natural language processing
Also called: NLP
Natural language processing (NLP) is the field of AI that gives computers the ability to read, interpret, and generate human language. It powers how search engines and AI assistants grasp the meaning behind a query and produce answers, weighing each word in full context.
NLP splits into two halves: natural language understanding (NLU), which pulls meaning out of text, and natural language generation (NLG), which produces it. Underneath sit tasks like tokenization (splitting text into units), part-of-speech tagging, named entity recognition, sentiment analysis, translation, and summarization.
The modern leap came from transformers. In 2019 Google put BERT (Bidirectional Encoder Representations from Transformers) into Search, a model that reads a sentence in both directions at once instead of one word at a time. Google’s own example: for parking on a hill with no curb, older systems leaned on “curb” and ignored “no,” which flips the intent; BERT reads the full sentence and gets it right. Google said it affected one in ten U.S. English searches at launch.
Why NLP drives visibility now
Every surface you compete on runs on NLP. Google’s BERT and later MUM interpret the query; ChatGPT, Perplexity, and AI Overviews read your page, decide what it means, and decide whether to cite it. MUM goes further than BERT: Google says it both understands and generates language across 75 languages. So the practical question shifts from “does my page contain the keyword” to “can a language model lift a clean, quotable claim from it.” Plain phrasing, clear structure, and self-contained passages are what these systems parse best.
How it affects your traffic
NLP is the layer that decides whether your content gets understood or skipped. If a language model cannot cleanly parse your page, it will not surface you in AI Overviews or cite you in ChatGPT and Perplexity, no matter how strong your backlink profile is. Our AI SEO work structures pages so both classic NLP ranking systems and generative engines can lift a clear answer, which is what earns the citation and the click. Getting the language machine-legible is the difference between being the source an AI quotes and being invisible to it.
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