How institutional decision desks evaluate AI tools

Institutional AI evaluation starts with accountability: what decision loop changes, who reviews output, what evidence is retained, and what happens when the system is wrong.

A credible tool can explain inputs, permissions, retention, lineage, exception handling, and how a reviewer reconstructs the path from context to suggested action.

The demo matters less than whether the workflow can survive governance, review, and ordinary messy market context.