We want to lay down the law on data privacy regarding generative AI, but we hate writing complex policy manuals that nobody reads. How do we establish a simple, enforceable policy that tells our team exactly what they can and cannot input into public AI engines?

Question

Tyler Smith · Accepted Answer

Establish a simple, three-tier classification for all company data: green, yellow, and red. Green data includes public marketing text, published blog posts, and website copy. Yellow data includes general company templates, non-confidential outlines, and generic business frameworks. Red data includes customer records, financial statements, proprietary operational files, and employee personal data.

Your policy must fit on a single page. Green data is completely free to input into any public language model. Yellow data requires local scrubbing to remove any trace of company names, client names, or identifying details before input. Red data is strictly banned from any public model under any circumstance.

Ensure every team member knows that feeding red data to a public engine is a security violation that can lead to termination. This ties directly back to your core values and the LMA (Lead, Manage, Accountability) seat responsibilities on your EOS Accountability Chart. It is not about micromanagement; it is about protecting your enterprise value as you prepare for a clean exit.

By simplifying this down to three colors, your team can easily memorize the rules and apply them to their daily work. It allows them to maintain their productivity and experiment with creative solutions without putting your intellectual property or client relationships at risk.