What is Natural Language Processing (NLP)?
Natural Language Processing (NLP) is the branch of AI focused on enabling computers to understand, interpret, and generate human language. In hiring, NLP is the core technology behind resume parsing, automated candidate communication, and sentiment analysis in interview feedback.
Natural Language Processing (NLP) is the foundational technology that enables modern recruitment AI to understand, interpret, and generate human language in a way that goes far beyond simple keyword matching.
Instead of treating resumes, job descriptions, and feedback as raw text, NLP systems extract meaning, structure, and intent. This allows software to read a resume similarly to how a human recruiter would, and to respond in language that feels natural rather than robotic.
Why NLP Matters in Recruitment
Nearly every advanced AI capability in a hiring platform depends on NLP:
- Resume parsing: Turning unstructured documents (like PDFs) into structured candidate profiles.
- Automated communication: Sending context-aware, natural-sounding messages to candidates.
- Job description analysis: Understanding requirements, seniority, and skill expectations.
- Semantic search and matching: Letting recruiters search in plain English (e.g., “backend engineers in London with fintech experience”) and find relevant candidates even when wording differs.
- Feedback and notes analysis: Interpreting interviewer comments and sentiment.
Without NLP, AI in hiring would be limited to rigid keyword filters and structured form fields. With NLP, platforms can:
- Extract structured data from messy, unformatted resumes.
- Normalize different ways of describing the same skill or role.
- Surface candidates who match implicit criteria that were never explicitly written.
Core NLP Tasks Used in Hiring
1. Named Entity Recognition (NER)
Identifies and classifies key entities in text, such as:
- Candidate names
- Company names