# Human checkpoint map

Fictional example: the refunds task of the customer success team at Lumen, an invented software company.

For each AI task your team repeats: the level of oversight, who approves what, what they see and how to stop and undo.

## Task

Describe the task in a few words, as the team would say it.

Refunds for billing complaints.

## Level

Choose one: AI drafts, AI proposes, AI acts within limits, or you do it.

AI proposes.

## Why this level

Answer the three questions: can it be undone, who else is affected, and what it costs if it’s wrong.

Refunds are hard to reverse once paid, they affect customers and revenue, and mistakes cost money and trust.

## Who approves

Name the role that approves, and a backup.

The team lead on duty. Backup: the support operations lead.

## What they see before approving

List what the reviewer needs to decide: the exact action, the amount, the recipient and the evidence.

The customer, the amount, the policy clause the agent cited and the draft reply.

## Limits enforced by the system

Write the limits set in permissions or settings, not just in the prompt.

The agent can create refund requests but can’t issue them. Requests over €200 need a second approver.

## If nobody responds

Say what happens when the approver doesn’t answer. Silence never counts as approval.

Requests wait. After four hours, the backup is notified.

## How to stop and undo

Say who can pause the task and how to reverse its effects.

Any team lead can pause the agent. Refunds requested in error are canceled before payment.

## Review date

When will you check that this checkpoint still works?

Monthly, alongside the refund report.

## Review

Owner: 
Agreed by: 
Date agreed: 
Next review: 

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From The RUAI Standard (2026 edition), developed by Founderz in collaboration with Microsoft. https://responsibleai.founderz.com/toolkit/team-tools/human-checkpoint-map
Licensed under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/