If you only document the inputs you fed into an AI model and the outputs it generated, you are missing the most critical piece of business data: Why were you doing it?
In the rush to deploy enterprise AI, teams are treating systems like black boxes. They record inputs and outputs, hand off the results, and assume the job is done.
This creates massive institutional debt.
Without documenting the underlying requirements and business logic:
- ▶️ Transferred work fails: A colleague cannot build on or audit your work because they don’t understand the original intent.
- ▶️ Validation is impossible: You cannot verify if an output is correct if you haven’t explicitly defined what success looks like.
- ▶️ System drift occurs: As model versions update, unanchored prompt inputs yield wildly inconsistent business results.
Inputs and outputs are merely transactional artifacts. The application profile—the brief—is the asset.
Define the why before you execute the how.
– Joseph Busch
#EnterpriseArchitecture #BusinessLogic #AIGovernance #Metadata #SystemsThinking