Core question
What should an AI use policy actually cover?
Short answer
Three questions answer most of it. Who is accountable for what the AI produces? What data is off limits? What is acceptable, what is not, and what is enforceable? Add a clear position on which outputs require human review before they leave the building.
Your policy is not just legal language. It tells your team what is acceptable and what matters, which makes it a culture document as much as a compliance one.
Start with those three accountability questions, then extend into the areas where people actually make judgment calls. Where must AI output be reviewed by a human before release? How do you handle inaccurate or biased output when it occurs? What are your obligations around customer data and regulatory compliance? When and how do you disclose AI involvement in customer-facing work? Who owns governance overall?
Culture shows up in micro-decisions. Should I use an AI tool for this client email? What is okay to automate? Where is the line? Your people are answering those questions right now, one at a time, with no guidance. Clarity drives behavior. Guardrails are not red tape. They are a compass.
The best use of a draft policy is not enforcement. It is conversation. Bring your team together, walk through it, and find out what they are actually doing and thinking. If you have younger or more adventurous employees, you may be surprised. Bring it into the open and keep the dialogue going.