AI-to-Human Handoff Patterns That Actually Work

Poor handoffs are the leading cause of low CSAT scores in AI agent deployments. The customer has already explained their problem to the agent — being forced to repeat it to a human is infuriating. The warm handoff pattern solves this: the agent prepares a structured summary (issue, steps taken, customer sentiment, recommended action) and delivers it to the human agent before the connection transfers. The threshold handoff pattern automatically escalates when the agent's confidence drops below a set level — preventing the agent from confidently giving wrong answers. The time-based handoff pattern escalates after N turns without resolution — stopping agents from running loops that frustrate customers. The sentiment-based handoff monitors tone and escalates when frustration signals appear. The best deployments combine all four and tune the thresholds based on weekly review of escalation transcripts.