aia-generation

To conduct an AI impact assessment, run a guided intake to capture what the AI does and affected parties, classify regulatory obligations across your footprint, and run a policy consistency diff to output required conditions and handoff flags.

Yes, you can generate a structured AI impact assessment for high-risk scenarios like HR résumé screening. It derives the appropriate risk track, cites controlling primary sources, and provides verification guidance for governance review.

Yes, the AI impact assessment process includes a policy consistency diff that checks alignment with your house AI policy commitments. It identifies gaps and outputs required conditions plus handoff flags for privacy or vendor review.

The best way to classify regulatory obligations for an AI system is to evaluate the use case against your configured regulatory footprint. This identifies applicable obligations and risk tiers while ensuring source attribution and citation expectations are met.

Automated regulatory classification provides structured documentation and citations, but it requires loading a house-style structure and configured footprint. It outputs verification guidance and handoff flags, meaning final legal review and sign-off remain necessary.