How to choose your first AI use case

When an organisation decides to adopt AI, the first challenge is often deciding where to start. A long list of possible uses can make progress harder, especially when every department has a different idea of what matters most.

Start with a workflow, not a tool

Choose a task that people already do regularly. Write down who does it, what information they need, how long it takes and where errors or delays occur. This makes the problem concrete enough to assess. “Use AI in customer service” is broad; “help staff find answers in approved policy documents” is a testable use case.

Score value and readiness separately

A useful opportunity should improve a result that matters: faster response, better quality, lower manual effort or a more consistent service. Then check whether the information and workflow are ready. Are the source documents current? Can the team describe a good answer? Is there an owner who can review the output? A high-value idea with poor data readiness may need preparation before a pilot.

Look at risk before you build

Decide what the AI may do on its own and where a person must review it. Consider privacy, accuracy, accessibility and the effect of a wrong answer. A low-risk internal assistant is often a better first project than an unsupervised customer-facing decision.

Pick one use case, define a baseline and agree on a small pilot. Measure whether it improves the workflow, then decide whether to expand, revise or stop. An AI roadmap becomes much more useful when it is built from decisions like these.