When Agents Hand Back to Users: Service Design for AI Agents

More and more companies now use AI agents: AI that doesn’t just answer questions but takes actions, like processing a refund, approving an expense or updating a record.

When the agent gets stuck, or a decision is too risky, it hands the task to a member of staff. That’s becoming routine- but trust is central: 63% of companies now require a person to check what their AI agents do, up from 22% a year earlier (KPMG).

The problem is that few companies design the handoff from the employee’s side: what they receive, and what they can do with it. So the employee gets a task with no summary of what the agent already tried. Nobody is responsible for it while it waits. And the customer has to explain everything again.

Your AI agent just gave up. Now what?

Agents pass tasks to a member of staff. They open it. No summary. No record of what the agent tried. No idea who’s meant to deal with it.

So they start from scratch. And the customer explains everything again.

Basically: The AI worked but the handoff collapsed.

This is now routine and why 63% of companies require a person to check what their AI agents do, up from 22% a year earlier (KPMG).

Getting it right takes two lenses

➡️ UX: what the customer sees when the agent steps back, and what the employee sees when they step in.

➡️ Service design: when the agent should stop, what information goes with the task, and who owns it while it waits. See Deconstructing AI-First Service Design

In this Lightning Lesson, When Agents Hand Back to Users: Service Design for AI Agents, Frank Spillers will demo an agent-employee hand-off and show how to approach careful consideration of guardrails, protecting customer trust alongside mapping end-to-end experience requirements.

What you’ll learn