How do you build an AI implementation roadmap?

A useful AI roadmap starts with business workflows, not model names.

Direct answer

An AI implementation roadmap should prioritise use cases by ROI, data sensitivity, implementation effort, integration complexity, governance needs, human review requirements, and adoption risk. It should start with small measurable deployments before scaling.

The first step

Map the workflows where time, cost, quality, or response speed creates a measurable business problem.

The evaluation lens

Balazs uses practical filters instead of hype.

What cost or time does this remove?
What data does it touch?
Who reviews the output?
How will success be measured?

The safest path

Start with constrained internal workflows, then expand once governance and adoption patterns are proven.