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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchAn AI agent is software that receives information about an environment and takes goal-directed actions in it with some degree of autonomy. The term has no single settled definition, so this practical definition focuses on what the software can do—not on a particular model, architecture, or marketing label.
What makes software an AI agent?
A useful test is whether the software does more than return information: does it use information about an environment to choose and carry out actions toward a goal? NIST’s glossary defines an agent as “Software programs that can interact with their environment, receive information, and undertake self-directed actions in service of a larger, externally-specified goal.” NIST’s agent glossary attributes this definition to NIST AI 100-2e2025.
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The goal is generally set by a person or another system; the agent’s role is to pursue it. “Self-directed” does not mean unsupervised in every case: a human may set limits, review proposed actions, or approve consequential steps.
How is an AI agent different from a chatbot?
The distinction is what the software does, not simply which AI model it uses. A chatbot that only responds to a question provides an answer. An agent can use information from its environment to take an action—for example, by calling a function or interacting with another system. The European Commission gives function calls as an example of an action in its AI Act Service Desk FAQ on AI agents.
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The boundary is not always sharp. A conversational interface can be part of an agent, and a system may answer questions while also taking actions. What matters is whether it can act toward a goal, and what controls govern those actions.
What an AI agent does—and what is optional
At a high level, an agent receives or observes information, processes it in relation to a goal, and selects an action. It may then receive new information and decide what to do next. The exact implementation varies; there is no universal checklist of technical components that makes software an agent.
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Agents can operate in digital services, physical settings, or both. They may have narrow action permissions or broad access to tools and systems. Planning across changing inputs appears in some descriptions, but it is not a requirement shared by every definition. The OECD’s 2026 review compares varied definitions and treats capabilities such as complexity and autonomy as variable rather than fixed criteria: The agentic AI landscape and its conceptual foundations.
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- An agent does not have to be fully autonomous; people may direct or approve its steps.
- It does not have to learn continuously, involve multiple agents, or use a large language model.
- It does not have to provide general-purpose reasoning. Its actions may be limited to a specific goal and environment.
How to compare systems called agents
Because the label is used inconsistently, ask what a specific system can actually do rather than relying on its name. These comparison axes are practical aids, not a formal standard or scoring system.
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| Question | What to check |
|---|---|
| How much autonomy does it have? | Can it act without review, or must a person approve each consequential step? |
| What actions can it take? | Can it only return information, or can it call tools, submit requests, or change another system’s state? |
| What environment does it operate in? | Does it interact with a digital service, a physical setting, or both? |
| How does it pursue its goal? | Can it adjust its actions as inputs change, or does it follow a narrow, predefined sequence? Adaptability appears in some descriptions but is not a universal criterion. |
Is “AI agent” a legal category?
Under the EU AI Act, “AI agent” is not a separate legal category or a legally defined term. The European Commission says agents will usually qualify as AI systems, so applicable obligations depend on the system’s properties and intended purpose—not the label alone. Existing rules for AI systems and, where relevant, general-purpose AI models may apply. See the Commission’s AI agent FAQ and the consolidated EU AI Act text dated 27 July 2026.
The Commission FAQ states that, from 2 August 2026, transparency rules apply when an agent is intended to interact with natural persons or generate content; high-risk requirements apply on later dates where an agent qualifies as high-risk. These dates and obligations are specific to the Commission guidance and the Act’s scope. Check current official guidance for the system and use in question.
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Why definitions vary
Institutions and organizations emphasize different features: interaction with an environment, self-directed action, limited human supervision, or the use of AI techniques. The OECD’s review compares these usages rather than prescribing one settled definition, while the European Commission notes that the term’s boundary is blurry and evolving. For a practical reading, focus on the system’s goal-directed actions, the information it uses, and the degree of autonomy and oversight.
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