Term · Apps & software
AI agent
An AI agent is software that uses a large language model not only to answer questions but to pursue a goal through several steps: deciding what to do next, calling tools — searching a database, reading a document, creating a CRM record, sending a message — and using the results to continue until the task is done or a person needs to decide.
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Explained
How it differs from a chatbot
A chatbot answers within a conversation. An agent acts: it can look up an order, check stock in another system, draft a reply and create a task, following instructions and permissions defined by the business.
Business uses
- Handling routine support requests end to end: checking status, updating details, arranging a return.
- Research and preparation: collecting information from several systems for a manager.
- Back-office tasks: processing incoming documents, categorising requests, updating records.
- Assisting staff inside internal tools.
Risks
- Actions based on misunderstood instructions or invented information.
- Excessive permissions that let a mistake cause real damage.
- Manipulation through malicious inputs ("prompt injection") in emails or documents the agent reads.
- Unclear accountability for automated decisions.
Controls
- Limit tools and permissions to what the task needs.
- Require human approval for sensitive actions: payments, refunds, messages to many customers, data deletion.
- Log every step for review.
- Test on realistic scenarios, including adversarial ones.
- Start with narrow, well-defined tasks.
See AI hallucinations and business risk and workflow automation.
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FAQ
Frequently asked questions
Are AI agents reliable enough for business?
For narrow, well-defined tasks with good controls, they can be useful. Broad autonomy over important systems is still risky.
How is an agent different from traditional automation?
Traditional automation follows fixed rules; an agent decides steps dynamically. Combining both — rules for critical steps, agents for flexible ones — is often best.