The definition
An AI agent is software that uses artificial intelligence not just to answer questions but to carry out tasks. It takes a goal, plans the necessary steps, accesses tools and systems, and works until the result is ready – within defined boundaries and permissions.
A comparison makes it tangible: a chatbot answers the question “How many open requests do we have?” An AI agent answers it, classifies the requests while it's at it, drafts responses for the most urgent ones, and files the results in the right system.
What an AI agent can do that a chatbot can't
- Actively search for information – in documents, databases, or on the web
- Plan multiple work steps and execute them in sequence
- Structure, compare, and summarize data
- Operate systems: create CRM entries, draft emails, route tickets
- Trigger follow-up actions when defined conditions are met
- Collaborate with other agents and hand off subtasks
Examples from everyday work
In sales, an agent researches the company before every customer meeting, summarizes recent interactions, and prepares talking points. In customer service, an agent classifies incoming requests, suggests responses, and routes edge cases to the right team. In internal processes, an agent checks documents for completeness or turns scattered information into a weekly management report.
What all these examples have in common: the agent takes over the recurring legwork; the decisions stay with a human.
What matters when introducing one
An AI agent is only as good as the process it supports and the data it's allowed to access. Before introducing one, three questions should be settled: Which specific process should it support? Which data sources and systems does the agent need for that? And which steps may run automatically, versus which require human sign-off?
A proven approach is to start with a clearly scoped use case that saves measurable effort – rather than an agent that's supposed to “do everything.”