Governance Domain
AI Governance
Turning AI policy into named ownership, risk decisions and evidence, not documentation alone.
Part of Emerging Technology Governance
Overview
Built on the OPERA methodology: named owners, a consistent risk evaluation model, and an assurance structure that keeps pace as use cases multiply. The goal is an operating model that survives a real audit, not a policy document that sits beside one.
Focus Areas
- AI use-case inventories and risk registers
- Ownership and decision-rights models for AI governance
- Risk evaluation criteria and escalation paths
Related Insights
Judgment Over Frameworks
A framework tells you what questions to ask. It does not make the decision for you. Most governance failures happen after the framework has already been applied correctly.
6 min read
What Boards Actually Need to Ask About AI
Board oversight of AI usually stops at 'do we have a policy.' The more useful question is who owns each decision the policy describes.
4 min read
Related Resources
AI Governance Maturity Framework
Assess where AI governance actually stands, across ownership, risk evaluation and assurance, built on the OPERA methodology.
AI Governance Decision Playbook
Use-case risk evaluation, escalation triggers and sign-off criteria for the decisions AI governance actually requires.