AI glossary for businesses
AI use case
In short
An AI use case is a specific, repeatable task where AI helps a defined group of people reach a measurable result. "Use AI in marketing" is not a use case. "Draft first versions of product descriptions for new arrivals, checked by the e-shop manager" is. Clear use cases are the building blocks of any AI roadmap.
How an AI use case works
A use case links four things: a task, the people who do it, the data it needs and the result you expect. If any of these is vague, the project usually drifts.
Think of a recipe card. "Make dinner" helps no one. A recipe names the dish, the ingredients, the steps and how many people it serves. A good AI use case is just as concrete:
Task: sort incoming customer emails by topic and urgency.
Who: the two-person support team.
Data: the shared inbox and a list of categories.
Result: a faster first reply and fewer missed urgent emails.
That example is described in full in the AI for email triage and routing use case.
In practice for a small business
A family-run building materials retailer in Larissa lists ten ideas in a short internal workshop. They score each idea on value (time saved, revenue, fewer errors) and effort (data readiness, cost, change for staff). Three rise to the top: product descriptions for the e-shop, a knowledge-base assistant for return and warranty rules, and a weekly sales summary from spreadsheets. They start with the product descriptions, because the data already exists and the risk is low. The others wait for the next cycle.
The article on how to choose your first AI use case goes deeper into scoring.
Why it matters and what to watch out for
Start from the problem, not the tool. Sometimes the answer is a simple process change or automation, not AI.
Check the data first. A great idea with missing or messy data is not ready yet.
Watch the risk level. Uses that affect people's rights, like screening job candidates, are high-risk under the EU AI Act and often need a DPIA under GDPR. Treat them with extra care and check with your DPO or legal advisor.
Make it measurable. If you cannot say what success looks like, you cannot run a fair pilot.