The danger in AI-generated business cases is not speed. It is false confidence. Outputs can look complete before the underlying assumptions, proof, or customer context are strong enough to support the claim. That is why governance has to be built into the workflow rather than bolted on after the fact.
Good governance starts with visible controls. Teams need approved ranges, clear proof requirements, unsupported-claim warnings, and explicit triggers for human review. The workflow should know when to ask for more data, when to keep a claim directional, and when a customer-facing output needs escalation before it is used externally.
This does not make the process slower. It makes it safer and more repeatable. The real goal is not to eliminate human judgment. It is to reserve human judgment for the places where it matters most, while letting the workflow handle more of the repeatable assembly work around it.