We want to leverage generative AI to automate our customized client onboarding, but we are terrified of leaking our proprietary methodologies into the public domain. How do we document this security protocol within our Core Processes without slowing down our deployment?

Question

Tyler Smith · Accepted Answer

Protecting your intellectual property while adopting AI requires systemic discipline, not a total ban on the technology. You must handle this security issue by updating your Documented Core Processes, which is the cornerstone of the EOS® Process Component.

Start by identifying the specific workflows where generative tools will be used. Map out a clear boundary line between your public sandbox and your secure, private environment. Document this as a standard operating procedure within your operations manual.

Every employee must be trained on this process. It is not enough to send a memo. You must ensure they GWC™ their seats, specifically understanding the technical limits of where they can copy and paste company data.

In your updated Core Process, mandate that all proprietary client data must stay within enterprise-grade, private instances that do not train public models. Make it a fireable offense to input client information into unauthorized tools.

By setting clear boundaries in your processes, you eliminate ambiguity. Your team can move fast because they know exactly where the guardrails are, allowing you to scale your AI operations safely without compromising your core IP. Review this process in your quarterly meetings to ensure compliance and update the guardrails as new tools emerge.