Natural language processing (NLP) is the AI application area concerned with extracting information from, or generating, human language — text or speech — rather than images or numbers. the NRC’s text analytics team describes its own mandate as building tools that “text analytics team conceives, builds, and evaluates tools that help extract information from textual data”.
the NRC’s text analytics team works on extracting several distinct kinds of information from text: explicit statements, implicit and inferred meaning, summaries, and “subtext information (sentiment, sarcasm, metaphor).” It applies this to “situational awareness, clinical research informatics, sentiment and emotion analysis, and intelligence” — a working definition grounded in what the discipline actually does, not a one-line abstraction.
ISED’s AI advantage blueprint names NLP as one of the fields transformed by deep-learning research with Canadian roots — the 2018 ACM A.M. Turing Award work “led to major advances in computer vision, speech recognition, natural language processing and robotics and many other applications” — and Statistics Canada’s Q2 2026 survey of AI use by Canadian businesses’s Q2 2026 business survey shows it is one of the most-adopted named applications in practice: 27.0% of AI-using Canadian businesses reported using natural language processing, up from 23.1% a year earlier — the fourth-highest of the sixteen named categories tracked, behind only data analytics (36.6%), text analytics (34.5%) and virtual agents or chat bots (28.2%).
A customer-service inbox that automatically tags an incoming email as a complaint, a billing question or a renewal request — and separately flags the ones that read as frustrated — is doing the same kind of work the NRC’s team describes: extracting explicit information (the topic) and subtext information (the sentiment) from the same message. Nothing about that pipeline requires the system to generate any text of its own; classification-only NLP and generative AI are related but distinct uses of the same underlying field.
See also machine learning, deep learning and artificial intelligence.
This is one term in a plain-English glossary on how AI actually works and where it fits in a Canadian business.
