The automated or manual mechanisms that ensure AI operations adhere to organizational policies, regulatory rules, and ethical guidelines.
The set of technical controls (e.g., policy-as-code gates, admission controllers, automated audits) and human-review processes that validate compliance at runtime and deployment. Policy enforcement tools intercept model builds, deployments, and API calls - checking against policy definitions (data usage rules, model-risk thresholds) and blocking or flagging any deviations for review.
A financial-services firm codifies its data-retention policy in a policy engine: any storage operation older than the TTL defined for PII fields is automatically purged. If a model-training job attempts to load wiped data, the engine rejects the job and notifies the data-governance team.
