AI agent vs chatbot: what's the difference?

A chatbot replies inside a chat window. An agent runs across your tools and can finish a job (sending an email, updating a CRM, closing a ticket) without you typing each step. Same underlying AI model. The difference is whether tools are attached and what starts it running.

A chatbot answers, an agent acts. If you have a ChatGPT tab open or a Notion AI button in your sidebar, you already use chatbots: they sit in a chat window and wait for you to ask something. An agent runs across your tools (Gmail, HubSpot, Slack) and can finish a job without you typing each step.

At a glance

AspectChatbotAgent
What it doesAnswers questionsTakes actions
Where it livesA chat windowAcross your tools
What starts itYou typing a messageAn event, a schedule, or a condition
What it remembersThe current conversationThe task, often across days
What it producesText repliesSent emails, updated CRM rows, closed tickets

Pick a chatbot when

The job is answering. A website FAQ widget like Intercom, an HR question-answerer that points staff to the right policy, a "what's our refund window" lookup. The person types, the bot replies, the loop ends.

Pick an agent when

The job has steps and lives outside a chat box. A lead qualification agent (Lindy, Zapier Agents) reads a new HubSpot contact, enriches it, scores it, and posts to a Slack channel. An inbox triage agent watches Gmail, drafts replies, labels threads, and books meetings on your calendar. A support agent (Gumloop) takes an incoming ticket, checks order status, refunds if eligible, and updates the ticket, all without you watching.

The same model (Claude, GPT) sits behind both. The difference is whether it has tools attached and runs on triggers.

For team leads picking one to pilot

Start with a chatbot for a question-heavy use case (internal HR, customer FAQ). Graduate to an agent once you can point at a recurring workflow your team does the same way every week.

Last updated: May 20, 2026

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