Why so many AI pilots never scale (and how to avoid it)

Most AI pilots work in the demo and stop there. Not because the technology fails, but because nobody defined what “working” meant.

Three common mistakes

First, scope that's too broad: a pilot that tries to solve everything can't be measured. Second, no baseline: if you don't know how long the process took before, you can't prove the improvement. Third, no owner: a pilot living in the innovation team never reaches operations.

How we avoid it

We narrow the pilot to one process and one team. We set two or three KPIs before starting. And we name a business owner who decides whether it scales.

Scaling is a business decision, not a technical one. Prepare it from day one.