We have integrated several customized generative AI workflows into our customer service and production processes, but how do we document these systems during due diligence so a buyer sees them as actual proprietary assets?

Question

Tyler Smith · Accepted Answer

To a buyer, AI tools can easily look like passing hype unless you can demonstrate their direct, measurable impact on your operating margins. To turn your AI integrations into verifiable enterprise value, you must document them as standard operating procedures.

Start by mapping out how these systems function. Document how your language models predict token likelihoods to generate relevant customer support text, and show how tasks like client onboarding or reporting are framed as completion tasks. This documentation must explain the specific prompt prefixes and systemic context you have built to ensure reliable outcomes.

Next, show the data. A buyer will want to see that your AI systems are not just theoretical, but that they deliver consistent, probabilistic completions that save time and reduce labor costs. Provide metrics showing the reduction in processing times or the increase in output quality since integrating these models.

Finally, ensure your intellectual property is clean. Document who owns the code, the custom APIs, and the training data. If your AI workflows are deeply embedded in your operations and fully documented in your company's playbooks, a buyer will see them as a scalable asset that can be easily transitioned to new ownership, rather than a fragile system that depends on your personal technical knowledge.