A good prompt can save minutes. A well-designed AI workflow can change the economics of a process. The difference is repeatability: clear inputs, an explicit output standard, quality checks, exception handling, and a human decision at the right point.
I start by mapping the current workflow and finding the steps dominated by search, classification, transformation, drafting, or comparison. These are often strong candidates for AI assistance, provided the source material is reliable and the cost of an error is understood.
The workflow should make verification easy. Structured outputs, citations to source data, confidence flags, and review queues are more valuable than fluent text alone. They let people concentrate judgment where it matters instead of rereading everything.
The goal is not to automate every step. It is to redesign the division of labor so machines handle scale and repetition while people retain context, accountability, and commercial judgment.