We want to feed our highly confidential proprietary templates into AI to build custom tools, but we are terrified of data leaks. How do we use the GWC™ filter on our Accountability Chart and our documented Core Processes to assign strict ownership over AI data privacy?

Question

Tyler Smith · Accepted Answer

Protecting your intellectual property while leveraging AI requires operational discipline, not just technical security. First, you must document your AI data intake as a standard operating procedure within your HR and IT Core Processes. This document must explicitly define what types of proprietary data can be entered into public models versus what must remain restricted to private, secure enterprise environments.

Once the process is documented, you must assign absolute ownership of data security to a single seat on your Accountability Chart, typically under your head of operations or IT. Use the GWC™ filter to evaluate the person in this seat. They must truly Get the technical realities of data privacy, such as how API data retention policies differ from standard user interfaces. They must Want the responsibility of auditing your team's software usage and enforcing security compliance. Most importantly, they must have the Capacity to do it, meaning they have the technical knowledge and the weekly allocation of time to run regular security audits.

Do not let individual departments buy and connect third-party AI tools without this central oversight. If your designated seat holder does not pass the GWC™ filter with three firm yeses, do not input any proprietary data. Either train them, redefine the seat, or hire external expertise to fill the gap. By establishing a clear owner and a documented process, you ensure your valuable IP is shielded from accidental public leaks.