What Is an AI Agent? Definition, Examples, and How They Work

By the time you open your CRM after a sales call, the deal has notes from the conversation. A follow-up email sits in your drafts waiting for your review, though no one on your team wrote it.

An AI agent did.

Once an agent has a goal and access to your tools, it works out the steps on its own. That sounds useful until you think about the same agent updating the wrong deal or sending that email before you’ve read it.

Before you give any tool that kind of access, you need to know what it can do without you. The product name won’t tell you, since vendors call plenty of chatbots and basic assistants “AI agents.”

This guide explains what an AI agent is and how it works. We’ll compare agents with chatbots and AI assistants, including whether ChatGPT counts as one. You’ll see real examples of agents at work, plus the checks to run before you let one act for you.

What Is an AI Agent?

An AI agent is software that uses AI to work toward a goal you give it. It decides which steps to take and carries them out with tools such as email and your CRM. Depending on how it’s set up, it may ask for your approval before taking action.

Ask an agent to find open deals that haven’t had a follow-up in two weeks. It checks your CRM for those deals and reads the notes from each one’s last meeting. Using those notes, it adds a follow-up task to each deal and suggests what to say.

Traditional sales automation follows rules and workflows you set up in advance. An agent can decide what each deal needs based on the information it finds.

Most modern AI agents share four traits:

• Works toward a goal. You set the outcome. The agent works out the route.
• Uses tools. It connects to apps like your calendar or CRM to read data and act inside them.
• Plans in steps. It breaks a task into parts and adjusts the plan when a step fails.
• Keeps context. It tracks what happened in earlier steps, so it doesn’t lose its place halfway through a task.

How Do AI Agents Work?

AI agents work in a loop, repeating five steps until the goal is met or a person needs to step in.

1. Get the goal. You describe the outcome you want in plain language.
2. Gather context. The agent pulls in what it needs, such as files or past meeting notes.
3. Plan the steps. It breaks the goal into smaller tasks and decides the order.
4. Act with tools. It uses connected apps to do the work, like posting in Slack or updating a project tracker.
5. Check the result. After each action, it compares the result with the goal. If a step fails or the output looks wrong, it tries another route or hands the task back to you.

You can see the loop at work when an agent prepares the weekly project update for your leadership team. After reading this week’s meeting notes and the project tracker, the agent sorts each project by status and drafts the update. While reviewing the draft, it finds a project with no status and asks the project owner to confirm its progress. Once the owner replies, the agent completes the report and posts it to Slack.

Many agents run on a large language model (LLM), which helps plan the steps and check the results. Connected tools, such as Slack or your CRM, let the agent take action. To access those tools, some agents use the Model Context Protocol (MCP), an open standard that lets AI apps connect to external data and services. The Fireflies MCP server, for example, lets compatible AI tools such as Claude and ChatGPT read your meeting transcripts and summaries.

AI Agent vs. Chatbot vs. AI Assistant

AI agents keep getting compared with chatbots and AI assistants. Chances are you’ve used the other two, such as the help bot on a store’s website or a tool that drafts your emails. With all three, you start by typing a request in plain language.

What happens after that is a different story. The table below tracks one customer’s refund request.

In the bottom row, the chatbot and the assistant stop at a reply. The agent goes further, checking eligibility and preparing the refund for your approval.

The line between an assistant and an agent isn’t fixed, though. Many products sold as an AI assistant include agent features, so one tool can play both roles.

Is ChatGPT an AI Agent?

It depends on the feature you use. In a regular chat, ChatGPT works as an AI assistant that answers each request. It works as an agent in ChatGPT Work, which handles longer, multi-step tasks and finished deliverables. OpenAI has retired its earlier agent mode and points users to Work.

Types of AI Agents

You can sort AI agents in two ways: by how they make decisions or by what they do at work.

The 5 Classic Types of AI Agents

Computer science textbooks describe five classic types of AI agents, ranging from simple rule-followers to systems that learn.

One agent can fit more than one type. A learning agent might plan toward a goal and weigh options before it acts.

Modern AI Agents You’ll See at Work

These are the kinds you’ll come across most:

• Task agents. They handle one workflow from start to finish, like following up on a deal or preparing a weekly project update.
• Voice agents. AI voice agents hold spoken conversations, such as screening job candidates or answering inbound sales calls. Learn more about how AI voice agents work.
• Coding agents. Give one a ticket, and it writes and tests the code. A developer reviews the result before it ships.
• Research agents. They search many sources and pull the findings into a report you can review.
• Multi-agent systems. Several specialized agents work together on a task. A research agent might gather data and pass it to a writing agent, which turns the findings into a report.

AI Agent Examples at Work

AI agents can take on work in most teams, from sales to engineering. Here are six areas where they help, including what they handle and what your people decide.

• Sales. AI sales agents check new leads against your ideal customer profile and update lead records in your CRM. Your reps own the conversations and the strategy for closing the deal.
• Recruiting. For roles with a flood of applicants, an agent can run first-round phone screens with set questions and score each answer against the role's requirements. Recruiters review the shortlist and make the final hiring decision.
• Customer support. When a customer asks about a late package, a support agent checks the carrier status and sends them an update. Your reps step in for escalations and requests that fall outside policy.
• Operations. An operations agent matches new invoices against purchase orders and flags any that don't line up. Your finance team approves payments and resolves the flagged ones.
• Engineering. When a user reports a bug, a coding agent reproduces it in a test environment and writes a draft fix. Developers review the code and decide when it ships.
• Meetings. An agent can track the action items from each meeting and check in with owners when a task runs late. Team leads set priorities and adjust timelines.

