Building Your AI Governance Foundation | Nate Pate
AI governance isn’t a future luxury—it’s today’s survival kit. Before regulations lock in and risks snowball, lay down a pragmatic framework that inventories every model, assigns accountable owners, embeds proven standards (NIST, ISO/IEC 42001), and hard-wires continuous monitoring. The action plan below shows how to move from scattered experiments to a disciplined, risk-tiered governance foundation—fast. Waiting for perfect regulations or tools is a recipe for falling behind. Start pragmatic, start now, and scale intelligently. Key Steps: Audit & Risk-Assess Existing AI: Don't fly blind. Inventory: Catalog all AI/ML systems in use or development (including "shadow IT" and vendor-provided AI). Risk Tiering: Classify each system based on potential impact using frameworks like the EU AI Act categories (Unacceptable, High, Limited, Minimal Risk). Focus first on High-Risk applications (e.g., HR, lending, healthcare, critical infrastructure, law enfor...