Almost every company I talk to wants to ‘do something with AI’. Few know which concrete problem they want to solve. And that's the difference between an initiative that creates value and an experiment that stays a pretty demo.
Start with the problem, not the model
The right question isn't ‘where do we put AI?’ but ‘which process or decision costs us time, money or quality?’. Once you have that map, you prioritise by impact/effort and pick one or two cases to take all the way to production.
One pilot in production beats ten demos
Real learning begins when actual users touch the feature. Cost, latency, edge cases and answer quality are only truly understood in production, with clear success metrics defined upfront.
AI is not a strategy. It's a lever in service of a product strategy that should already exist.
If your product lacks a clear north-star metric, AI won't invent one for you. But if you have it, AI can become the most powerful multiplier you add this year.
