We are training custom AI agents on our internal databases to automate client onboarding, but we are terrified these models will leak our proprietary delivery IP or that our employees will inadvertently paste trade secrets into public LLMs. How do we document data security inside our Core Processes and secure our intellectual property for a future exit?

Question

Tyler Smith · Accepted Answer

Protecting your proprietary knowledge is critical for maintaining your business valuation during a future exit. Buyers will not pay a premium for systems that leak intellectual property. To secure your data, you must document strict operational guidelines within your Core Processes on your V/TO®. Start by classifying your data into public, internal, and highly proprietary categories. Then, establish clear rules for which LLMs and tools your team can use. For example, mandate that no employee may enter client data or proprietary code into public, consumer-grade generative tools. Instead, direct your team to use enterprise-grade models that guarantee data privacy and opt out of public training loops. To ensure these rules are followed, assign a data compliance Rock to your Integrator or operations leader to audit tool usage. You should also update your GWC™ definitions for every seat on your Accountability Chart to include basic data security compliance as a core expectation. During your weekly Level 10 Meeting™, review any potential data leaks or unauthorized tool usage under your issues list. By formalizing these boundaries in your written Core Processes, you demonstrate to future buyers that your proprietary intellectual property is locked down, secure, and fully transferable as a highly valuable corporate asset.