A chatbot usually follows scripts or gives generic answers. A business agent is trained on your real business information, answers specific questions accurately, takes actions like booking, and is built on open standards so other AI assistants can talk to it.
What is a traditional chatbot?
A traditional chatbot is a scripted helper that matches questions to pre-written answers or decision trees.
They're useful for simple things like "What are your hours?" but tend to break when questions get specific: "Do you service 15-year-old furnaces, and is the diagnostic fee credited toward the repair?" That's when customers hit the dreaded "Sorry, I didn't understand that."
What is a business agent?
A business agent is an AI trained on your own information (services, prices, policies, FAQs) that can understand natural questions, answer accurately, and complete tasks.
It follows rules you set: what it can talk about, which prices it can quote, what it should never promise, and when to hand off to a person.
How do they compare?
| Chatbot | Business agent | |
|---|---|---|
| Knowledge | Scripts or generic info | Your real, approved business information |
| Questions it handles | Simple, expected ones | Specific, detailed, natural questions |
| Actions | Usually links to a form | Books, quotes and captures intake where connected |
| Talks to other AI assistants | No | Built for open standards like A2A and MCP |
| Gets better over time | Only if someone rewrites scripts | Improves as you review real questions |
Why does the difference matter now?
Because customers' AI assistants will increasingly want to ask a business questions directly, and only an agent built on open standards can answer them.
A chatbot was designed to talk to people on your website. A business agent can talk to people on your website and, using standards like A2A, to the AI assistants your customers use (A2A specification). That's the door we build. See Business Agent Build.
Is a business agent safe?
It should only answer from information you've approved, with clear limits and a hand-off to your team when needed. Testing before launch and reviewing real conversations afterward are part of doing it properly.