'AI agent' has become a label for almost anything. In practice there's a useful distinction: an automation follows rules you define in advance; an agent decides what to do next based on the situation. Both are valuable. Choosing the wrong one makes systems either brittle or unpredictable.
Use a rule-based automation when
- Inputs are structured and predictable — form fields, database rows, webhooks.
- The correct action can be written as clear if-then logic.
- Mistakes are expensive and every step must be auditable.
Use an AI agent when
- Inputs are unstructured — free-text emails, chat messages, documents.
- The right next step depends on interpreting intent or context.
- A wrong step is recoverable, or a human approves before anything irreversible happens.
The pattern that usually wins
Most reliable systems combine both: AI at the edges to understand messy input and turn it into structured data, and deterministic automation in the middle to act on it. The agent reads the enquiry and extracts intent; the automation creates the CRM record and schedules the follow-up. This keeps the unpredictable part small, testable and easy to monitor.
Whichever you choose, log every action, define what the system is not allowed to do, and give people an easy way to step in.