Getting AI right takes more than information. It takes experience.
I work with leaders and their teams to build and scale the judgment to get AI right.
Over fifteen years leading product and technology organisations, from data science and AI at Quantium to scaling at wefox in Berlin.
The leadership teams that move confidently on technology are the ones whose leaders can see clearly what to invest in, and what not to. Without that clarity, organisations waste millions on the wrong bets, or watch promising initiatives lose momentum before they deliver.
Today, I work with CEOs and leadership teams to build the confidence, the capability, and the conditions for AI to work across the organisation - not as a series of experiments, but something the organisation owns.
The organisations that get AI right do not start with the technology. They start with which problems are worth solving, in what order, and whether the organisation is set up to act on what it learns. Most haven't built that discipline yet. The few that have need to scale it as they accelerate.
The Work Was the Teacher
Producing raw work was never only about the output - it was how judgement got built, and how a manager read who had it. As AI takes over the doing, we're asked to verify more with expertise we're building less, unless we put the formation back in on purpose.
Hand It Over, or Think It Through?
Being good at AI is usually framed as fluency with the tool. The real test is whether the work can be cheaply checked - hand that over and let AI run it - or whether it turns on judgement you could never verify, where you keep the pen and use AI to think against rather than decide for.
Before You Decide Who Owns AI, Answer These Two Questions
The debate over who owns AI is premature. Two questions come first - what AI is actually for in your business, and what you say when someone asks how you use it - and answering either one well depends on the leader having worked with AI directly.