AI chat vs rule-based chatbots

Decision trees are not obsolete. They are just wrong for most of what shops get asked.

A rule-based chatbot follows a flowchart somebody drew. It is predictable, cheap and completely reliable inside the flowchart — and useless one step outside it.

Where rules genuinely win

Regulated answers that must be word-for-word every time
Short, fixed flows with no variation — order tracking by number, nothing else
Situations where a wrong answer is expensive and a non-answer is fine

The hybrid most shops actually want

The useful arrangement is rarely one or the other. Let the model handle understanding — what did this person actually ask — and let fixed rules handle consequences: what may be promised, what must always reach a person, what wording is used for refunds. The flexible part reads; the rigid part decides.

How to tell which one you are being sold

Ask the vendor what happens when a customer asks something nobody anticipated. A rule-based tool will describe a fallback message. A model-based one will describe where the answer comes from. If the answer is that it will figure it out, you are being sold the risk without the mitigation.

Where rules fall apart

Customers do not ask questions in the shape the flowchart expects. They ask two things at once, in the middle of a sentence about something else, in their second language. Every "I did not quite get that" is a rule-based bot meeting a real person.

The real trade

A language model handles the phrasing problem and introduces a new one: it can be fluently wrong. The mitigation is not a better model, it is a shorter leash — answer only from the shop's own catalog and written policies, and hand off rather than improvise.