/ insufficient evidence / AI uncertainty / verification
When AI Should Say Not Enough Evidence
A verification system earns trust when it can refuse to overstate what the case file proves.
Why it matters
One of the most valuable outputs in verification is not a score. It is a clear statement that the evidence is not enough. Buyers need systems that can admit missing identity, stale documents, weak provenance, or unresolved payment mismatch instead of forcing every case into a confident answer.
Evidence to collect
Define missing-evidence triggers: no original license, no beneficiary match, no product-specific documents, no source date, unclear production site, or unresolved relationship between seller and factory. These triggers should appear in the case file.
How to review it
The system should explain what evidence is missing and what the buyer should request next. This turns uncertainty into an action list rather than a dead end.
Where buyers get misled
Teams get misled when AI fills gaps with plausible language. A fluent paragraph can hide the fact that the core evidence is absent. That behavior is dangerous before payment decisions.
Practical next step
Add a formal Not Enough Evidence status. It should block automatic clearance and generate a targeted request list for the supplier or analyst.
Working checklist
- Define missing-evidence triggers.
- Use an explicit uncertainty status.
- Generate request lists.
- Block auto-clearance for critical gaps.
- Review cases after evidence arrives.