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Glossary

What is natural language processing

A plain definition of NLP: what it does with human language, its main tasks, how it relates to large language models, and where businesses use it.

Updated

Definition

Natural language processing

Natural language processing (NLP) is the field of AI that lets computers read, understand and produce human language. It turns text and speech into something software can work with. This is the definition of natural language processing in one sentence.

In short: NLP lets software work with words.

What is natural language processing in AI

  • Reads

    Takes in text or speech from people.

  • Understands

    Works out the meaning behind the words.

  • Produces

    Writes or speaks an answer back.

IBM describes NLP as a subfield of computer science and AI that uses machine learning so computers can understand and communicate with human language.

Language is messy. People use slang, shortcuts and context that rigid rules cannot capture. NLP gives software a way to cope with that.

A related term is natural language understanding. IBM treats it as a part of NLP focused on the meaning behind a sentence.

Main NLP tasks and techniques

  • Classification

    Sort messages into categories.

  • Extraction

    Pull names, dates and amounts.

  • Sentiment

    Judge positive or negative tone.

  • Translation

    Convert text between languages.

  • Summarization

    Shorten long text to key points.

NLP is a toolbox, not one trick. Each natural language processing technique solves a different job with text.

Most business uses combine several of these tasks in one flow.

NLP vs large language models

Classic NLP

  • Often built for one task
  • Smaller, focused models
  • Rules plus machine learning

Language models

  • Handle many tasks at once
  • Trained on large amounts of text
  • Generate fluent text

NLP is the wider field. A large language model is one kind of natural language processing model, trained on huge amounts of text to predict and generate language.

Read more in our large language model entry.

Older NLP methods are often smaller and built for one task, such as flagging spam. Language models handle many tasks with one system. Both belong to NLP.

Related ideas include sentiment analysis and conversational AI, which apply NLP to specific jobs.

Where businesses use NLP

  1. 01

    Message arrives

    An email, ticket or invoice comes in.

  2. 02

    NLP reads it

    The system finds meaning and key details.

  3. 03

    Action follows

    It routes, files or answers the message.

IBM notes that NLP already powers search engines, customer service chatbots, voice-operated GPS and assistants such as Alexa and Siri. Siri natural language processing is how a spoken request becomes an action on your phone.

Inside a company, NLP reads the text that piles up every day: emails, invoices, contracts and support tickets.

  • Routing support emails to the right person
  • Reading invoices and matching them to records
  • Flagging unhappy customers from their messages
  • Summarizing long contracts for review

Our data

What AI answers when buyers ask

We asked ChatGPT, Gemini and Perplexity 10 buyer questions about AI customer service. They named 101 companies, and 79% appeared in only one of the three.

CriterionChatGPTGeminiPerplexity
Companies named403851
Sites cited mostzendesk.com (5 of 10)botpress.com and gartner.com (5 of 10)sobot.io (6 of 10)

Nexum measurement, October 20, 2026, via DataForSEO: 10 buyer questions to each AI, US English, 30 answers in total. 7 companies appeared in all three. Google showed an AI Overview for 8 of the 10 questions.

FAQ

Natural language processing questions

  • NLP is the part of AI that helps computers understand and use human language, written or spoken. It lets software sort, read, translate and write text instead of treating it as random characters.

  • Natural language processing models are programs trained to handle language tasks, from small classifiers that flag spam to large language models that write full answers.

  • A voice assistant turning your spoken request into an action is a clear example. So is software that reads a stack of invoices and pulls out the amounts and dates.

  • Typical services include reading and sorting documents, chat and voice assistants, and summaries of long text. These sit on top of existing tools, such as the CRM or inbox.

  • No. NLP is the broader field of working with language. Generative AI is one branch that creates new text, images or code. See generative AI for the difference.

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