Definition
Natural language processing (NLP) — Natural language processing, or NLP, is the field of artificial intelligence focused on enabling computers to understand, interpret, and generate human language. It covers tasks like extracting structured meaning from unstructured text, such as pulling job titles and dates out of a resume, understanding intent behind a written or spoken sentence, and generating a coherent response. NLP is a foundational discipline rather than a single product; it's the underlying capability that specific tools are built on top of, including resume parsing, semantic search, and the language understanding layer inside a conversational AI system. Modern NLP has largely shifted toward large language models, which handle a broad range of language tasks with a single underlying system rather than requiring a separate hand-built tool for each specific task.
In hiring, NLP shows up anywhere text or speech needs to be understood rather than just stored. A resume parser uses NLP to extract structured fields from an unstructured document. A semantic search tool uses NLP to match a recruiter's plain-language query to relevant candidates.
An AI interview relies on NLP to understand a spoken answer well enough to generate a genuine follow-up. The common thread across all of these is turning language, which computers don't natively understand the way they understand structured data, into something a system can reason about.
Frequently asked questions
Is NLP the same thing as a large language model?
No. NLP is the broader field of making computers understand and generate language. A large language model is a specific, modern type of system built to perform many NLP tasks at once, rather than one tool per task.
Where does NLP show up in the hiring process?
It underlies resume parsing, semantic candidate search, and the language understanding behind conversational AI interviews, anywhere text or speech needs to be interpreted rather than just stored or displayed.
Does NLP work equally well across languages?
Performance can vary. Most NLP systems are trained on far more data in some languages than others, which typically means accuracy is strongest for widely used languages and can drop for less common ones.
Related pages
See NLP applied to real interview conversation
Intervieux uses natural language understanding to follow a candidate's actual answers during an AI interview, not just match against a fixed script.