vantage-ai-policy-mapper

To map AI use cases to data governance policies, the Skill matches proposed AI tools against established organizational data classes, policy requirements, and restrictions. It provides an explainable, auditable basis for approval decisions.

AI policy mapping for vendor reviews is the process of matching proposed AI tools against organizational data classes and policy restrictions. It identifies approval blockers and unmet requirements to facilitate AI governance compliance.

You identify approval blockers during risk assessment by mapping the AI use case against existing policy rules and tenant-scoped records. The Skill explicitly highlights unmet requirements, prohibited conditions, and necessary approval conditions.

No, you cannot use this Skill for AI governance without tenant-scoped records. The policy mapping and explicit matching against policy rules require tenant-scoped records to generate an explainable basis for approval decisions.

Yes, AI policy mapping works by requiring explicit matching against policy rules or generated outputs. This ensures the approval or rejection of AI use cases and vendor reviews remains clear, auditable, and grounded in established data governance requirements.

A limitation of automated policy mapping for AI governance is that it requires explicit matching against existing policy rules and tenant-scoped records. It cannot evaluate use cases lacking established organizational data classes or generated outputs to match against.