of generative AI pilots reach rapid revenue growth.
of agentic AI projects are forecast to be canceled by the end of 2027.
Three reasons pilots stall
- 01
They start with the technology, not the P&L.
Nobody agreed which number should move, so nobody can say whether the pilot worked.
- 02
They prove it can work, not that it pays.
A demo shows feasibility. A budget owner needs evidence of value against a baseline.
- 03
They are not built to be approved.
Risk, security and model-validation teams see the system late, find gaps, and production waits.
What works instead
- 01
Start with the P&L line.
Agree the number, the baseline and the owner, and size the return before anything is built.
- 02
Prove value with a measured prototype.
Build a working prototype on your own data and measure it against that return. Keep it, change it or stop it.
- 03
Build approval in from the first commit.
Evaluation sets, monitoring and human approval steps are part of the design, so the path to production is planned, not discovered.
- 04
Release something people want to use.
A minimum viable product (MVP) earns adoption, and adoption is what moves the number.
Questions to ask about any AI pilot
Which P&L line does this move, and by how much?
What is the baseline today, and who owns the number?
What evidence will the budget owner accept?
What will risk and security need to see, and when do they see it?
What would make us stop?