Oversight decision policy
Risk-based thresholds for review, approval and escalation
04 / OVERSIGHT
Human oversight.
Define where people review, intervene, override or stop AI-supported decisions.
Explore the processHOW IT WORKS
From AI output to accountable action
Human oversight is effective only when reviewers have enough context, authority and time to challenge the system. A nominal human click is not a meaningful safeguard.
STAGE01
CONTROL FOCUS
AI proposes
System produces an output
EVIDENCE TO CAPTURE
Output, confidence indicators and relevant context
Select any stage to see its control focus and expected evidence.
QUESTIONS TO ANSWER
Make it operational.
Use these questions to turn governance principles into decisions that your organisation can evidence.
- Which decisions require human review before action?
- Can reviewers genuinely challenge and override outputs?
- What happens when a reviewer is unavailable or uncertain?
TANGIBLE OUTPUTS
What good looks like.
Reviewer playbook
Information to inspect, challenge criteria and stop rules
Override & feedback log
Decisions, reasons, corrections and follow-up improvements
MEASUREMENT
Signals worth tracking
Illustrative measures to adapt to your organisation's risk profile and delivery model.
Override rate by use caseTime to resolve escalationsHigh-impact decisions reviewed