Glass Box AI refers to an approach where every AI-assisted recommendation carries its own explanation by default — the information considered, the policies applied, and the evidence behind the outcome — rather than producing an answer without a visible reasoning path.

Compliance review usually slows down when a system can't explain its own recommendations, forcing reviewers to manually reconstruct context before they can sign off. The delay comes from the AI's opacity, not from the review process itself.

When a recommendation already includes its reasoning, evidence, and policy checks, a reviewer can confirm it directly instead of requesting logs or reconstructing context — turning a multi-step investigation into a single review session.

Ask whether the vendor can show the reasoning behind a specific recommendation, whether the audit trail is generated automatically, whether policy is enforced inside the workflow rather than flagged after the fact, and whether a past decision can be reconstructed by someone uninvolved in it.