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What Is an AI Agent? Definition, How It Works, and Examples
AI agent explained simply: definition, how agents work, how they differ from chatbots, and what they need in a company.
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:
- Understand the goal: The agent receives a task – for example, "check incoming documents for deadlines."
- Plan: It breaks the task down into intermediate steps and decides which tools it needs.
- Act: It carries out the steps – reading data, creating content, making entries.
- 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.
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 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.
FAQ
What is an AI agent?
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.
How does an AI agent differ from a chatbot?
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.
What does an AI agent need to work well?
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.
Are AI agents safe?
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.
Where are AI agents used today?
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.