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AI agent

In short: An AI agent pursues a goal over several steps on its own: it plans, uses tools such as a browser, email or software interfaces, and checks its result. The difference from a chatbot: it acts instead of only answering.

Updated 29 September 2026 · 2 min read · 4 sources

What it is

An AI agent is a program that pursues a goal over several steps on its own. It uses a language model to decide what to do next, carries out that step with a tool, looks at the result and continues until the goal is reached or it has to stop.12

How it works

  • Goal. A person or another system sets the task, for example “find three suppliers and request quotes”.
  • Plan. The model breaks the goal into steps.
  • Act. It calls a tool: searches the web, opens a file, fills in a form, sends a message. Tool access is increasingly standardised, for example through the Model Context Protocol.4
  • Observe. It reads what came back.
  • Check and repeat. It decides whether the step worked and what comes next.

Agent, chatbot, automation

ChatbotClassic automationAI agent
Decides next stepNoNo, fixed rulesYes
Uses toolsRarelyYes, pre-definedYes, chooses itself
Handles surprisesAnswers onlyStops or failsTries another way
PredictabilityHighVery highLower

What businesses use it for

  • Research and preparing documents from many sources.
  • Sales support: finding contacts, drafting first messages for a person to approve.
  • Back office: sorting emails, updating records, reconciling lists.
  • Software development: writing, testing and fixing code.

Risks

  • Mistakes add up. A small error early on can lead to many wrong steps.
  • Prompt injection. Text on a web page or in an email can contain hidden instructions the agent follows.3
  • Too many rights. An agent that may pay, delete or send can do real damage.
  • Cost. Every step uses the model; long tasks become expensive.

Introducing agents safely

  • Give it only the rights the task needs.
  • A person approves anything that cannot be undone: payments, deletions, messages to customers.
  • Set spending and time limits.
  • Log every action so it can be traced.
  • Start with one narrow task and measure the result.

Key terms

Tool call
The moment the agent uses an external function, for example a search or an email.
MCP
Model Context Protocol, an open standard for connecting models to tools and data.4
Human in the loop
A person approves certain steps before they happen.
Prompt injection
Hidden instructions in content the agent reads.3

Latest research

New papers and reports that mention this term, found by our daily source scan. One line per source, quoted as published.

Sources

  1. Yao et al.: ReAct — Synergizing Reasoning and Acting in Language Models (2022)
  2. Anthropic: Building effective agents (December 2024)
  3. OWASP Top 10 for Large Language Model Applications
  4. Model Context Protocol

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