natural language processing
This glossary entry explains natural language processing for AI governance and model risk programs. The sections below summarize what the term means in plain language, why chief AI officers and cross-functional committees track it, where teams often get confused, and—when you are signed in—how it shows up across major industries and in expectations tied to the EU AI Act and NIST AI RMF. Use related links at the end of the page to explore neighboring concepts without losing context.
What It Means
Natural language processing is the technology that enables computers to understand, interpret, and generate human language in all its forms - whether it's text, speech, or even sign language. It's what powers chatbots, voice assistants, translation services, and document analysis tools that can read and respond to language the way humans naturally communicate.
Why Chief AI Officers Care
NLP is fundamental to most customer-facing AI applications and internal automation tools, making it critical for competitive advantage and operational efficiency. Poor NLP implementation can lead to embarrassing customer interactions, biased hiring decisions, or regulatory compliance failures when processing sensitive communications. The quality of your NLP capabilities directly impacts customer satisfaction, employee productivity, and your ability to extract insights from unstructured text data.
Real-World Example
A major bank uses NLP to automatically analyze thousands of customer service emails daily, routing complaints to appropriate departments, flagging potential fraud mentions, and generating suggested responses for agents - reducing response time from hours to minutes while ensuring no critical issues are missed.
Common Confusion
People often think NLP means AI can truly 'understand' language like humans do, when it's actually sophisticated pattern matching that can miss context, sarcasm, or cultural nuances. Many also confuse basic keyword searching or simple chatbots with advanced NLP capabilities that can handle complex, contextual conversations.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, natural language processing enables the extraction of clinical insights from unstructured data like physi...
Finance: In finance, natural language processing enables automated analysis of unstructured data like earnings calls, regulatory ...
Premium content locked
Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"The field concerned with machines capable of processing, analysing, and generating human language, either spoken, written or signed."Source: TTC6_Taxonomy_Terminology
Explore more glossary terms
Discuss This Term with Your AI Assistant
Ask how "natural language processing" applies to your specific use case and regulatory context.
Start Free Trial