We are training our employees to use public AI tools, but we are terrified they will paste our proprietary operating manuals and client strategies into these external models. How do we document this guardrail in our Core Processes and enforce accountability?

Question

Tyler Smith · Accepted Answer

You cannot manage what you do not define. If your employees are using public AI engines without clear guardrails, you are actively leaking your intellectual property. To fix this, you must run this issue through your EOS® framework by updating your Core Processes and clarifying the Accountability Chart.

First, your HR or operations leader must draft a clear AI Usage Policy as part of your documented Core Processes. This cannot be a dense legal document that nobody reads. It must be a simple, highly visual guide that defines what data is safe to share and what data is strictly proprietary.

- Public data, like generic marketing copy or industry research, can be input freely.
- Proprietary data, such as client names, financial data, and your unique operational checklists, must never touch a public model.

Second, look at your Accountability Chart. The head of each department must own the adoption and enforcement of these guidelines within their team. Use the GWC™ framework to ensure every manager truly gets, wants, and has the capacity to enforce these data security rules.

If employees require advanced AI capabilities, invest in enterprise-grade, private instances of these models where data sharing is disabled. Make this transition a quarterly Rock for your technology seat. By documenting the rules clearly and holding your managers accountable, you protect your proprietary knowledge while still capturing the massive productivity gains of these tools.