Governance
From policy to practice: testing AI governance
An AI policy describes intent. Testing governance means examining whether that intent consistently shapes system selection, use, review and escalation.
Look for repeatable decisions
Operational governance should produce recurring evidence: approvals, classifications, oversight records, exceptions and review outcomes. If the same question is resolved differently across teams, the control may not be sufficiently defined.
Review the difficult cases
Governance is most informative at boundaries, such as experimental tools entering production, vendor features changing after approval, or outputs influencing decisions without a clear human review step.
These cases test whether owners understand their authority and whether escalation mechanisms are usable in practice.
Improve from evidence
A governance review should lead to specific changes in ownership, records or controls. The objective is a clearer operating system, not a larger collection of policy language.