use case

basicwidespread

A use case is a specific, well-defined task or situation where a technology – such as artificial intelligence – can be deployed with tangible benefit.

In plain terms

A use case answers the question: 'Fine, but what exactly do we use it for?' 'We are introducing AI at the company' is not a use case. 'AI pre-fills the details of incoming invoices in the accounting software, and the accountant only checks them' is.

It is like a drill: on its own, it is just a tool on the shelf. The use case is that you want to mount a shelf on the wall. That shows which drill bit you need, how long it will take, and whether it is worth buying a drill at all.

A good use case specifies who uses the tool, for what task, what inputs it works with, and what indicates success. This distinguishes it from an idea or a promise: it can be tested, measured, and discarded if it does not work.

You encounter it so often in AI news because companies are asking less what the technology can do and more which specific tasks deliver more value than they cost.

How it works

Naming the problem: you pick a repetitive, time-consuming or error-prone task, such as sorting customer complaints.
Precise description: you record who currently performs the work, from what data, in what steps, and what counts as a good result.
Weighing up: you check whether an AI or an agent is suitable, how much it costs, how much damage an error could cause, and whether there are legal or data protection barriers.
Test on a small scale: run it for a few weeks with a limited group and human oversight, while measuring time saved and errors.
Decision: if the numbers confirm it, you expand; if not, you modify or drop it, and the next candidate can come.

An everyday example

At your workplace, your manager asks you to gather three tasks where AI could help. You propose that an automatic summary and to-do list be generated from the audio recording of weekly meetings. This is already a use case: it has an owner, an input, an output, and it is measurable how much time it saves.

Who is affected

entrepreneur, executiveThey must decide which specific tasks are worth spending money and time on, and which AI idea merely sounds good.

employeeThey know their own job best, so the best use cases often come from them, and it is their daily tasks that get reshaped. → Work & HR

developerWithout a precise use case, you cannot know what to build or what counts as good for the system. → Code

lawyer, citizenThe EU AI Act classifies AI systems primarily into risk categories based on their intended use. Thus, the same technology can be used with almost no restrictions in one case, while in another, such as recruitment or credit assessment, it is subject to strict conditions. → Law

A common misconception

MythIf an AI tool is smart enough, it is good for everything; searching for use cases is just unnecessary paperwork.

In realityAI implementations often fail not due to the technology, but because no one specified exactly what task the tool should solve or what counts as success. The same model can be excellent for one task and unreliable for another.

Limits and risks

The term is often used as a marketing tactic: much of a list promising 'a hundred use cases' may be untested ideas.
What works well in a demo may not necessarily succeed with your data and processes, so always request measurable results.
An overly broadly defined case ('improve customer experience') cannot be verified, while an overly narrow one does not recoup the outlay.
AI is not suitable for every task: where a mistake causes serious damage, human oversight is still needed even if the use case appears profitable on paper.

Similar, but not the same

business case – The use case describes how you use the technology, while the business case calculates whether it is financially worthwhile.
proof of concept – The use case is the task to be solved; the proof of concept is the small-scale trial that reveals whether it is solvable.
function – The feature tells you what the device can do; the use case tells you what you use it for in a specific situation.

Related concepts

Broader

AI implementation, digital transformation, automation

Narrower

customer service chatbot, coding agent, document processing, high-risk AI system

On the edge

business case, proof of concept, return on investment, munkafolyamat, AI-agent

A brief history

The term originates from software development. Swedish computer scientist Ivar Jacobson developed it while working at Ericsson and presented it publicly in 1987 as a method for describing, from the user's perspective, what a system must be able to do. It later became part of the UML modeling language. From there it entered business language, where it now refers more broadly to a concrete application of any technology.

Where things stand

By the end of 2026, the term became the basic vocabulary of business and administrative AI communication. The focus shifted from idea generation to identifying cases that deliver measurable results, especially for autonomous agents.

Status: 2026 November

In the news

Appears in 2 Agent Age stories; the curve shows weekly occurrence in the news magazine.

Thomson Reuters v. ROSS: Third Circuit recognizes licensing market for AI training dataOct 27, 2026 · Jog
Hong Kong selects 36 AI use cases for financial-sector GenAI trials, including Ant BankAug 31, 2026 · Money

Also known as

use case · use-case · use case · use case · AI use case · AI use case

Sources

Wikipedia: Use case

This entry was machine-edited and has undergone machine expert review; the “In the news” section updates automatically from Agent Age stories.