We need a clear, non-bureaucratic AI policy for our staff, but standard corporate templates are forty pages of legal theory. What core operational rules actually belong in a practical company AI policy?

Question

Tyler Smith · Accepted Answer

A functional AI policy fits on a single page. If your team needs a law degree to interpret it, they will ignore it and use unauthorized tools on their personal phones. Your policy exists to protect client confidentiality, assign operational accountability, and eliminate sloppy work.

First, define data boundaries. List exactly what data can never touch an open model. This includes unredacted client financial records, personally identifiable information, proprietary source code, and signed legal agreements. Mandate that employees only use company-provisioned enterprise accounts where model training on inputs is explicitly disabled.

Second, establish absolute output accountability. State clearly that the human sitting in the seat on your Accountability Chart owns every word, number, and calculation delivered to a client or internal team. The excuse that the AI generated a mistake is treated the exact same way as making the mistake by hand. AI drafts; humans inspect, verify, and approve.

Third, mandate disclosure on external deliverables. If a deliverable contains AI-generated analysis or content, the client must receive what was promised in the scope of work. Ban using AI to simulate personal human relationships, such as writing quarterly reviews, sensitive client apologies, or performance management notes.

Keep the policy simple: protect data, verify facts, and own the results. Review it quarterly in your Level 10 Meeting to address new tools, but do not turn common sense into bureaucratic red tape.