AI Agent
An AI agent is an AI system that works towards a goal by taking actions, such as reading an email, looking up an order, drafting a reply and updating the CRM, rather than only answering a question. Agents work best today on narrow, well-defined tasks with clear limits and human approval for important steps.
Key Facts
| Reliable today | Triage and routing, data entry from documents, drafting replies, looking up and summarising records |
|---|---|
| Needs caution | Payments, customer-facing commitments, deleting data, long multi-step plans |
| Essential guardrails | Limited permissions, action logs, approval steps, easy human override |
| Good first pilot | One repetitive back-office task with a clear definition of done |
Agents versus automation
Traditional automation follows fixed rules. An agent can handle varied inputs, such as emails written in different ways, and decide which of a few allowed actions to take. That flexibility is useful, and it is why limits matter.
Designing a safe agent
- Give it only the tools and permissions the task needs.
- Log every action and the reason.
- Require approval above set limits.
- Measure accuracy on real cases before widening its scope.
Frequently Asked Questions
Will AI agents replace staff?
For narrow tasks they remove repetitive work; people move to exceptions, judgement and customer relationships. See our post on redeploying people when work is automated.
How much does an AI agent cost to build?
A focused agent for one task is usually a few weeks of work plus model usage costs, which scale with volume.
Related Glossary
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