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AI Usage Policy Template: What to Include

#ai #governance

Originally published at https://charz.ai/blog/ai-usage-policy-template by Char-Z AI.

Why an AI Usage Policy Matters

An AI usage policy is the governance baseline that tells employees, contractors, and partners what they may and may not do with AI tools. Without one, acceptable and unacceptable use are decided ad hoc — which is how data gets pasted into the wrong tools and how shadow AI spreads.

A good policy is short, specific, and written for the people who actually use AI, not for lawyers. It names the approved tools, states the data rules plainly, requires disclosure where it is due, and sets consequences. The goal is to enable safe use, not to ban AI.

The Core Sections

1. Scope and audience.

State who the policy covers (employees, contractors, temps) and what it covers (all AI tools, internal and external, on any device).

2. Approved tools.

List the sanctioned AI tools and any restrictions attached to each. Reference your approved-tools process rather than hard-coding a long list that goes stale.

3. Permitted and prohibited uses.

Be explicit. Permitted uses often include drafting, summarization, code assistance, and analysis of non-sensitive data. Prohibited uses typically include inputting personal or confidential data into unsupervised tools, using AI for regulated decisions without human review, and copying model output verbatim into customer-facing material without checking it.

4. Data-handling rules.

State plainly: what data may be entered where. A simple tiered rule works best (see our data-handling guidelines guide):

Public — e.g. published material — rule: fine in any approved tool.

Internal — e.g. company documents — rule: approved tools only.

Restricted — e.g. personal, regulated, confidential — rule: approved, DPA-backed tools only.

5. Disclosure and transparency.

Where the EU AI Act's Article 50 transparency obligations apply — AI interacting with people, deepfakes, or AI-generated content — require disclosure. Tell employees when they must label or announce AI output (European Commission, 2024).

6. Review and human oversight.

Require human review before AI output is used in decisions that materially affect individuals. Prohibit fully automated consequential decisions without a documented approval path.

7. Security and accounts.

Cover use of personal accounts, sharing of company credentials, and device rules. Employees should not use their personal AI logins for company work that touches internal data.

8. Violations and consequences.

State the consequences of breach clearly but proportionately, and match them to the severity (accidental vs. deliberate exposure).

Writing Style That Works

  • Use plain language. Write at the reading level of the audience, not legal density.

  • Give examples. "Do not paste a customer's name, email, or health details into a public chatbot" beats generic "avoid sharing personal data."

  • Keep it reviewable. Set a review cadence (annually) and a named owner for updates.

A Short Template to Adapt

AI Usage Policy — [Company]

  1. Scope: this policy applies to all [employees/contractors] and all AI tools used for company purposes.

  2. Approved tools: use only tools on our approved list. To propose a new tool, follow the [intake process].

  3. Data rule: public data may be used in any approved tool; internal data only in approved tools; restricted data only in DPA-backed approved tools.

  4. Prohibited: do not enter restricted data into unsupervised tools; do not make consequential decisions without human review; do not present unchecked AI output as your own work.

  5. Disclosure: disclose AI-generated content and AI interactions where the law or our client agreements require it.

  6. Violations: [consequences]. Report suspected misuse to [contact].
    Tie It Into Your Governance

A usage policy for employees is one layer of governance. Combine it with vendor management (procurement checklist), data-flow mapping, and an incident plan. Together these make up the practical operating layer that frameworks like the NIST AI RMF describe (NIST, 2023).

Sources

European Commission. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council. *Official Journal of the European Union*. https://eur-lex.europa.eu/eli/reg/2024/1689
NIST. (2023). *Artificial Intelligence Risk Management Framework (AI RMF 1.0)*. National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.100-1
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