AI Agent Escalation Policy
An AI agent escalation policy defines the specific conditions under which an autonomous agent must stop acting independently and transfer control to a human operator, including confidence thresholds, financial exposure limits, regulatory triggers, and retry limits.
Why It Matters
Without clear escalation policies, agents either over-act (taking high-risk actions autonomously) or under-act (escalating everything, defeating the purpose of automation). The escalation policy is the governance layer that makes enterprise AI deployment safe.
The FourKites Perspective
FourKites escalation policies are defined within each AOP and are configurable per customer, per workflow, and per risk level. Common escalation triggers: carrier unresponsive after N contact attempts, delay exceeding N hours, revenue exposure exceeding $N threshold, regulatory or compliance issue detected, agent confidence below threshold. Every escalation includes the complete Decision Trace so the human starts with full context.