---
title: "What Is an AI Agent? Definition, How It Works, and Examples"
description: "AI agent explained simply: definition, how agents work, how they differ from chatbots, and what they need in a company."
type: "wissen"
product: "agent"
slug: "what-is-an-ai-agent"
source_language: "de"
target_languages: ["de", "en", "es", "pl", "tr"]
published: "2026-06-10"
status: "publish"
faq_json: [{"q":"What is an AI agent?","a":"An AI agent is an AI system that independently pursues a given goal: it plans intermediate steps, uses tools such as search, calendar, or email, and keeps working even without ongoing instructions – instead of merely answering individual questions."}, {"q":"How does an AI agent differ from a chatbot?","a":"A chatbot responds, an agent acts: it plans several steps, accesses data and tools, remembers context, and completes tasks – a chatbot delivers one answer per request."}, {"q":"What does an AI agent need to work well?","a":"Three things: access to the relevant context (the company's data), clear instructions on what it should and may do, and defined boundaries with approvals for actions that have external effect."}, {"q":"Are AI agents safe?","a":"Control comes from the approval principle: the agent prepares and proposes, but actions with external effect – such as emails or calls – run through a human's approval."}, {"q":"Where are AI agents used today?","a":"For example, in answering phone calls, evaluating documents, for recurring tasks on a schedule, and as personal assistants that work with a company's data."}]
language: "en"
source_id: "wissen/was-ist-ein-ki-agent"
source_hash: "1d39215daad15f44be17e4d33dea7f94f93387e8bb41d808ce1842c3d4d46451"
---

An AI agent is an AI system that independently pursues a given goal: it breaks the task into steps, uses tools such as search, calendar, email, or databases, evaluates intermediate results, and keeps working until the goal is reached – even without a human giving ongoing instructions. This makes an agent fundamentally different from a chatbot that delivers one answer per request: a chatbot responds, an agent acts.

## How an AI Agent Works

At its core, an agent runs through a cycle of four steps:

1. **Understand the goal:** The agent receives a task – for example, "check incoming documents for deadlines."
2. **Plan:** It breaks the task down into intermediate steps and decides which tools it needs.
3. **Act:** It carries out the steps – reading data, creating content, making entries.
4. **Review and adjust:** It evaluates the result and corrects its plan until the task is done or a follow-up question becomes necessary.

On top of this come two properties that make an agent fit for everyday use: **memory** – it remembers context and instructions instead of starting from scratch with every task – and **tool access**, that is, the ability to work with real systems instead of merely generating text.

## Distinction: Agent, Chatbot, Automation

- **Chatbot:** answers requests in dialogue, usually forgets between sessions, and does not act – the end result is text that a human has to process further.
- **Classic automation:** executes hard-coded rules ("if X, then Y") and reaches its limits as soon as a case deviates from the intended pattern.
- **AI agent:** pursues goals with leeway – it can interpret situations that were not exactly foreseen and decides for itself, within its guidelines, how to proceed.

The direct comparison is explored in more depth in the article [AI agent vs. chatbot](/en/wissen/ki-agent-vs-chatbot.html).

## What an Agent Needs in a Company

An agent is only as good as its context. Three prerequisites determine the quality:

- **Data:** access to the relevant knowledge of the company – contacts, tasks, documents, goals. If this data sits in separate silos, no agent can work reliably.
- **Guidelines:** clear rules about what it should do and under what conditions – the more precise, the better the result.
- **Boundaries:** defined points where a human decides. The approval principle has proven effective: actions with external effect – emails, calls, changes to master data – run through the user's approval. The agent does the preparatory work, the human keeps the decision.

## Example: The AI Agent as a Personal Employee

[webRichtung agent](https://www.webrichtung.de/module/agent/) implements this concept as a personal AI employee: it knows the company's context through the platform data, remembers what is important, and handles recurring tasks via automations even without an ongoing chat – according to the user's guidelines. External effect runs through follow-up questions: the agent does the preparatory work, the human gives approval. How this works in detail is described in the [documentation](https://docs.webrichtung.de/agent/).