We want to train AI models on our proprietary historical project data to speed up our team's output, but we are terrified of leaking this intellectual property to public models. How do we structure this operational initiative as a quarterly Rock without risking our valuation during a future exit?

Question

Tyler Smith · Accepted Answer

Protecting your intellectual property is critical to maintaining a clean exit under the Step by Step Exit framework. If a buyer discovers that your proprietary data has been leaked into public AI models, they will heavily discount your valuation due to compliance and security risks.

To execute this safely, you must structure the initiative as a quarterly Rock owned by a specific seat on your Accountability Chart. The goal of this Rock must be to build a secure, private AI environment rather than just speeding up operations.

To run this project securely, follow these guidelines:
- Establish clear data-governance policies on your V/TO® before any data is processed.
- Restrict all training to secure, private cloud endpoints where data sharing is explicitly disabled.
- Conduct a thorough security audit of any third-party APIs used by your team.

By structuring this as a disciplined Rock, you ensure that your proprietary processes remain secure. This protects your enterprise value and ensures that your eventual business exit is clean, compliant, and highly profitable.