Automation for decision support should make trade-offs explicit, assumptions inspectable, and ownership unambiguous. When a system recommends an action, decision owners should immediately understand why that recommendation appears.

A practical first step is to map three elements for each recurring decision:

1. Who owns the final call.
2. Which signals and evidence they trust.
3. What risk threshold triggers escalation.

From there, automation can improve quality without reducing accountability. The strongest implementations do not attempt to replace judgment; they reduce repetitive cognitive load so judgment can be applied where it matters most.