Definition
Natural language processing (NLP)
Natural language processing (NLP) is the branch of AI concerned with getting computers to understand, interpret, and generate human language, whether written or spoken.
NLP is the umbrella field for teaching machines to work with human language: understanding what a sentence means, pulling structured facts out of messy text, and producing fluent replies. Modern Large language model (LLM) systems are the current, most powerful form of NLP, but the field also covers narrower jobs like classifying a message, detecting a topic, or extracting a date and party size from a phrase.
For a restaurant, NLP is quietly behind a lot of the AI worth having. It is how a phone agent (Voice AI) turns a caller's spoken request into a booking, how Sentiment analysis reads whether a review is happy or angry, and how a tool sorts hundreds of guest comments into themes you can actually act on. Each of these is NLP aimed at a specific operating problem, not a general chatbot.
You rarely meet the term head-on; you meet it as features. What is worth knowing is that language tasks that used to require a person reading everything (triaging reviews, answering routine questions, tagging feedback) are now things software can do at volume, freeing your team for the judgment calls machines still get wrong. Just remember those systems can still be confidently mistaken (see Hallucination), so the higher the stakes, the more a human should stay in the loop. See review management.
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