AI Governance
The operational architecture that makes an AI program defensible under audit and useful under load, governance committees, risk taxonomies, intake processes, model inventories, and board-level reporting that your regulators, operators, and public stakeholders can all read.
- AI governance frameworks — policy operationalization, committee design, intake
- Regulatory readiness — EU AI Act, NIST AI RMF, ISO/IEC 42001, sector guidance
- Model risk & inventory — documentation, tiering, and lifecycle controls
- Board & executive enablement — reporting, training, and decision structures