Start with the decision, not the model
A useful AI strategy begins with a business decision or workflow worth improving. Define the problem, the people involved, and the outcome before choosing a model. A narrow, well-understood use case creates a better foundation than a collection of disconnected pilots.
Make data readiness a delivery priority
Understand the quality, ownership, and permissions of the data your system needs. Establish clear boundaries for sensitive information, document sources, and plan for the way information changes over time.
Design responsibility into operations
Assign owners for evaluation, human review, monitoring, and incident response. Evaluate accuracy and usefulness against representative tasks. Treat AI as an operating capability that needs continuous oversight, not a one-time deployment.
Measure value in the real workflow
Connect adoption metrics to outcomes such as time saved, decision quality, or reduced rework. Start with a baseline, validate assumptions in a controlled environment, and expand only when the evidence supports it.