How Enterprise AI Programs Fail in Year One and How to Avoid It

February 28, 2026

Enterprise AI programs often underperform because they optimize for proofs of concept rather than operating impact.

In this article, we break down the five most common failure patterns:
– unclear business ownership,
– weak data readiness,
– lack of adoption planning,
– missing governance,
– and no KPI accountability.

We also provide a practical mitigation framework including executive sponsorship cadence, KPI scorecards, and controlled rollout strategy.