My leadership team wants to draft an AI policy for our staff, but I do not want a 20-page document that nobody reads. How do we keep our AI guidelines simple and actionable?

Question

Tyler Smith · Accepted Answer

Keep it to one page. If it is longer than that, your team will ignore it and use unauthorized tools anyway. An effective AI policy does not need complex technical jargon. It needs to establish clear boundaries around data, quality, and accountability.

First, define what data can never enter a public AI model. This means customer lists, proprietary financial data, and intellectual property are strictly off limits for free, non-enterprise AI systems.

Second, define the accountability rule. No work product generated by AI can be sent to a client or published without human review. The person who owns the seat on the Accountability Chart is fully accountable for the accuracy and quality of the output, regardless of whether a machine wrote it.

Third, encourage experimentation with a greenlight process. Instead of banning tools, create a simple list of approved enterprise platforms. If an employee wants to use a new tool, they must bring it to their manager to verify its data security.

This approach aligns with the EOS framework. You are not micromanaging; you are setting clear guardrails so your self-governing team can run fast without exposing the business to unnecessary risk. Focus on the core principles of data security, human accountability, and transparent tool usage to keep your operations clean.