# Team AI charter

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

One page that records how your team applies the ten principles: approved tools, data classification, checkpoints, sources, agents and who to contact when something goes wrong.

## Approved AI tools (principle 3)

List the AI tools and accounts the team may use for work, and what each may be used for. Include assistants built into software you already use.

Lumen’s work assistant, under the company contract, for drafting, summaries and research. The CRM’s built-in assistant for account notes. No personal AI accounts for client information.

## Data traffic light (principle 3)

Say which kinds of information are green, amber and red for your team, with examples from your own work.

Green: our public help articles. Amber: internal roadmaps and team notes. Red: customer contracts, support tickets with personal data and anything from a customer’s systems.

## Human checkpoints (principle 1)

List the AI tasks the team repeats and the level for each: AI drafts, AI proposes, AI acts within limits, or you do it. Link to the checkpoint map if you have one.

Drafting replies: AI drafts. Refunds and credits: AI proposes, a team lead approves. Tagging tickets: AI acts within limits. Decisions about renewals and people: you do it.

## Where our facts live (principle 2)

Name the official home and owner of the facts the team uses most, and how people report a mistake.

Prices: the Pricing 2026 page, owned by revenue operations. Refund policy: the legal wiki, owned by Marta. Mistakes: post in #source-fixes.

## Agents we share (principle 4)

List each shared agent, its owner and where its permission card lives. Say who can switch it off.

Ticket triage agent, owned by Jon. Permission card in the team wiki. Jon or any team lead can pause it.

## Skills and learning (principle 5)

Say how people keep their core skills and how new colleagues learn to use AI well.

New colleagues answer their first 20 tickets without AI, then with it. A monthly 30-minute review of one AI-assisted case.

## Decisions (principle 6)

Say how the team makes sure decisions meet the case against them.

Every decision note includes the best argument against it and why we’re going ahead anyway.

## Verification levels (principle 7)

Say which outputs get a glance, spot checks or full verification.

Internal notes: a glance. Replies to customers: spot checks on names, dates and amounts. Anything contractual or published: full verification and a second reader.

## Norms for what we send (principle 8)

Agree simple norms for AI-assisted messages and documents.

Summary first. Customer replies under 150 words. Drafts that still need checking are marked as drafts.

## Disclosure (principle 9)

Agree when the team tells customers, colleagues or the public that AI played a part.

Our chat assistant introduces itself as an AI. Help articles drafted with AI are reviewed by a person. Realistic images of people are always labeled.

## When something goes wrong (principle 10)

Name the contact for AI problems and how the team shares near misses without blame.

Contact: the support operations lead. Near misses go in the retrospective held every two weeks, no names needed.

## Owner and review date

Name who keeps the charter current and when the team will review it next.

Owner: Priya, team lead. Next review: in six months, or when we add a new agent.

## 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/team-ai-charter
Licensed under CC BY 4.0: https://creativecommons.org/licenses/by/4.0/