AI agents
A chatbot answers. An agent solves.
If the goal is "information," it's a chatbot. If the goal is "resolution," it's an agent.
In short
A chatbot answers questions from a predefined set or a knowledge base (RAG — Retrieval-Augmented Generation, generating answers augmented by searching proprietary sources). An AI agent receives an objective, independently chooses steps, uses tools (API — Application Programming Interface, an interface through which two applications communicate; CRM — Customer Relationship Management; email), and executes real actions within your systems. The practical difference: a chatbot tells you what to do; an agent does it.
- Chatbot: answers, but doesn't act
- Agent: plans, decides, uses tools, executes
- Chatbot: good for FAQ, L1 support, lead capture
- Agent: good for end-to-end processes (sales, ops, back-office)
Spectrum, not binary — 4 levels
In practice, it's not "chatbot OR agent" — it's a spectrum:
- Level 1: scripted chatbot (answers based on rules)
- Level 2: RAG chatbot (answers from documents)
- Level 3: copilot (suggests actions, human decides)
- Level 4: autonomous agent (executes, with guardrails)
When to choose each
Chatbot — for FAQs, level 1 support, simple lead capture. Copilot — for teams that want speed without giving up decision control. Agent — for repetitive end-to-end processes where each step is auditable and reversible.
Why the difference matters for ROI
A chatbot saves minutes. An agent saves hours. The difference between the two is the scaling factor of your AI project.