aia-generation

Generate a structured AI impact assessment by inputting an AI use case to capture system description, affected parties, data inputs, oversight, accuracy, bias, regulatory classification, and risk mitigations. The output applies governance tiering and impact criteria to produce a deployment-ready recommendation.

Regulatory classification in an AI impact assessment categorizes an AI use case by applicable regulatory regimes, determining risk tiering, prohibited-practice exposure, and obligations with primary-source citations. It ensures the system meets specific regime requirements before deployment.

Check AI policy consistency by running a policy diff that compares the impact assessment against configured AI policy commitments. This surfaces mismatches requiring changes before deployment, ensuring the AI system adheres to governance frameworks and organizational standards.

A privacy impact assessment handoff is needed when the AI impact assessment outputs privacy review triggers or required conditions. These handoff-ready indicators, including PIA or vendor review flags, direct the workflow to the appropriate privacy stakeholders for further evaluation.

Classify AI risk tiers across different regulatory regimes by capturing the regulatory footprint within the assessment. The system applies regime-specific research-backed tiering to identify prohibited practices and obligations, providing primary-source citations for each classification outcome.

Limitations in AI governance triaging include conditional outcomes based on configured governance tiers and impact criteria. The assessment requires reading house-style and governance framework seed documents from the configured claude-for-legal AIA environment to ensure accurate policy consistency checks.