AI strategy becomes useful when it changes how decisions are made and work gets done. The strongest roadmaps do not begin with a catalogue of models. They begin with business constraints.
Start with friction
Map the workflows where speed, consistency, or access to information limits performance. Look for repetitive decisions, manual handoffs, document-heavy processes, and places where valuable context is trapped across systems.
Prioritize for value and readiness
Score opportunities against commercial value, operational impact, data availability, implementation complexity, and risk. A modest workflow with strong adoption can outperform an ambitious platform nobody trusts.
Design the operating model
Technology is one part of the system. Ownership, review points, data governance, training, and performance measurement determine whether the capability becomes durable.
The goal is not to add AI everywhere. It is to make intelligence operational where it matters most.