Oversight requires understanding and control, not merely an approval button.
A person in the loop needs agency
A confirmation is useful only if the person can understand the action and meaningfully reject or change it. A rushed, vague approval may add friction without adding much oversight.
Surface the consequential details
Show what will change, what data will leave the system, who is affected, and whether the action is reversible. Put these details next to the decision rather than burying them in a long log.
Keep intervention possible
Pausing work, narrowing permissions, revoking access, and undoing changes can all support oversight. Design these controls as normal parts of delegation.
The reviewer needs a real opportunity to intervene
Our view is that a human-review step should be judged by what the person can see and change. A reviewer needs the proposed action, relevant evidence, enough time and the authority to stop it. A button clicked after an irreversible action is a notification, not meaningful prior oversight.
Match friction to consequence
OWASP’s agent guidance includes explicit authorization for sensitive operations and human involvement for high-risk actions. In practice, frequent low-value prompts can consume attention needed for the important ones. Design the scope of delegation and the escalation rules together.
Source: OWASP · AI Agent Security Cheat SheetMake uncertainty and recovery visible
A reviewer should be able to tell whether an action completed, failed or has an unknown status. If a tool times out after sending a request, automatically retrying may duplicate the action. Our recommendation is to preserve status and a receipt where possible, and establish who investigates uncertain outcomes.
A situation to think through
Before an assistant publishes a newsletter, the reviewer sees the final subject, recipient list, attachments and content. If the recipients change after approval, the workflow asks for a new decision. After sending, it shows the delivery status and a record of what was approved.
Questions to take with you
- Can the person inspect the actual consequence before it occurs?
- Can they stop or narrow the action without abandoning the whole task?
- Is someone responsible for unresolved or disputed outcomes?
For more reading
The sources behind this page, with a reason to open each one. Practical examples and recommendations are our editorial interpretation.
- AI Agent Security Cheat Sheet
Practical guidance on tool permissions, memory isolation, oversight and agent failure handling.
- Generative AI Profile · NIST AI 600-1
A framework for identifying, measuring and managing generative AI risks across the system lifecycle.
Sources reviewed 13 September 2026. Product documentation can change. How we use evidence