After the AI Hype Comes the Real Revolution

Last January I wrote about Laloux and what AI does to our view of people in organisations. In April I looked at the Wild West of LLM use, where employees experiment while company policy lags behind. This time it is less about tools and more about the bet you are placing on the kind of AI future your organisation is heading towards.

Gillian Tett makes an important point in the Financial Times. Current Big Tech valuations rest on a seductively simple idea: today’s large language models will stay dominant, and the only rational strategy is to pour billions into the data centres and chips that power them. Markets behave as if the game is already over.

Meanwhile, researchers around the world are working on alternative forms of AI. Some try to mirror how humans build a mental model of the world, others mix statistics with logic and explicit knowledge. They are not yet ready to replace the current generation, but they signal something crucial: this revolution is still in its early stages and there may be several technological paths to “intelligent” systems.

That is where it gets interesting for you as a leader. Most organisations do not build LLM's, they buy it. You sign contracts, move key processes onto a specific platform and teach your people to work in that ecosystem. Whether you name it or not, you are placing a clear bet on a particular technology, vendor and way of working.

If the underlying technology shifts, can you move with it, or do you find yourself locked into expensive dependencies that suit the vendor more than your strategy? That is not just market risk, it is architecture risk and, above all, leadership risk.

So the real question is not whether your organisation is “doing something with AI”. Almost everyone is by now. The question is whether you have people at the top who are explicitly responsible for thinking beyond the hype. Leaders who understand that several AI trajectories are emerging in parallel and that the choices you make today shape your room for manoeuvre tomorrow.

If you notice that the AI conversation in your organisation gets stuck on tools, pilots and glossy slideware, you do not have an IT problem, you have a people problem. You need leaders who can turn this noisy landscape into a few clear decisions: where AI genuinely adds value, which risks you are willing to take, and how you keep enough flexibility to adapt when the technology shifts again.

If you’d like to explore how to find, select and define the roles of leaders who can make this topic tangible and meaningful in the strategy, tactics and operations of your organisation, you’re very welcome to get in touch.

Warm regards,

Aegeus