In An Agentic World Where Automation Gets Cheap, Which Work Is Worth Routing to a Human?

Agentic AI systems are transforming finance by automating tasks like accounts payable, recovering millions of dollars in otherwise unclaimed credits from vendor statements. This automation raises a critical question: when should an autonomous agent act alone, and when is the work valuable enough to require human judgment? A proposed economic framework provides a clear answer by calculating if the expected value of catching an error outweighs the cost of a human's time for review. This risk-adjusted approach means that as the potential financial impact of a mistake increases, the level of confidence required for the AI to act autonomously must also increase.