How to run AI governance at scale
Find answers to the AI governance questions your team faces. These guides give compliance officers, lawyers, GRC teams, and risk managers the steps to put each control in place.
Compare AI governance tools by control domain when you need software. Use the AI governance maturity model to assess your program.
Get the free AI Governance Control Tracker
Get the free Excel tracker for all 136 governance controls. Score maturity, assign owners, and set deadlines, with EU AI Act, NIST and ISO 42001 coverage on a dashboard.
- 136 controls in Excel
- Score maturity and assign owners
- Track deadlines and regulation coverage
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Do we have a complete AI inventory?
Maintain a registry of AI tools, including shadow AI found through procurement reviews, network checks, and employee surveys.
How do we build and maintain an AI model registry?
Keep a model registry with production status, owners, training data, risk classifications, and review dates.
What does audit-ready AI documentation look like in practice?
Keep evidence of responsible AI development, deployment, and monitoring. Prepare for regulatory scrutiny, board questions, and litigation throughout the lifecycle.
How do we build an AI governance program from scratch?
Start an AI governance program with a system inventory. Follow the steps through to ongoing operations.
What AI documentation do we actually need?
Identify legally required AI documentation by risk tier. Distinguish those duties from useful voluntary records and unnecessary paperwork.
What do we do when an AI system causes harm or fails?
Respond to AI failures through detection, containment, investigation, and regulatory notification. Use findings to prevent recurrence.
How do we govern AI models from preview release through retirement?
Govern models from preview evaluation through production approval and retirement. Define reassessment triggers throughout their working life.