Clarity not Data

The leaders of tomorrow won't be systems builders

Years ago I wrote a piece called “Are we doomed?” and I remember the feeling very well: megacities literally sinking while oceans keep warming, democracies losing their balance, and technology accelerating faster than our capacity to absorb it without breaking something in the process. It was as if we were building systems bigger than us, then acting surprised when those systems started to dictate our behavior.

For most of my 25 years in tech, I genuinely believed that more data would bring more clarity, because that’s what we were selling ourselves: more ERP, more CRM, more dashboards, more “visibility”, more control. The promise was simple: if we can measure everything, we can manage everything. But in the real world, it rarely worked that way. Most of the time, it was the same old story: garbage in, garbage out, except now it had a polished UI and a nice chart in a board pack.

What bothered me with time is that we were not measuring reality; we were measuring ourselves, our processes, our internal language, our own biases turned into KPIs. Slowly, almost without noticing, we outsourced judgment to dashboards; not because they were right, but because they felt objective, neutral, scientific. They were not. They were just scalable, and scale is seductive because it hides the fact that you can be consistently wrong at speed.

The real mistake was not that we used data, but that we optimized the wrong layer. We optimized control instead of impact, reporting instead of outcomes, structure instead of value, and we got very good at it.

Meanwhile, biodiversity kept declining, mental health deteriorated in societies that supposedly have everything, and capital kept flowing to the same places, reinforcing the same incentives, because the system is designed to reward what is easy to count rather than what is important to protect.

Then AI arrived, and it didn’t feel like another heavy system you need two years to implement with a consulting army in the background. It arrived more like a collapse in the cost of intelligence, and once that happens, you can’t unsee it: a small team can now do in weeks what used to require years, budgets, and institutional permission. That’s exciting, but it’s also dangerous for the same reason.

Because AI won’t save us. It can help us move faster, yes, but speed is not direction; it just amplifies whatever you already are. If your incentives are wrong, you will scale the wrong thing with more elegance. Technology does not fix incentives; leadership does, and incentives are a leadership choice, whether we admit it or not.

What is strange is that for the first time in a long time I feel optimistic again, not because I believe in automation as a magic wand, but because clarity is becoming cheaper. We can measure impact in ways that were too costly before, we can simulate second-order consequences instead of pretending the world is linear, we can prototype solutions without asking permission from ten layers of hierarchy, and we can reallocate capital based on evidence rather than narratives—if we choose to do it.

So no, I don’t think we are doomed. I think we were simply optimizing the wrong layer for too long, confusing management with progress and dashboards with truth. Now the constraint isn’t really technology anymore; the constraint is maturity, and maturity is not a software problem. It’s a leadership question, and a cultural question, and honestly, a personal one too.

For the first time in my many months, I am feeling very very optimistic again as I see a path where our current and future leaders will finally stop using data to feed their financial forecast and bring back human in the equation. There is no doubt the financial system has not optimised for compassion. We now have the tools to change it.