Agent-to-Human Handoff

Agent-to-Human Handoff is the systematic process where an AI agent transfers control of an ongoing interaction, task, or decision-making process to a human operator when the agent encounters limitations in its capabilities, requires human judgment, or faces complex scenarios outside its training parameters. This critical mechanism ensures service continuity and quality by recognizing when human expertise, empathy, or authority is needed. The handoff typically includes context preservation, where all relevant conversation history, user data, and situational information are seamlessly transferred to the human agent. Effective handoffs maintain user experience while leveraging the complementary strengths of both AI efficiency and human nuanced understanding, making them essential components in hybrid automation systems across customer service, healthcare, financial services, and complex decision-making processes.