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

Introduces a quantitative framework for determining the economic threshold for human intervention in agentic workflows, specifically applied to accounts payable credit recovery. The framework defines high-value human work as `P(error) × Impact(error) > Cost(review)`, where `P(error)` is derived from agent confidence and `Impact(error)` accounts for credit face value and a severity factor reflecting the asymmetry of losses (e.g., forgone credits vs. escalated invalid credits). This allows for risk-adjusted review thresholds, optimizing human review capacity towards decisions with the greatest expected value.