Want an agent to run your screening or discovery calls? Fireflies Voice Agents handle the conversation and send you the full summary.

See Voice Agents

What Is Agentic AI?

Agentic AI is the approach of building AI that can work toward a goal and take action to reach it. AI agents are the systems built with that approach.

“Agentic” describes a quality, so a tool can be more or less agentic. The more it can plan and act without step-by-step direction from you, the more agentic it is.

Generative AI creates content when you ask for it, like a draft email or a summary. Agentic AI goes further by planning and taking actions to complete tasks.

When a product calls itself agentic, check how much it can do across your tools before it asks for your approval.

Benefits and Limitations of AI Agents

AI agents can save your team hours on repetitive work. Because they act on their own, they also bring new risks. Knowing both sides helps you decide which tasks to hand over.

Benefits of AI Agents

• Time back on busywork. An agent handles the copy-and-paste work between your apps and keeps records up to date. Your team gets more time for work that needs their judgment.
• Consistent work. An agent can follow the same process each time, so steps don't get skipped on busy days.
• Work outside office hours. Agents can handle tasks overnight or answer messages across time zones while your team is offline.

Limitations of AI Agents

• Small mistakes snowball. On a long task, one wrong step early on carries into every step after it.
• Connected tools add risk. An agent works through the tools you connect. If one of those is your email or a browser, hidden instructions on a website or in a message could trick it into the wrong action.
• Bad data leads to bad actions. If your records are outdated or your notes are messy, the agent will act on the wrong information.

How to Use AI Agents Safely

AI agents can be safe to use at work when you put a few guardrails in place:

1. Start small. Give the agent an easy internal task first, like sorting support tickets. Keep it away from payments and customer messages until you've tested it.
2. Keep a person on approvals. Have someone review and approve before the agent sends a mass email or makes a payment.
3. Limit what it can reach. Connect the apps a task needs and nothing more. Give the agent a specific job, since a vague request like “handle my inbox” leaves room for mistakes.

How Fireflies Puts AI Agents to Work

Meetings and calls are where your team makes decisions and agrees on next steps. The follow-through afterward is where details get lost, which makes conversations a natural place for AI agents. Fireflies works as an AI teammate that takes on that follow-through while you stay in control.

• Voice Agents. Fireflies Voice Agents run routine calls, such as screening interviews and inbound lead qualification. You set the questions and guardrails and decide when the agent hands a call to a person. After the call, you get a transcript and summary, with the outcome synced to your ATS or CRM.
• AI Skills. AI Skills run after every meeting or on a weekly schedule. A skill can draft your follow-up email or qualify a deal with BANT. The results go to tools like HubSpot or Slack. You can preview a skill on real meetings before you turn it on.
• AskFred. AskFred answers questions across your meetings and connected apps. Ask “What did the client say about pricing last month?” and get the answer without digging through transcripts.

You choose which meetings each skill runs on and who sees the results.

Fireflies is SOC 2 Type II and GDPR compliant. It's also ISO/IEC 42001 certified, with HIPAA compliance available on the Enterprise plan with a signed BAA and Private Storage.

Fireflies is the AI teammate that handles the follow-through, from running routine calls to turning meetings into action items and CRM updates your team can use.

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FAQs

What is an AI agent in simple terms?

In simple terms, an AI agent is software you give a goal to. It works out the steps and uses the tools available to it to get the job done. For anything important, like sending an email or making a payment, it can ask for your approval.

Is ChatGPT an AI agent?

It depends on the feature you use. ChatGPT works as an AI assistant in a regular chat and acts as an agent through ChatGPT Work, which handles longer, multi-step tasks.

What are the 5 types of AI agents?

The five classic types differ in how they make decisions:

• Simple reflex agents follow fixed if-then rules.
• Model-based reflex agents keep track of what happened before to make decisions when they can't see everything.
• Goal-based agents pick actions that move them toward a goal.
• Utility-based agents compare options and choose the best one.
• Learning agents get better by learning from results.

Are AI agents safe to use at work?

They can be, as long as you set some limits on what they can do. Start with low-risk tasks and keep a person on approvals for anything that matters. It also helps to check where your data goes. When you connect an agent to an outside AI tool, your data falls under that tool's terms, so read them before you share anything sensitive.

Will AI agents replace jobs?

Agents can take on repetitive steps of a job, like screening applicants or matching invoices. People should remain responsible for important decisions, such as who to hire or which payment to approve. That gives teams more time for work that needs their judgment.

Hand Off the Steps, Keep the Decisions

The biggest change with AI agents may be how much work you no longer have to do yourself. An assistant responds to your requests, while an agent takes a goal and works through the steps using your tools.

Remember the sales call from the opening? The agent updated the CRM and drafted a follow-up email, leaving you to review the email before it goes out.

You can start the same way. Pick one repetitive task and keep a person on approvals. As the agent proves reliable, you can trust it with more work.

With Fireflies, meeting follow-ups are one less thing your team has to worry about.

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