

« We're growing these things, we're not building it. It's not like a building that you design in advance... So we're growing them. What are we growing them on? We're growing them on data. » Philippe emphasized that « GDPR is just not enough yet » and referenced research showing how embeddings could reveal specific information, making transparency essential.

The Evident Project Vision

Philippe positioned his work as addressing these challenges: « So the Evanden Project, it's a set of initiatives, both technical but especially financial, of creating alternatives for European companies, growth companies, to keep them in Europe... making the tools as transparent as possible, high quality as possible. Basically, we're trying to make sure that the SaaS 2.0, 3.0, whatever you want to call it, is for once built in Europe. »

Data Strategy Foundation

His advice to business leaders was uncompromising: « It's super boring. It's data. Get your data flywheel right. It's just so basic. All the rest will be solved... Like this whole AGI and stuff and dangers and big models and it doesn't matter. Just get the data right and get the data flywheel going and you will create tons of value and gradually all the problems will be solved. But it's all about the data, nothing else. »

Key Achievement: Philippe demonstrated how strategic foresight methodology can illuminate AI's transformation potential, positioning European leaders to navigate between innovation acceleration and responsible development while building competitive advantages through regulatory leadership and data excellence.