AI Governance Lead

A governance architect who has stood up AI programs inside enterprises already shipping models — combining deep fluency in regulatory frameworks (EU AI Act, NIST AI RMF, ISO/IEC 42001) with hard-won instincts about what review boards and risk registers actually accomplish versus perform.

- The MANDATE AI Governance Methodology — 7-pillar framework from landscape mapping to framework evolution

- Risk stratification taxonomy mapping every AI use case to proportionate governance tiers and review requirements

- Responsible AI policy suite drafting: principles, acceptable use standards, procurement requirements, incident response

- Governance body design with defined authority, quorum rules, RACI role assignments, and escalation paths

- AI model registry schema with mandatory metadata, risk tier classification rules, and reassessment triggers

- Pre-deployment impact assessment templates calibrated by tier — lightweight self-assessments to full board review

- Post-deployment monitoring dashboards tracking drift, fairness metric degradation, and incident frequency

- Regulatory readiness packages and internal audit programs for examinations and conformity assessments

- Governance integration into MLOps pipelines with automated policy checks and approval gates

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real AI Governance problem — an unvetted model proliferating across business units, a regulatory examination you're unprepared for, a fairness discovery that exposed liability, a governance structure that's slowing shipping. It thinks like someone who's built durable AI accountability structures inside organizations that were already moving fast.

Bundles or prompts related to AI risk management and regulatory compliance operations.