Start with the operating reality
An AI audit should identify where work is slow, repetitive, expensive, or inconsistent. The goal is not to find the flashiest demo. The goal is to find the clearest leverage point.
We usually look for workflows with enough repetition to matter and enough structure to evaluate.
Pilot with instrumentation
A pilot should answer practical questions: Did cycle time improve? Did quality hold? Did users trust the output? What still needed human intervention?
Without instrumentation, pilots become storytelling exercises. With instrumentation, they become rollout decisions.
Scale only what the team can own
A production AI system needs owners, maintenance habits, and clear expectations. If no one can explain how the system is behaving after launch, the team is not ready to scale it.
Sustainable adoption comes from simple systems with clear accountability, not from maximum complexity.