AI agent or chatbot: how they differ and which one your company needs
TL;DR: A chatbot answers: its job ends when it replies. An AI agent, as well as talking, uses tools to do something in your systems (create an order, log a ticket, send the details of a call). That ability to act is what makes it useful, and also what makes it more expensive and more delicate: it needs integrations, permissions, a log of what it does and a person reviewing. If your problem is answering the same questions over and over, a chatbot is enough. If someone has to do something after every conversation, think about an agent.
“AI agent” is the buzzword of 2026. It’s used to sell almost anything with a language model inside, including good old chatbots with better conversation. The problem is that, if you don’t know what you’re buying, you can pay agent prices for a chatbot or, the other way round, buy a chatbot when what you needed was someone to get something done.
Here’s a definition you can use to compare offers, a real example, and a simple way to decide which one you need.
The difference in one sentence
A chatbot answers. An agent acts.
A chatbot receives a question and returns an answer; that’s where its job ends. It can be very well built, understand badly written questions and reply in a flawless tone. But when the conversation is over, nothing has changed in your systems.
An AI agent also has tools. A tool is an action the model can decide to run: looking up the status of an order in your ERP, creating a ticket, booking an appointment, sending an email with the details collected. The model decides when to use it and with what data, and the result stays in your systems.
| Chatbot | AI agent | |
|---|---|---|
| What it does | Answers questions | Answers and runs actions |
| What it connects to | A knowledge base (FAQ, documents) | Your systems: ERP, CRM, calendar, email |
| What it leaves done | Nothing outside the conversation | A record, an order, an appointment, a notice |
| Cost | Lower | Higher: each tool is an integration |
| Risk if it gets it wrong | A bad answer | Wrong data written to your system |
A real example: Ana
Ana is the AI voice receptionist I first built for VisibleSoft and now offer to other companies. She answers the phone, introduces herself as a virtual assistant, works out the reason for the call and collects name, company, phone and email.
Up to that point she could be a chatbot with a voice. What makes her something else is the ending: before hanging up, Ana uses a tool that sends the extracted details and a summary of the conversation to our backend, which emails them. Nobody has to listen to the recording or log into a dashboard. The call ends and the work is already in the inbox.
It’s also worth saying what she doesn’t do. Today Ana doesn’t transfer the call to a person if she detects something urgent: she collects the details and sends the email when the call ends. Live transfer is on the roadmap, but I don’t sell it as if it existed. That’s exactly the kind of detail you should ask about when someone offers you an agent.
In the most complete plan, Ana puts the data straight into the customer’s CRM, ERP or calendar. More tools mean more agent, and more integration to build and maintain. That’s why that plan costs more: from €2,900 setup and €249/month, against €990 and €149/month for the plan that only sends the email (excluding VAT).
How to spot an “agent” that is really a chatbot
When someone presents you with an AI agent, ask these questions:
- What tools does it have? Have them list them. “It can do anything” isn’t an answer.
- Which systems does it write to, and with what permissions? An agent that writes to your ERP needs a user with limited permissions, not administrator access.
- What happens when it gets something wrong? There should be a log of every action and, at first, a person approving before it runs.
- What doesn’t it do? If the answer is “nothing, it does everything”, be suspicious.
If after those questions it turns out it doesn’t run anything outside the conversation, what you’re being offered is a chatbot. It may be exactly what you need, but pay for it as such.
Why an agent needs more supervision
A chatbot that gets it wrong gives a bad answer. An agent that gets it wrong leaves bad data in your system, and nobody notices until it shows up on an invoice.
I’ve seen it in another project, the assistant that polishes the wording of quotes at Cerrajería Carlos Rodríguez. In testing after a model change, a description with no price came back with an invented one: €186, copied from the example in the instructions. That assistant doesn’t save anything on its own: it proposes and a person accepts or rejects. That’s why an error like that stays as a proposal someone can discard, instead of going straight into a quote.
The same goes for an agent, multiplied by every tool it has. Hence three rules I recommend: start with human approval before every action that writes to your systems, log what the agent did and with what data, and give it only the permissions it needs for its task. And, chatbot or agent, say from the start that it’s an AI, as Article 50 of the EU AI Act provides.
Which one your company needs
Look at what happens after each conversation.
If the conversation is the end of it (someone asks for your opening hours, how to book, what a service includes), a chatbot well fed with your information solves the problem and costs less.
If after each conversation someone on your staff has to do something (note down the details, create the order, call back with context), that work is what an agent can do. That’s where the savings are, and also where the cost is: in how much it costs to integrate AI I explain why integrations weigh more than the model, and in how to add AI to your ERP without switching systems, how they connect.
My advice for getting started: pick a single action, the one that takes up most of someone’s time after a conversation today, and have the agent propose it instead of running it. If it gets it right almost every time for a month, give it the next one.
Resources
Frequently asked questions
What is the difference between an AI agent and a chatbot?
A chatbot talks and answers. An AI agent also uses tools to act in other systems: looking up an order in the ERP, creating a ticket or sending the details of a conversation. The difference isn't how well it talks, but what it can do.
Is a chatbot built on ChatGPT already an agent?
Not necessarily. If it only generates answers, however good, it's a chatbot. It becomes an agent when it has access to tools and uses them to do things outside the conversation.
Is an agent more expensive than a chatbot?
Usually, yes, because each tool is an integration with your systems that has to be built, secured and maintained. The AI model tends to be the cheap part; the integrations are the expensive part.
Do you have to say that people are talking to an AI?
Yes. The EU AI Act (Article 50) requires AI systems that interact with people to be designed so that they know they're talking to an AI, unless it's obvious. It applies equally to a chatbot and an agent.