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.
What's Covered
- The stark reality: 95% fail, but 5% see millions in returns
- The speed collapse in software development: Why one person can now build in a week what used to take 20 people 6 months
- The operator-engineer: The critical role that makes AI adoption work
- VC portfolio approach: How to think about AI project investments
- Five practical actions: Concrete steps executives can take to enable success
Watch Time
~3 minutes for this condensed version
Interested in the Full Talk?
The complete 30-minute version includes detailed case studies, implementation frameworks, and the "Gravel Road Prototype" methodology. Contact us to schedule a presentation for your team.