MIT says 95% of AI pilots never make it past the demo, and the number hasn't moved in 2026. The failure is almost never the model. It's operating discipline. This piece breaks down what separates the 5% that reach the P&L: a use-case backlog built from real work, governance set before scaling rather than after the audit, and a named human owner on every AI output. Plus why four-to-six-week sprints beat six-month decks, and the three questions to ask before anything ships.
