Many AI products treat review as an operational afterthought: a queue, a table, a status label. But for the people responsible for decisions, review is often the product experience that matters most.
Show why something needs attention
A review surface should not only say that something is pending. It should show the relevant signal, source, change history or user context, and meaningful confidence information when available that explains why a person is being asked to intervene.
Separate priority from noise
AI systems can create large volumes of tasks. Good UX helps teams see urgency, risk and pattern, so they are not forced to inspect everything with the same level of effort.
Make decisions reversible when possible
Review workflows need confirmation, audit trails, undo paths and escalation. This is especially important when actions affect customers, money, health, education or trust.
Design the handoff between machine and person
The transition from automated suggestion to human decision should feel explicit. People need to know what the system did, what it expects from them and what happens after they act.