A chatbot answers questions inside a conversation, while an AI agent completes a whole job by taking action. A chatbot can tell a customer the warranty policy. An agent can look up their specific order, check its warranty status, and issue the replacement, with no person doing the lookup in between. If a request only needs an answer, a chatbot is the right tool. If it needs an action taken inside your systems, it needs an agent.
What each one actually does
A chatbot is a conversational interface, and its job ends when it has produced a helpful reply. It's a good fit for FAQ-style questions, first-line support triage, or catalog Q&A where the answer is the whole outcome.
An agent is software that completes a workflow. It reads an incoming request, retrieves the data it needs from your systems, takes the action (generates a quotation, updates a record, sends a confirmation), and escalates to a human only when a case falls outside its scope. For an agent, the reply is a by-product of the work.
How to tell which one a workflow needs
Ask what happens after the answer is given. If nothing happens and the conversation really ends there, a chatbot is enough, and it's simpler and cheaper to build and maintain. If a person normally does something next (updates a system, generates a document, routes a request), that next step is exactly what an agent should absorb.
Volume and repetition matter too. High-volume, rule-heavy workflows such as dealer support, order intake, and document processing are where an agent pays for itself, because it can take the same correct action hundreds of times a day.
Where most businesses should start
Start with one agent on one specific workflow, wired into the tools already used for it, instead of a general-purpose agent that tries to do everything. A dealer-support agent that reads incoming queries, checks the catalog, and answers or escalates is a concrete, measurable pilot. A generic 'AI assistant for the company' has no clear success metric and nowhere obvious to plug in.
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