One question your clients are increasingly going to ask is:
“What’s the difference between a chatbot and an AI agent?”
They’ll be hearing terms like agents, agentic AI, and autonomous AI in the news, from marketing and from friends and family. Many will feel like they should be using an agent, but in reality, they often do not clearly understand what a chatbot is, let alone how an agent is different.
As a domain expert, understanding this distinction helps you give credible, grounded AI advice instead of adding to the jargon.
The simple explanation you can give
Chatbots and copilots respond.
AI agents take action.
A chatbot waits for a prompt, answers, and stops. It helps an individual work faster, but nothing actually changes in how the business operates.
An AI agent is different. You give it a goal and clear boundaries, and it can plan steps, move data between systems, and complete multi-step work with minimal human involvement.
This is why Brim is described as an AI agent, not a chatbot. It is designed to do work, not just talk about it.
How to explain the difference clearly to clients
There are three useful ways to think about it.
Autonomy
- Chatbots assist, but humans still decide and execute every step.
- Agents operate independently within a defined scope and involve humans when important decisions or information need to be reviewed.
Proactivity
- Chatbots are reactive and only act when a user requests.
- Agents can monitor triggers or events and start workflows on their own across systems.
Tool access
- Chatbots usually help inside one application.
- Agents can pull data from one system, update another, and notify people automatically.
Why this matters to your clients
Many clients say they have “tried AI” because someone used a chatbot. That often leads to disappointment because nothing meaningful changes at a process or workflow level.
Agents are different. They can replace hand-offs, remove delays, and standardise how work gets done. This is why agents are being used for things like finance workflows, operations, and customer service, not just drafting text.
For clients, this means AI can move from experimentation to measurable outcomes. For you as a domain expert, it means you can help them move beyond surface-level adoption.
How to advise clients on where to start
The biggest mistake is starting too big.
Instead, guide clients to:
- Choose one repeatable, rules-based, high-friction workflow.
- Keep the scope tight: one task, one team, clear boundaries.
- Measure the before and after so value is visible.
- Scale only once trust and results are proven.
If your clients are confused about chatbots, agents, or what AI can realistically do for them, this distinction will come up again and again. We cover this in more depth in our recent blog and podcast episode on Spotify and Apple Chatbots vs AI Agents: Why Action-Taking AI Is the Next Big Shift.
If you want to talk through how to explain this to a specific client or apply it to a real workflow, post here and we’ll work through it together.
