Start with the broken workflow, not the newest AI tool.
Teams often begin AI adoption with a product demo and then search for a problem. That creates scattered experiments, uncertain quality, and no clear owner.
Map the work as it exists
Document the trigger, inputs, repeated steps, decisions, handoffs, review points and output. The useful automation opportunity usually appears where people reformat, route, summarize, compare or retrieve information again and again.
Protect the judgment
Separate repeatable work from decisions that need context, accountability, empathy or risk review. Automation should create capacity for judgment, not hide it.
Measure adoption and quality
Speed alone is not success. Track rework, exceptions, output quality, user confidence, and whether the workflow produces a better business outcome.
