Natural language processing, or NLP, is the field of AI concerned with human language. It covers tasks such as understanding what a customer is asking, spotting the sentiment in a review, translating, summarising, pulling names and dates out of text and generating replies.
Older NLP relied on rules and keyword lists. Modern NLP is mostly built on neural networks and large language models, which learn from huge volumes of text how words and sentences relate, so they cope much better with slang, typos and varied phrasing.
Retailers and venues use NLP in chat assistants, email sorting, review and survey analysis, voice ordering, call transcription and search that understands intent. It can show, for example, that complaints this month cluster around slow delivery rather than product quality.
Language is messy, so accuracy is not perfect. Sarcasm, regional expressions, mixed languages and industry jargon can trip systems up, and accuracy can differ across accents or dialects. Check how a tool performs on your own messages, and keep a person in the loop for sensitive replies.
NLP is what lets customers and staff use ordinary words instead of menus and forms, and it turns the large volume of unstructured text a business collects into something measurable.