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Writing an AI policy a team can apply

An organization publishes its AI policy. It is one line: “Use AI responsibly.” The finance team reads it and decides it means “never paste anything into a chat tool” and stops using AI at all. The support team decides it means “be careful” and connects an agent to the customer mailbox the same afternoon. The marketing team decides it means whatever the last person to speak decided. All three followed the policy. The policy decided nothing, so every team decided for itself, and the organization’s exposure is now the sum of the most careless choice.

In this lesson we write the replacement: a one-page policy with the tasks an agent is allowed to do, the data it is allowed to see, the approvals it waits for, and the person to call when it goes wrong. The worked example is one invented team, the claims team at a small insurer. At the end you fill in the same template for your own team, and you need a chat assistant or a blank document and nothing else.

A policy line is useful when two people on the team, reading it alone, would make the same call. “Use AI responsibly” fails that test. So does “no sensitive data in AI tools”, because each reader decides for themselves what counts as sensitive. A line that passes names the task, the tool, and the data, and says what happens at the boundary.

Here is the claims team’s first attempt, rewritten line by line.

Before After
-------------------------------- -----------------------------------------------------
Use AI tools carefully. The approved assistant may summarize a claim file and
draft the first reply. It may not decide a claim.
No sensitive data in AI tools. Claim files go in the approved assistant only, with the
claimant's name and policy number replaced by the claim
id. Medical reports never go in.
Check the output. A person reads every drafted reply against the claim
file before it is sent, and puts their name on it.

Every “After” line answers a question a team member has on a Tuesday afternoon, such as “can I paste this?” or “what do I do before I send?”. The “Before” lines answer none of them.

Checkpoint · choice

The claims team is choosing one line for the section on customer contact. Which line would two team members apply the same way?

A policy that fits on one page gets read. The claims team’s page has five headings, and any team can fill the same five.

AI policy: claims team Owner: team lead Reviewed: quarterly
1. Allowed tasks What the agent may do, and what it may not decide.
2. Data What may go in, what is replaced before it goes in, what never goes in.
3. Approvals Which actions a person approves first, and who that person is.
4. Logging Where the agent's actions are recorded, and who reads the log, how often.
5. Escalation What stops the agent, who is told, how fast, what is kept, who restarts it.

The owner and the review date are part of the template on purpose. A policy without an owner is nobody’s job to update, and a policy without a review date is still describing last year’s tools.

Sections 1 to 3 are the questions from the agent risk lesson, written down once for the whole team. The blast radius of each allowed task sets what goes in section 2. Least privilege sets how narrow section 1 is. The approval moments go in section 3. Section 4 is new. The agent’s actions are recorded where a person can read them later, because the first time something goes wrong the log is the only record. Recording is only half of it. The claims team names the team lead to read a sample every Friday, since a log nobody reads doesn’t catch anything. A later lesson in this course goes into what a log needs to hold.

Checkpoint · multi-choice

Which of these belong on the claims team’s one page?

Select exactly 2.

The approvals section is where most policies get vague, because the decision feels like it has to be made per task forever. A framing from Anthropic’s course “Deploying Claude Enterprise with confidence” turns it into a rule, paraphrased here in our own words [1].

Treat read access and write access as two separate levels of sign-off. An agent that can only read a system can get a fact wrong. An agent that can write to it can change a record or send a message under the team’s name. So a team starts every agent read-only, and grants write access one workflow at a time, each grant approved by the person who answers for that workflow when it goes wrong. The claims team’s agent reads claim files from the first day. Writing a reply into the outbox is a separate grant, approved by the claims manager, and sending it is a grant the team hasn’t made.

The same course states a fact about connectors that belongs in section 2. When an agent reaches a system through a connector, it acts as the person who connected it, and it sees what that person can see, no more and no less [1]. The corollary is this lesson’s own advice. The connecting person’s access is the agent’s ceiling. The claims team connects the agent from an account that has what the task needs, and never from the account of the person with the most access.

The claims team adds one more line under logging, as its rule for choosing a tool at all. A tool that doesn’t record what the agent did is the wrong tool for a workflow a regulator can ask about, because the team couldn’t answer the question.

