Define who can act and what they can decide.
Identify the operational reviewer, escalation contact and person authorised to stop or restrict use. Describe the decisions each role may make and the support available when a case exceeds their competence. Consider absence cover and conflicts of interest, not just the normal working day.
For high-risk deployers, Article 26 specifically addresses competent, trained and authorised human oversight. An oversight plan should therefore describe practical authority and support, not simply list a nominal human participant.
Set clear intervention points.
Decide when a person must inspect an output before it affects someone, which warning signs require additional review and when the system should stop being used. Explain how to challenge a recommendation, seek further information or take an alternative action.
The appropriate design depends on the use case. A drafting assistant and a system affecting access to an important service need different review arrangements. Avoid using a generic sign-off step for both without examining the consequences.
Record whether oversight works in practice.
Useful records can include review instructions, competence information, overrides, escalations and the reasons behind decisions. Look for patterns: repeated acceptance without examination, frequent unexplained overrides or queues that encourage reviewers to rush.
- Named roles and the authority assigned to them.
- Intervention and escalation instructions.
- Training or briefing relevant to the use case.
- Review outcomes and changes made after feedback.
Build the workflow around real constraints.
EUAIC can help scope the oversight record and connect responsibilities to each AI use case. Discuss workload, time available for review, information shown to the reviewer and the ability to pause a process. These factors determine whether the planned oversight is realistic.
A completed checklist does not prove effective human judgement. Review the process with the people operating it, use representative scenarios and record improvements when the intended intervention cannot be performed reliably.