AI creates value when it removes a specific bottleneck in a real workflow. Choosing a model before understanding the work usually adds complexity instead of reducing it.
Choose a bounded workflow
Look for repetitive work with stable inputs and an output that a subject-matter owner can verify. Classification, summarisation and draft preparation are often safer starting points than autonomous decisions.
Keep people at consequential decisions
Define where the system may proceed, where a person must approve and what happens when confidence is low or data is incomplete.
Measure operating outcomes
Compare processing time, rework, exceptions and output quality before and after the pilot. Expand only when the team can explain, monitor and stop the workflow safely.