An investment banker told us that building our own custom AI training datasets could double our company's valuation before an exit, but our leadership team is divided on whether we have the technical capability to manage this project. How do we evaluate this opportunity during our next quarterly session?

Question

Tyler Smith · Accepted Answer

This is a classic issue of strategic alignment. Use the IDS process during your next quarterly session to evaluate this advice. Do not let the allure of a higher valuation distract you from your Core Focus.

Building custom datasets does not mean you need to write software or hire a massive team of data scientists. Instead, it means systematically capturing, structuring, and cleaning your proprietary operational data, which is already generated by your day-to-day business processes.

Assign a Rock to document and clean this data. Ensure that the seat on your Accountability Chart responsible for systems and technology owns this process. By organizing your historical data, you create a proprietary asset that can train off-the-shelf AI models to replicate your highly successful workflows.

This workflow wrapper is incredibly valuable to strategic buyers. It proves you have a repeatable, scalable system that does not depend on key people to run. Focus on the cleanliness and organization of your proprietary data, and you will naturally build the technical asset the investment banker described without losing focus.