What is intent recognition?
Intent recognition is the classification of a customer message into one of a predefined set of purposes, so a system can decide how to respond.
Older chatbots were built entirely on this. Someone enumerated the intents — check_order_status, request_refund, ask_shipping_cost — wrote training phrases for each, and mapped every intent to a scripted reply. It worked exactly as well as the list was complete.
Why it matters
The failure mode is the interesting part. A question that matches no intent falls into a catch-all, which is why so many bots answer 'I didn't quite get that' — the phrase is not a bug, it is the architecture becoming visible. Keeping the list complete means constant maintenance, and the list is never complete, because customers keep inventing phrasings. Retrieval-based systems sidestep the problem: instead of classifying the question, they search the content for whatever is closest to it, so a phrasing nobody anticipated still finds the right page. Intent recognition remains useful for routing — deciding which team gets a message — rather than for answering.
Examples
- A bot trained on twelve intents meeting the thirteenth and apologising.
- Routing a message to billing versus technical support, where classification is genuinely the job.
- A retrieval system answering a phrasing nobody wrote a training example for.
Not the same as
Semantic search
Intent recognition sorts a question into a fixed bucket. Semantic search finds the closest content without needing buckets to exist.
Related
term
What is semantic search?
Keyword search asks whether two pieces of text share words. Semantic search asks whether they mean the same thing. The difference shows up immediately in customer questions, because customers do not use a company's vocabulary: someone asks 'can I send it back?' about a page headed 'Returns and exchanges', and the two share not one significant word.
term
What is a website chatbot?
The term covers two very different things. Older chatbots follow scripts and break the moment a visitor phrases something unexpectedly. Modern ones retrieve from a business's own content and generate an answer, which handles arbitrary phrasing.
term
What is conversational AI?
The term is used loosely enough to cover almost anything with a text box, but there is a practical test, and it is a follow-up question. Ask 'do you ship to Ireland?', get an answer, then ask 'how much?'. A system that answers the cost of shipping to Ireland is conversational. One that asks 'how much of what?' — or worse, answers about product pricing — is a form with a chat interface.
comparison
Rule-based chatbot vs AI chatbot
A rule-based chatbot follows a flowchart: recognised phrases lead to scripted replies. An AI chatbot retrieves relevant content and generates an answer. The first is predictable and brittle; the second handles what nobody anticipated.
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