Why it matters
AI policy encodes access, response, citation, escalation, and prohibition rules per application. PDF policies nobody operationalizes fail customers at scale.
Durable policy is executable: tied to gates, contracts, tests, and logs stakeholders can read.
Policies fail when exceptions become permanent without owners. Track each exception with expiry and approver or policy becomes Swiss cheese.
Reorgs change who owns policy interpretation. Reassign policy owners explicitly or enforcement drifts.
How it works
Translate policy sections into machine-checkable rules with human-readable mirrors.
Review policy after launches, regulatory changes, and rebrands. Static policy rots.
Track exceptions with owners and expirations. Permanent exceptions become holes.
Align policy training with support onboarding for shared refusal vocabulary.
Pair human-readable policy with executable rules referencing the same section numbers. Dual form increases trust across legal and engineering.
Run policy tabletop exercises: CMS outage, viral wrong answer, regulatory inquiry. Exercises reveal gaps in escalation paths.
Example
Nintendo AI policy requires citations on all billing answers, prohibits guaranteed refund language, and mandates human handoff on legal threats. Tests encode each rule for the chatbot.
Common mistakes
- 1Policy PDFs lawyers never connected to runtime enforcement
- 2Policies too vague to test automatically
- 3Different policies per channel without documentation
- 4No version history on policy changes
Your AI does not need more access. It needs the right access.
Set policies that control what each AI application can read, cite, and answer from.
See AI access policies