The best AI opportunities are not always the most dramatic. They are repeatable decisions or knowledge tasks where better context and faster synthesis improve the work.
Look for evidence-rich work
Strong candidates have source material that can be retrieved, permissioned, and cited. If experts cannot agree on what good input looks like, the model will not solve that ambiguity for them.
Define the human boundary
Decide what the system may suggest, what it may execute, and what always requires review. This boundary should reflect the cost of being wrong, not the novelty of the technology.
Evaluate the complete workflow
Model quality is only one variable. Measure whether people complete the task faster, catch more issues, and understand why an answer was produced.
A narrow workflow with clear evaluation usually creates more value than a general assistant with unclear ownership.