# AI agent: what it is and how it works · Zorraquino
> An AI agent is a system that uses information and tools to decide on and carry out steps towards a goal, with a defined degree of autonomy.
URL: https://www.zorraquino.com/en/dictionary/ai-agent

# AI agent

An AI agent is a system that uses information and tools to decide on and carry out steps towards a goal, with a defined degree of autonomy

What it means, how it is used and where it comes up, with its related concepts.

[The whole glossary](https://www.zorraquino.com/en/dictionary)

## What it is and how it works

In LLM-based systems, the model can choose actions, observe results and adjust the next step. One example is reviewing a request, checking data and preparing a reply. Permissions, stopping conditions and actions that require human intervention must be defined. A chatbot that only answers questions does not necessarily work as an agent.

Also known as

Intelligent agent

Topics

[Artificial intelligence](https://www.zorraquino.com/en/dictionary/category/inteligencia-artificial)

## Frequently asked questions about AI agent

### When is an AI agent better than an automated workflow with fixed steps?

An agent is worth considering when the path to completing the task changes depending on what it finds and it is not practical to define every step in advance. If the rules and routes are clear, a fixed workflow may be simpler to control. The choice should compare quality, time, required resources and ease of supervision for the specific task; more autonomy does not mean more usefulness.

### Does an AI agent have to be allowed to take actions without review?

No. Autonomy can be limited to searching for information, preparing proposals or carrying out low-impact actions, while others are reserved for human approval. Permissions should be separated technically, and it should be defined when the system must stop or ask for help. In a hypothetical example, an agent could prepare an order change without confirming it. Supervision should match the risk and be workable in day-to-day work.

### How do you evaluate an AI agent before adding it to a process?

You need to check both the task outcome and the path the agent takes to reach it. Include typical cases, incomplete information and tool failures, and observe whether it respects permissions and stopping conditions. A favorable demo is not enough. The evaluation should record errors, required interventions and resources consumed, so the agent can be compared with a simpler alternative to decide whether it adds value.

## Related concepts

- [Multi-agent system](https://www.zorraquino.com/en/dictionary/internet/multi-agent-system.html)
- [Tool use in AI](https://www.zorraquino.com/en/dictionary/ai-tool-use)
- [Agent orchestration](https://www.zorraquino.com/en/dictionary/agent-orchestration)
- [Workflow](https://www.zorraquino.com/en/dictionary/lean/workflow.html)
- [AI adoption](https://www.zorraquino.com/en/dictionary/ai-adoption)

## References

- [Anthropic: building effective agents](https://www.anthropic.com/engineering/building-effective-agents)
- [Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile](https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf)
- [LLM06:2025 Excessive Agency](https://genai.owasp.org/llmrisk/llm062025-excessive-agency/)