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.
Trust nothing and verify everything: Why the best AI policy in law wasn't enough
Sullivan and Cromwell had the best AI verification controls in the legal profession, and they still filed 40 fabricated citations in a federal court - this is what the failure tells us about how human judgment interacts with AI output, and what firms can do differently.
What separates leaders who get value from AI?
Most organisations invest in AI training. The research suggests the skill that actually matters is one they already have - but have not connected to AI.
Experience and the AI Adoption Gap
The adoption gap is shaped less by the technology and more by the experience leaders have with it.