From an open question to a defensible answer.

Find the workflow or business problem worth examining.

We start with the work, not the technology. Which processes carry the cost, the delay, the error rate, or the risk that would justify changing them at all.

Determine value potential, readiness, constraints, and risk.

Data quality, process stability, ownership, skills, regulatory exposure, and the size of the prize. Assessment produces a defensible value estimate, stated as a range with its assumptions, and a clear list of what is missing.

Proceed, test first, redesign, gather evidence, or stop.

A decision is a deliverable. Stopping early is a valid and often valuable outcome — it is far cheaper than discovering the same answer after implementation.

Improve the workflow and introduce AI with ownership and controls.

The workflow is redesigned before anything is automated. Controls, accountability, and escalation paths are defined as part of the build, not bolted on afterwards.

Measure what changed, what AI contributed, what humans retained, and whether the economics justify continuing.

Baselines are captured before the change where feasible. After implementation, measure workflow and business outcomes, attribution limits, AI touchpoints, human authority, failures, full operating cost, and economic value so the next decision can be ACT, TEST, DEFER, STOP, or remain human-led.