I’ve been thinking about where human approval actually belongs in an AI workflow.
For low-risk actions like classifying a message or drafting a summary, automatic execution seems reasonable. But the boundary gets less clear when the workflow can send an email, issue a refund, update customer data, or trigger another external system.
Requiring approval for every step removes much of the benefit of automation. Requiring it only after something goes wrong is obviously too late.
Do you define approval rules by action type, confidence score, financial impact, or reversibility? I’m especially curious whether anyone has found a practical way to reduce approvals over time without quietly increasing risk.