Short answer: a useful AI policy fits on one page. It lists the tools your team may use, the data that must never go into them, which work needs human review before it's published or sent, how you disclose AI use, and who owns the policy. Keep it short, train the team on it and review it every quarter.
Who this is for: CMOs, marketing operations and compliance leaders whose teams already use AI, with or without permission.
Why does a marketing team need its own AI policy?
Your team is probably already using AI to draft emails, summarize calls, write ads and clean lists. Without clear rules, customer data ends up in tools nobody approved, off-brand content gets published and claims go out that nobody checked. A company-wide policy often covers security in general terms. Marketing needs specifics, because marketing publishes in public every day.
What should the policy cover?
| Section | What to write |
|---|---|
| Approved tools | Which AI tools and accounts are allowed, and which are not |
| Data rules | What can never be entered: customer personal data, contracts, pricing not yet public, passwords |
| Human review | What a person must check before it's published or sent |
| Accuracy and claims | Every fact, statistic and quote checked against a source |
| Brand voice | How AI drafts get edited to sound like your company |
| Images and rights | Rules for AI images, real people, logos and other companies' work |
| Disclosure | When to tell customers that AI was involved |
| Agents and automation | What AI may do on its own, and what always needs approval |
| Ownership | Who maintains the policy and who to ask |
Which work should always get a human review?
- Anything published under your brand: website pages, blog posts, ads and social posts.
- Emails to customers or prospects, especially anything sent at scale.
- Statistics, customer results, pricing and legal or regulatory claims.
- Anything that names a customer, partner or competitor.
- Changes an AI agent wants to make to your CRM, lists or campaigns.
Internal first drafts, brainstorms and meeting summaries can usually skip formal review, as long as no sensitive data was entered.
How do you roll it out?
- Find out what's already in use: ask the team which tools they use and for what, without blame.
- Approve a short list: pick business accounts with proper data protection over personal ones.
- Write the one page: plain language, with examples of what's allowed and what isn't.
- Train in 30 minutes: walk through real examples from your own work.
- Review every quarter: tools and risks change quickly, so the policy should too.
Frequently asked questions
Should we ban AI tools until the policy is ready?
Usually not. A ban tends to push use onto personal accounts where you have even less control. A short interim rule, such as no customer data and human review before anything goes out, is safer while you write the full policy.
Do we have to tell customers we use AI?
It depends on your industry, location and how AI is used. Be open where AI talks to customers directly, such as chat or automated replies, and check local rules with your legal team.
Who should own the policy?
Marketing operations is a natural owner, working with legal, security and IT. One named person should be responsible for updates and questions.
Rolling out AI across marketing? We help teams pick the right workflows and put guardrails in place. Read how to pick your first AI agent, or request a call.