The work between the work
Teams rarely describe their biggest cost as a handoff. They talk about slow follow-up, inconsistent records, unanswered questions, or decisions waiting on context. Underneath each symptom is often the same pattern: information has to move from one person or system to another, and someone has to interpret it along the way.
Look for repeated judgment
A good AI opportunity combines repetition with bounded judgment. The input changes, but the questions stay recognizable: Is this lead a fit? Which policy applies? What is missing from this document? Where should this request go? These are not simple if-then rules, but they are constrained enough to evaluate.
Keep the human boundary explicit
The goal is not to remove every person from the loop. It is to decide where human judgment creates value and where it merely repairs a broken flow. Strong systems make that boundary visible: what the model may decide, what requires review, and how exceptions are surfaced.
Measure the operational result
A compelling demo is not an outcome. Measure cycle time, rework, error rates, response quality, and the number of manual touches. If the system cannot improve a real operating measure, it is probably not the first thing to build.