AI Policy
AI policy is the set of internal rules that define how an organization approves, deploys, and manages AI systems, what AI use is permitted, what is prohibited, and who is responsible for enforcement.
What AI Policy Actually Contains
A functional AI policy typically covers several categories.
- Permitted use: Which AI systems, models, and tools are approved for enterprise use and under what conditions.
- Prohibited use: AI applications the organization will not deploy, whether for regulatory, ethical, or risk reasons.
- Approval process: How new AI systems are reviewed, risk-assessed, and authorized before deployment.
Layered onto those are the data handling rules for AI, the incident reporting procedures, the roles and accountability structures, and the reference frameworks the policy is aligned against.
Why AI Policy Matters
Policy is the document that lets an organization say what it does about AI. Regulators, customers, auditors, and cyber insurers all increasingly ask for it. Without a documented policy, an organization cannot demonstrate that its AI use is deliberate rather than accidental.
Policy is also the anchor that turns the rest of the AI governance program from ad hoc into systematic. Every control, assessment, and monitoring process traces back to policy requirements.
AI Policy vs. AI Program
Policy is the intended behavior. The AI governance program is what actually happens. A written policy without an operational program is the most common failure mode. Policy that describes controls the organization does not actually have is worse than no policy at all in an audit.
Related Terms
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