We suspect our team is quietly using public generative AI tools to draft client deliverables, which puts our proprietary client data and trade secrets at risk. How do we establish operational guardrails and update our Accountability Chart to police this without killing our team's productivity?

Question

Tyler Smith · Accepted Answer

Employees using unauthorized public AI tools is a common problem that puts your company at risk. You cannot solve this with a simple policy memo. You must treat security as an operational workflow. Start by updating your Accountability Chart. Your Integrator or technology leader must own the seat responsible for data security and software compliance. This leader must clearly understand what GWC means for AI usage across all departments. Next, set a company Rock to create a secure internal environment. This is often called a sandbox. You can set this up using private APIs that do not train public models on your proprietary data. Once this secure environment is active, you can train your team on how to use it safely. This allows your team to keep their speed gains without risking your client data. Add a simple metric to your weekly Scorecard to track compliance. For example, you can track the percentage of team members who have completed security training. In your Level 10 Meeting, encourage open communication about how your team uses these tools. If they are hiding their usage, it is because your current systems are too slow. Build a secure path that makes it easy for them to do the right thing. This protects your IP and keeps your operations running fast.