Generative AI in production: from prototype to real value

Many generative AI projects get stuck at the demo stage. The difference between a prototype and a product lies in evaluation, integration with real data and governance.

Starting with a small, measurable use case, defining quality metrics before building, and keeping a human in the loop for sensitive decisions are practices that reduce risk and speed up adoption.

Finally, operations matter: monitoring responses, costs and quality drift should be part of the product from day one.