An agent is most useful when it is built around one business task. Start there, not with everything an agent could do.
What an agent brings together.
Information. It retrieves the records and documents the task depends on.
Tools. It works with the systems the task already uses.
Boundaries. It acts within defined permissions, with stopping points and review.
One useful task, a testable result.
Define the input, the output and what success looks like. Prototype the task and the points where a person reviews it. Then connect the systems, test the exceptions and improve.
Practical check: If you can’t say what the agent receives, what it produces and how you will judge the result, the scope isn’t ready yet.
Decide where it stops.
Agree what the agent may access, what it may change and when it must hand over to a person. What it can do depends on access, integrations and the scope you agree.
Start with the repeated work.
Describe the work your team repeats and the result you need. A sensible first version is small enough to test and useful enough to matter.
Read more: What AI Agents Actually Do · AI Agents