01
Decide
Set boundaries, responsibilities, and risk decisions for AI use.
AI governance
Govern AI in a way you can explain and test.
AI governance is the system an organization uses to decide how AI may be used, who is accountable, how risks are handled, and what evidence shows those decisions are working.
Start here
AI Governance Foundations
Use the four-part series in order or jump directly to the problem you are working on.
01020304
What Is AI Governance?
Start with a practical definition and the structure behind accountable AI oversight.
Roles and Accountability
Define ownership, decision rights, escalation, and evidence of accountability.
Risk, Controls, and Evidence
Connect risk decisions to controls, records, monitoring, and testing.
Independent Assurance
Understand readiness, independent review, audit, and certification.
Applied risk
Catastrophic AI Risk
Use a five-part practitioner series to connect frontier-AI safety, severe-harm analysis, downstream dependencies, controls, evidence, and audit questions.
Current analysis
AI Governance in Practice
Follow developments that change what organizations, auditors, and assurance providers need to prepare for.
California · Analysis
AI Auditor Registration Is Becoming a Requirement in California
Understand the registration, independence, evidence-retention, and verification requirements taking shape in California.
Read the analysisReferenceAI Governance Glossary
Look up sourced definitions for AI governance, AI management systems, responsible AI, independent assurance, risk assessment, and more.
Browse definitionsA useful mental model
Governance Should Leave Evidence
A policy can state an expectation. Governance also needs people who own decisions, controls that put those decisions into practice, records of what happened, and a way to test whether the system works.
02
Operate
Put those decisions into controls, workflows, oversight, and records.
03
Test
Use evidence to evaluate whether the controls and governance process actually work.