use-case-triage

To triage AI use cases, you classify proposed automation or decision support scenarios against an internal governance registry. This process maps each use case to approved, conditional, or not approved outcomes by applying red-line rules and regulatory footprint checks.

AI governance red lines are strict regulatory boundaries that restrict unauthorized use cases. During risk classification, proposed AI scenarios undergo a red-line check across their regulatory footprint to immediately block non-compliant automation, content generation, or decision support tasks.

Yes, you can batch triage multiple AI use cases simultaneously. The process generates a summary table classifying each scenario as approved, conditional, or not approved, then expands the non-approved and conditional items to display specific conditions tables and next-step plans.

Next-step planning for conditionally approved AI use cases involves generating a concrete conditions table. This table outlines required governance steps, assigns a governance tier, and explicitly flags when privacy or product counsel handoffs are necessary for regulatory compliance.

You need to flag a privacy handoff during legal triage when a proposed AI use case involves data processing that triggers privacy regulatory requirements. The triage process identifies these scenarios and routes them directly to privacy counsel for review.

Yes, use case registry classification supports both internal and external contexts. It evaluates AI automation, recommendations, content generation, and decision support applications across both environments to ensure comprehensive governance tiering and compliance.