What are AI agents and how are they different from chatbots?

An AI agent is an AI system that can work toward a goal by planning steps and taking actions on its own, rather than just answering one question at a time. If a chatbot is like a knowledgeable person you ask questions, an agent is more like an assistant you hand a task to and who goes and gets it done.

A normal chatbot works in a simple loop: you ask, it answers, it waits. An agent works in a longer loop: it receives a goal, breaks it into steps, uses tools to carry out each step, checks the results, adjusts its plan and continues until the task is complete or it needs your input.

The key ingredient is tools. An agent might be able to search the web, open and read websites, run code, read and write files, use a browser to click and fill forms, query a database, send emails or call other software through APIs. The language model acts as the brain that decides which tool to use next and what to do with the result.

Here are some real examples of agents today:

Coding agents such as Claude Code can read a whole codebase, make changes across many files, run tests, fix the errors they find and repeat until the tests pass.
Research agents run dozens of searches, read the sources and write a structured report.
Browser agents can navigate websites to fill a form, compare products or collect information.
Business agents can process incoming invoices, extract the details, check them against purchase orders and flag mismatches.

Agents are powerful because they handle multi-step work that would otherwise need constant human attention. A task that takes a person two hours of clicking, copying and checking might run in the background while you do something else.

They also come with real limits and risks. Agents can make mistakes that compound over many steps. They can misunderstand a goal and do the wrong thing confidently. Giving an agent access to email, payments or file deletion means its errors can have real consequences. Agents can also be tricked by malicious instructions hidden in web pages or documents they read, an attack called prompt injection.

Good agent design keeps a human in the loop for important actions, such as sending messages, spending money or deleting data, and limits each agent to the tools it truly needs. Agents are improving fast, and they are likely to become a normal part of how work gets done.