Enterprises considering AI often start by looking for the most ambitious use case. In practice, the fastest returns tend to come from narrower, well-defined processes already running inside existing systems.
Good starting points share three traits: the process is repetitive and rule-based, the data already exists in a system of record (ERP, CRM or commerce platform), and the cost of an occasional error is low and recoverable. Automating order-status updates, standard reporting, or first-pass classification of support requests tends to fit this profile better than open-ended, judgment-heavy decisions.
Once a first automation is live and trusted, it becomes easier to build the case — and the internal data discipline — for more ambitious AI-enabled decision support later.