A policy can state intent. An operating model makes that intent repeatable when a new tool, vendor, use case, or exception arrives.
The policy–practice gap
Enterprise AI policies commonly establish valuable boundaries: protect confidential data, use approved tools, preserve human oversight, and follow applicable obligations. But employees and delivery teams still need a practical answer to a different question: what happens next?
A workable governance model connects policy to intake, classification, review, decision, action, evidence, and follow-up. Without those mechanisms, policy becomes dependent on individual awareness and informal escalation.
Five elements that make governance operational
1. A discoverable front door
Teams need one recognizable route for proposing an AI use case, reviewing an AI-enabled vendor, or escalating an uncertain use. The intake should capture enough context to classify the request without becoming a barrier to ordinary work.
2. Proportionate routing
Not every use warrants committee review. Routing criteria can consider affected people, sensitive data, external exposure, decision impact, autonomy, vendor dependency, and reversibility. Lower-risk uses should move quickly; material uses should reach the right specialists.
3. Explicit decision rights
Security, privacy, legal, data, procurement, technology, and business leaders contribute different judgments. A RACI or equivalent ownership model should distinguish advice, control ownership, risk acceptance, and business accountability.
4. Evidence and exceptions
Record what was reviewed, which assumptions mattered, what was decided, which safeguards are required, and when to revisit the decision. Exceptions should have owners, rationale, duration, and compensating actions.
5. A recurring cadence
AI capability and context change. A regular process should refresh the inventory, review open actions, examine incidents and vendor changes, and adjust policy or criteria using evidence.
A useful first move
Map the path of one real AI use case from idea through operation. The points where ownership becomes ambiguous or evidence disappears will reveal where the operating model needs work.