6 min read
Selecting the right first AI project
Selecting a first AI project requires balancing impact potential with implementation complexity. Start with problems that have clear decision owners, accessible data, and measurable outcomes. A small, well-scoped pilot that connects directly to a key process often result the fastest path to value. This article outlines a checklist for assessing candidate projects, including data availability, stakeholder alignment, and realistic timelines. It also explains metrics to monitor during pilots and how to design experiments that reduce operational risk. The guidance is grounded in experience from regional deployments and emphasizes repeatability so teams can build a sustainable pipeline of initiatives.