A measurable project
An artificial intelligence project becomes assessable when it has a reference process, an owner and a measure of results. “Adopting AI” is not a sufficient objective. Reducing time spent on a specific task, improving a control or making internal information more accessible are hypotheses that can be tested.
The cost of testing and the cost of scale
A pilot may require limited effort yet prove expensive to integrate. The economic comparison should therefore separate experimentation, integration, controls and ongoing operation. Results should also be assessed for errors, review work and demands on people, rather than apparent speed alone.
When to proceed and when to stop
Before testing, it is useful to define conditions for continuing, changing direction or stopping. This preserves a clear investment decision. This note proposes a general strategic framework; technical and regulatory assessments require specialists and are not replaced by this perspective.