When AI helps decision-loop explainability and when it does not

AI can help explainability when it reduces search cost, prepares decision context for inspection, summarizes recurring patterns, or surfaces exceptions for human review.

It does not help when it hides uncertainty, weakens ownership, or produces outputs that cannot be traced back to source context.

The right boundary is assistance that sharpens judgment, not automation that obscures it.