The AI Adoption Paradox: Why 95% of Companies Fail (And How to Be in the 5% That Succeed)
Why AI pilots fail, why the rare winners matter, and how operators can move from experiments to production systems.
Most corporate AI pilots fail. The ones that work do not fail quietly, they return millions. This short talk lays out the paradox: the technology works well, yet most implementations capture no value. It explains what the winners do differently, including the operator-engineer who makes adoption actually stick.
Most AI pilots fail. But when they work, they deliver transformational results worth millions. In this 3-minute overview of our 30-minute talk, we explain the paradox: AI technology works incredibly well, yet 95% of corporate implementations fail to capture value.
This condensed 5-slide presentation reveals the real reasons AI projects fail and provides a clear framework for success.
Why do most AI pilots fail?
Not because the technology is weak. It works. They fail on everything around it: unclear ownership, messy data, and no one accountable for moving an experiment into daily use. The winners treat AI like a portfolio of small bets and put an operator-engineer on each one, the person who makes adoption actually work.