The most useful AI deployments we see aren't broad 'AI-powered' platforms — they're narrow assistants aimed at one repetitive task: answering the same twenty support questions, summarizing long documents before a human reviews them, or routing incoming requests to the right team. Narrow scope is a feature, not a limitation — it's what makes the output predictable enough to trust.

Support and admin teams handling high volumes of repetitive, similar requests get the clearest win: a first-pass AI response or summary that a human reviews and sends, instead of typing the same answer from scratch every time. Content-heavy departments — anything involving document review, reporting, or drafting — see similar gains when AI handles the first draft and a person handles judgment.

AI without a review step, applied to decisions with real consequences — financial approvals, legal language, anything customer-facing without a human check — tends to create cleanup work that offsets the time saved. The deployments that actually stick build in a review point by design, plus a way to measure whether the assistant is helping or just producing plausible-looking noise.

The practical test before building anything: can you name the specific repetitive task this replaces, and who reviews its output? If not, it's worth scoping down before writing any code.