Why do most AI agent projects fail, and what do the winners do differently?

MIT's much-cited finding is that 95% of enterprise AI pilots deliver no measurable ROI, and the cause is rarely the model: it's missing context, no workflow integration, and celebrating the demo instead of the deployment. LangChain's industry survey adds that quality is the top blocker and teams with observability and evals ship far more reliably. The 5% that win start with one narrow, high-value use case, wire the agent into real systems and data, measure outcomes from day one, and keep a human on the risky steps.

A quick orientation. The real value is below: resources worth your time, from people who've actually done it.