OPERATIONS

A handoff should feel like progress, not failure.

An AI employee should complete the work it is authorised and equipped to handle. When judgment, sensitivity, approval, or an unusual request falls outside that boundary, the correct action is to involve a person. The quality of that transition often determines whether the customer still trusts the experience.

A weak handoff makes the customer repeat the story, search for another channel, or wait without knowing who owns the request. A strong handoff preserves momentum and gives the human teammate the context required to continue.

Define handoff conditions before launch

Do not rely on a vague instruction to “escalate when needed.” Write specific conditions for the workflow. These may include low-confidence answers, requests outside approved knowledge, complaints, payment or legal questions, repeated misunderstanding, explicit requests for a person, or actions that require approval.

Give the employee a clear response for each condition. It should explain what is happening, collect only the information that is useful, and set an honest expectation about the next step.

Transfer a useful context package

The receiving teammate should not need to reconstruct the conversation. A practical handoff package includes:

  • the customer’s stated goal and preferred channel;
  • a concise summary of the conversation;
  • the approved sources already consulted;
  • actions attempted and their outcomes;
  • the reason for handoff and any urgency signal;
  • the next step the customer was promised.

Make ownership visible

Someone must own the request after the transfer. Route it to a named team or queue, record the handoff time, and make the status reviewable. If no person is immediately available, say so clearly and provide a realistic follow-up expectation.

The customer should never have to manage the boundary between automation and the team.

Review the handoff as a product surface

Measure how often handoffs occur, how quickly people respond, whether customers repeat information, and whether the receiving teammate has enough context. Review false escalations and missed escalations separately. Over time, these patterns show where knowledge should improve, where a tool permission is missing, and where the boundary should remain human.