Most enterprise AI initiatives fail for operational reasons, not technical reasons.
Teams usually have access to capable models and platforms. The breakdown happens between strategy and execution.
The Three Gaps
1. Role Clarity Gap
Teams know they need AI, but do not define who owns:
- model selection
- risk approval
- quality assurance
- production monitoring
2. Process Gap
Pilot efforts succeed because they receive special attention. Production efforts fail because they lack repeatable process.
3. Accountability Gap
Without clear standards, outcomes cannot be attributed or improved reliably.
What Works
High-performing teams move from ad hoc experimentation to governed delivery:
- define a single operating model for project intake and prioritization
- create review gates for risk, quality, and rollout readiness
- measure delivery outcomes by cycle time, defect rate, and adoption
Tooling matters. But operating discipline matters more.