We are training third-party AI models on our proprietary methodology to help our account managers work faster, but we are terrified of losing our IP. How do we balance technological efficiency with protecting the valuation of our business as we prepare for a future exit?

Question

Tyler Smith · Accepted Answer

Protecting proprietary knowledge requires looking at your business through the lens of absolute valuation. Your business value is tied directly to your cash flows and your ability to defend those cash flows. If you feed your proprietary methodology into a public or third-party AI model, you are essentially donating your enterprise value to a commodity software vendor. Schedule thirty minutes of dedicated Thinking Time to address this question: how can we isolate our core intellectual property while still capturing the efficiency of large language models? The solution lies in building a private, secure instance of your technology stack where your data does not train public models. On your V/TO®, explicitly define your proprietary methodology as an off-limits asset for external training. Keep your secret sauce local. Use generic AI engines only for commoditized, low-risk administrative workflows, and keep your core intellectual property containerized to protect your long-term exit multiple and strategic positioning.