We need a practical AI usage policy for our team that actually gets followed, rather than a twenty-page legal document that sits in a drawer. How do we write a simple, one-page operational policy that encourages innovation while protecting our IP and client data?

Question

Tyler Smith · Accepted Answer

A successful AI policy must be highly practical and fit on a single sheet of paper. If it is too restrictive, your team will simply bypass it to get their work done, creating a massive shadow IT security risk. If it is too vague, you risk losing proprietary IP or violating client confidentiality.

Your one-page policy should cover three core operational rules:

First, establish data classification boundaries. Clearly state what information can never be pasted into public AI models, such as client names, financial data, and proprietary source code.

Second, define the mandatory human in the loop protocol. State clearly that every single AI-generated output, whether it is an email draft, a client report, or a code block, must be fully reviewed and approved by a human before it is sent or deployed. The human who hits send retains absolute accountability for the accuracy of the work.

Third, list the pre-approved AI tools that the company pays for and supports. Encourage your team to submit new tools for review during your weekly Level 10 Meeting rather than downloading them secretly.

By setting these clear boundaries, you foster an environment of open experimentation while protecting your business assets. Review this policy quarterly during your Rock-setting sessions to ensure it keeps pace with technological changes.