Error recovery is the AI agent’s ability to handle misunderstandings, failed actions, and unexpected situations gracefully. Effective recovery maintains conversation flow and caller confidence when things do not go as planned.
What types of errors require recovery?
Common errors include misheard speech, unrecognized intents, failed API calls, ambiguous requests, and out-of-scope questions. Each requires different recovery strategies, from simple clarification requests to graceful explanations of limitations.
Why does error recovery matter?
Errors are inevitable in voice conversations. Background noise, accents, unclear requests, and system issues all cause problems. How the AI handles errors determines whether callers become frustrated or feel supported. Good recovery feels natural; poor recovery breaks trust and often leads to escalation.
Error recovery in practice
An API call to check appointment availability fails due to a system timeout. Rather than confusing the caller with technical details, the agent says: “I’m having trouble accessing the schedule right now. Let me try a different approach.” It attempts an alternative method or offers to call back in a few minutes with the information.