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Glossary · Updated Oct 22, 2026

Shadow mode

Shadow mode is a way to test an AI system by running it on live inputs while its output is recorded for comparison but never acted on.

In shadow mode the system sees the same real cases your team handles, but nothing it produces is written to a system of record or sent to a customer. You then compare what it would have done with what your team actually did, which shows how it behaves on live data that a test set may not cover.

Shadow mode sits between offline testing and a pilot. It is a stage with an exit condition, such as agreement with the team holding steady over a defined period, not a permanent state. Its limit is that it proves the output is right, not that the surrounding workflow is ready, so approvals, error handling and a way to switch back still need testing before the system is allowed to act. Evals on a held-back set of past cases usually come first.

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