How to Write an AI Acceptable-Use Policy (What to Include)
RedHub AI Editorial5 min read
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TL;DR
- What it is: the written rules for how your team can and can't use AI — the first leg of any governance program.
- Who it's for: founders and ops leads who need a policy their team will actually follow. See the policy builder.
- How it works: cover approved tools, off-limits data, human-review rules, and who to ask — short enough to read, specific enough to settle arguments.
- Bottom line: a good policy is clear, short, and enforced by training — not a legal wall of text. This is a working aid, not legal advice.
What should an AI acceptable-use policy include?
An AI acceptable-use policy should cover five things: which AI tools are approved, what data must never be entered into them, when a human has to review AI output before it's used, who owns questions and exceptions, and what happens if the rules are broken. The goal isn't a legal document — it's a short, plain-English set of rules specific enough to settle real arguments ("can I paste a customer's contract into this?") and clear enough that your team actually reads it. It becomes real when you train on it, not when you file it.
Best for: teams writing their first AI policy — the AI Acceptable Use Policy Builder drafts it for you. A working aid, not legal advice.
An AI acceptable-use policy is the first thing to write when you're standing up governance, and the easiest to get wrong in two opposite ways: too vague to be useful ("use AI responsibly") or too heavy to be read (ten pages of legalese). The sweet spot is a short document that answers the questions your team is actually asking. Here's what to put in it.
The five things every AI policy needs
- Approved tools. Name the AI tools your team is allowed to use, and say how someone requests a new one. A short allow-list beats a vague "use judgment" — it prevents shadow tools no one vetted.
- Off-limits data. Spell out what must never be pasted into an AI tool: customer PII, credentials, source code, anything under NDA. This is the single most important line in the policy.
- Human-review rules. Say when AI output can't be used as-is — anything customer-facing, anything that becomes a record, anything with legal or financial weight gets a human check before it ships.
- Ownership and questions. Name who owns the policy and who to ask when a situation isn't covered. A policy with no owner goes stale the week it's written.
- Consequences and updates. State what happens if the rules are broken and how often the policy gets reviewed. AI tools change fast; a policy that never updates is a policy that's already wrong.
Key insight: the off-limits-data line does more work than the rest of the policy combined. Most real AI incidents at small companies aren't exotic — they're someone pasting something sensitive into a chatbot because no one told them not to.
Keep it short enough to be read
The best AI policy is one page your team can skim in three minutes, not a contract they scroll past and click "agree." Every extra clause you add is a clause someone won't read. If a rule isn't specific and enforceable, cut it. You can always add detail later when a real situation demands it.
A policy only counts if people follow it and somebody is accountable for the decisions it governs. The free AI Governance Gap Assessment asks 22 questions about exactly that, and deliberately names no framework. Self-assessment, not an audit and not legal advice.
Draft your policy in an afternoon
The AI Acceptable Use Policy Builder walks you through approved tools, off-limits data, and review rules and produces a policy tailored to your business — the Policy leg of the governance program.
Get the AI Acceptable Use Policy Builder — $69 →A policy is only leg one
Writing the policy is the start, not the finish. A policy nobody trained on doesn't change behavior, and a policy with no evidence behind it can't answer a reviewer's question. That's why the policy is one leg of a three-leg program: Policy sets the rule, People (training) make it real, and Proof (records) make it defensible. If you only ever write the policy, you've done the visible third and skipped the two that make it work.
A good policy is
- Short and plain-English
- Specific enough to settle arguments
- Backed by training and review
A bad policy is
- Vague ("use AI responsibly")
- Ten pages nobody reads
- Written once and never updated
See the full model in the Policy-People-Proof framework, or the whole 90-day plan in AI governance for small business.
Decision Guide
Use it if: your team uses AI and you have no written rules for it yet.
Skip it if: you already have a current, trained-on acceptable-use policy that covers AI specifically.
Best first step: write the off-limits-data line first — it prevents the most common real incident — then fill in approved tools and review rules.
FAQ
What is an AI acceptable-use policy?
It's the written set of rules for how your team can use AI: which tools are approved, what data is off-limits, when output needs human review, and who to ask. It's the first leg of a governance program — the rule that training and evidence are built on.
What's the most important part of the policy?
The off-limits-data line — what must never be entered into an AI tool (customer PII, credentials, source code, anything under NDA). Most real AI incidents at small companies come from someone pasting sensitive data into a chatbot because no rule told them not to.
How long should an AI policy be?
Short — ideally about a page your team can skim in a few minutes. Every extra clause is one someone won't read. If a rule isn't specific and enforceable, cut it; you can add detail later when a real situation calls for it.
Is a template enough, or do I need the whole program?
A template gets you the policy, but a policy alone doesn't change behavior or produce evidence. To actually govern AI you also need training on the policy (People) and records that show it's followed (Proof). The policy is leg one of three.
Is this legal advice?
No. A policy builder and this guidance are working aids, not legal advice or a conformity assessment. For a policy that has to satisfy a specific law or contract, have qualified counsel review it before you rely on it.
How often should I update the policy?
Review it on a set cadence — at least once or twice a year — and whenever you adopt a new AI tool or a new rule you care about. AI tools change quickly, so a policy that never updates drifts out of date fast.
Write the policy, then make it real
Approved tools, off-limits data, review rules — the policy leg of a real governance program. A working aid, not legal advice.
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