AI Resume Analyzer: A Review and Case Study of an NLP-Driven Recruitment System

The growing demand for efficiency in recruitment has accelerated the adoption of AI-powered resume screening systems. This paper reviews the evolution of resume analysis approaches, from keyword-based filters to large language models (LLMs) and Retrieval-Augmented Generation (RAG) pipelines. A critical analysis compares accuracy, scalability, fairness, and regulatory compliance across methods. Ethical concerns, includ- ing bias and privacy, are discussed alongside recent regulations such as the EU AI Act and GDPR. To complement the review, we present a case study of an AI Resume Analyzer system, followed by experimental validation. The paper concludes with limitations and future research directions for trustworthy, scalable, and fairness-aware recruitment systems.