5 min readAI leadership
Why most AI pilots stall, and the three things that fix it
95% of organisations report no measurable return from generative AI. The 5% that do share three habits, and none of them is choosing a better model.
By Gary Kellett, architect, fractional CTO and chief AI officer
MIT's 2025 study of generative AI in business found that 95% of organisations saw no measurable return. RAND found the most common root cause of AI project failure is simpler still: people misunderstood the problem they were trying to solve.
In my experience the pilots that stall share a pattern. They start with a tool rather than a process. They are judged on a demo rather than a number. And nobody owns them once the workshop ends.
The fix is unglamorous. Start with one process that runs every week and costs real hours. Agree the before-numbers in writing. Build it on real data, not a sample. Then give it an owner who is measured on the result.
That's exactly why I offer the first automation free. It forces both of us to pick a process that matters, measure it honestly, and prove it in the real world before anyone signs anything.