Three things people call "AI"
The same word covers very different tools. A chatbot answers questions. A copilot suggests an edit while you stay in control. An agent is different in kind: it perceives its environment, reasons about a goal, and takes actions to reach it. IBM and McKinsey both define an AI agent as a system that can act autonomously toward an objective — the gap between that and a chatbot is the whole point.
The difference is action
Chatbots and most copilots are built on the same generative core — they produce text. An agent adds the ability to use tools and take steps. IBM draws the line between generative and agentic AI the same way: generative answers, agentic acts. In a marketing platform, that means the agent does not describe the segment you should build — it builds it.
| Chatbot | Copilot | AI agent | |
|---|---|---|---|
| Output | A text reply | A suggested edit | A shipped action |
| Initiative | Waits for you | Waits for you | Pursues a goal |
| Works in | A chat box | Your tool, beside you | The platform itself |
| You get | An answer | A faster keystroke | Finished work to approve |
Why it matters for growth
If you ask a chatbot for an onboarding sequence, you get text you still have to build. An AI growth team builds it — drafts the emails, wires the journey, sets the waits — and hands you finished work to approve. That is the practical difference between talking about growth and running it.
Agents still answer to you
Acting is not the same as acting unsupervised. Capable marketing agents keep a person on every consequential step through human-in-the-loop approval. Analysts expect agents to take on a growing share of routine work — Gartner predicts agentic AI will resolve 80% of common customer-service issues without human intervention by 2029 — but in growth, the responsible default keeps you in command.