Checkpoint · sort

The last section of the page is the one teams skip, and the one they need first. Escalation is the agreed route for the day the agent does something wrong: a reply went to the wrong claimant, a file left the building, the agent approved a claim it should have flagged. The first incident is the wrong time to find out who can revoke the agent’s access.

The claims team’s section answers five questions, each with a name, or a number.

5. Escalation
What stops it Anyone on the team may stop the agent. The button is in the assistant's
settings, and IT can revoke its account.
Who is told The team lead, at once, by phone. Out of hours: the IT on-call.
How fast Within the hour of noticing. A report is never too early.
What is kept The conversation, the agent log for that day, and the affected record
as it is now. Nobody tidies up first.
Who restarts it The claims manager, after the team lead has read the log and written
two lines on what changes.

People report when the route is known, so nobody has to work out who to call while worried, and when the route is blameless, so the person who noticed is thanked and the fix goes into the policy. An organization with that route learns from near-misses. One without it learns only from disasters, and late.

One more line goes under escalation, because it is a change nobody on the team makes and everybody feels. The vendor updates the model behind the agent, and the same instructions now act differently: a format changes, a refusal appears, a shortcut is taken. The claims team treats a model update the way it treats any change to a tool it depends on. Before the agent goes back on live claims, someone reruns it on last month’s files and compares [2].

Checkpoint · scenario

A drafted reply was sent to the wrong claimant, and you noticed. The team’s policy has no escalation section yet. What do you do in the next five minutes?

Checkpoint · repair

This is the escalation section of a policy as drafted. Rewrite it so a new team member who notices a problem knows what to do without asking.

Many vendors sell the same assistant at a consumer tier and at a business or enterprise tier. The pitch of the higher tier is often the sections of this lesson as product features: central control over which tools and connectors are on, an admin’s view of the log, and a promise about data handling. Those features make sections 2 and 4 of your page easier to enforce, but the tier has no way of knowing which tasks your team may hand over or who to call at nine on a Friday evening, and it doesn’t write the page for you. Buy the tier if your organization needs it, and write the page either way.

The questions to ask a vendor before buying are the ones from the responsible use lesson. Put the answers on the page in the data and logging sections.

Exercise

Fill in the five-heading template for your own team, in a document, or in a chat with an assistant that has no tools, using the claims team’s page as the model. Name the allowed tasks and what the agent may not decide, the data that goes in and what’s replaced first, the approvals with the person who gives each one, where the log goes and who reads it, and the escalation route with real names and a time. It should fit on one page.

A good result has a name in every section that needs one, and each rule has one example of a use it allows and one it forbids. If a section reads “use good judgment” or “the appropriate person”, you have written the old policy in more words. Which section was hardest to give a name to, and why is that the section you need most?

Stretch: Show the page to one colleague on the team and ask them to apply section 1 to a task they did this week. Every question they ask is a line to sharpen.

More practice

Extra checkpoints on the same ideas, if you want them. You can finish the lesson without them.

Checkpoint · scenario

The vendor announces that the assistant behind the claims team’s agent now runs on a newer model. Nothing else changed. What does the policy say happens before the agent goes back on live claims?

Recap

  1. A policy line is useful when two team members reading it alone make the same call. “Use AI responsibly” leaves every team to decide for itself.
  2. One page with five headings is enough: allowed tasks, data, approvals, logging and escalation, with an owner and a review date at the top.
  3. Start every agent read-only. Each kind of write access is a separate grant, approved by the person who answers for that workflow when it goes wrong [1].
  4. An agent that connects through a person’s account inherits that person’s access. Give it an account with what the task needs.
  5. The escalation section names what stops the agent, who is told, how fast, what’s kept and who restarts it. The first incident is the wrong time to find out.
  6. A model update is a change to a tool you depend on. Rerun last month’s work before the agent goes back on live work [2].

You can now

  • Sets policy, logging and escalation for agents in an organization

  1. Anthropic. Deploying Claude Enterprise with confidence. Claude Academy. Course. Academy deploying-claude-enterprise-with-confidence
  2. Addy Osmani, Ivar Soares Urdalen, Leo Simons. From prototype to production: eval-gated deploys, rollout, cost. Agent Engineer Course. Course. AEC-11