What Are AI Agents?
An AI agent is an AI system that can take multiple steps toward a goal — deciding what to do next, using tools, and adjusting based on results — with far less human input per step than a normal chatbot conversation, where you drive every single exchange yourself.
Key takeaways
- A chatbot responds to one prompt at a time; an agent works toward a goal across multiple steps with less human input per step.
- Agents typically combine an AI model with the ability to use tools — searching, running code, calling other software — to complete a task.
- Agents are useful for multi-step, well-defined tasks; a simple prompt is usually faster and more reliable for a single, well-defined question.
- "Agentic" workflows are becoming common in customer support (an agent that handles a full support ticket, not just one reply) and research (an agent that searches, reads, and synthesizes across many sources).
Definition
An AI agent is a system built around an AI model that can plan and take multiple steps toward completing a task, using tools along the way (search, code execution, calling other software), and adjusting its next step based on what happens — rather than producing one response to one prompt and stopping.
Agent vs. chatbot
| Chatbot | AI Agent | |
|---|---|---|
| Interaction pattern | One prompt, one response, repeat | Works through multiple steps toward a goal |
| Tool use | Usually none, or limited | Can use tools — search, code, other software |
| Human input needed | Every step | Mainly at the start and end |
| Best for | Quick, single questions | Multi-step, well-defined tasks |
How agents actually work
Most agent systems follow a loop: the agent decides what step to take next based on the goal and what it knows so far, takes that step (which might mean calling a tool), observes the result, and decides the next step — repeating until the goal is met or it needs human input.
Real examples
- A research agent that searches multiple sources, reads them, and synthesizes a report — instead of you manually searching and summarizing each source yourself.
- A support agent that reads a full customer ticket, checks an order status through a connected tool, and drafts (or sends) a resolution.
- A coding agent that reads a codebase, makes a requested change across multiple files, and runs tests to check its own work.
When to use an agent vs. a simple prompt
Use a simple prompt for a single, well-defined question you can answer in one exchange. Reach for an agent when the task genuinely requires multiple steps you'd otherwise do by hand — searching several sources, checking a status and then acting on it, or making coordinated changes across several files or systems.
Learn more
AIVX Labs covers this directly in AI Agents Explained, part of the Learn to Use AI pillar, free on every plan. AIVX Labs' own AI Chatbot Builder tool lets members deploy a real one, live today. See also the AI Glossary for related terms like MCP and RAG.
Every course and tool mentioned here is included free on AIVX Labs.
Start freeFrequently asked questions
What's the difference between an AI agent and a chatbot?
A chatbot answers one prompt at a time, with you deciding every next step. An agent works through multiple steps toward a goal on its own — searching, deciding, using tools, checking results — with much less back-and-forth required from you.
Are AI agents the same as automation?
They overlap but aren't identical. Traditional automation follows a fixed, predefined sequence of steps. An AI agent can make judgment calls about what to do next based on what it finds, which is more flexible but also less predictable than fixed automation.
Is an AI agent the same as a chatbot deployed on a website?
Not necessarily. A simple deployed chatbot might just answer FAQs from a knowledge base — that's closer to a scripted assistant. A true agent version could also take actions (booking a call, updating a record) as part of handling the conversation, not just answering questions.