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Every AI asset carries a confidence value saying how certain the system is that the asset exists and is described accurately. It is computed automatically from which channels detected it — never set by hand.

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The four levels

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How it is computed

Source count dominates. A second independent channel promotes an asset to verified regardless of which channels they were — because agreement between two blind observers is stronger evidence than either one alone.

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Why multi-source matters

A survey response saying “yes, my team uses ChatGPT” is weak evidence. Someone may be guessing, or describing a trial from six months ago. Watch confidence climb as evidence accumulates:
1

Survey reports HR uses ChatGPT

One source, self-reported → low
2

Browser extension detects ChatGPT in HR

Now two independent sources → verified
3

SDK captures GPT-4o calls tagged business_unit=HR

Three sources, one of them code-level → stays verified, with a richer evidence trail

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Using it

Treat confidence as a triage tool rather than a scoreboard.
  • verified — safe to put in front of an auditor or an EA tool.
  • high — real, but seen through one lens; the business context may be thin.
  • medium — worth a look; often shadow AI nobody has registered.
  • low — a lead, not a finding. Confirm before acting.
A large low-confidence population is not a defect. It usually means your survey coverage runs ahead of your technical coverage — the fix is deploying another channel, which promotes the real ones and leaves the phantoms behind.

Where the sources come from

The channels feeding this calculation, and what each one can and cannot see.