- An AI agent does not just answer; it takes steps, uses tools and completes tasks.
- Agents work best on well-defined, multi-step tasks with clear success criteria.
- Limit their permissions and keep a person approving actions with real consequences.
"AI agents" has become one of the most used terms in business technology. Behind the hype is a useful idea: AI that can carry out a sequence of steps, not just produce text.
Chatbot versus agent
A chatbot answers a question. An agent is given a goal, such as "prepare a weekly sales report", and works through the steps: retrieve data from the CRM, calculate figures, write commentary, format the report and send it for review. It uses tools, checks results and adjusts.
Where agents help today
- Research tasks: gathering and summarising information from several sources.
- Back-office tasks: preparing reports, reconciling records, updating systems.
- Customer operations: handling routine requests end to end, with hand-over rules.
- Sales operations: researching prospects and drafting outreach.
Deploying safely
- Narrow scope: one clearly defined task per agent.
- Least privilege: access only to the systems and data the task needs.
- Human approval: for payments, external messages and changes to records.
- Logging: every action recorded so it can be reviewed.
- Testing: run on real past cases before going live.
Who builds them
Agents are built on top of leading AI models and automation platforms. The skills needed are those of an implementation lead or generative AI engineer: understanding the process, configuring tools and designing safeguards.
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