ARTIFICIAL INTELLIGENCE APPLICATIONS IN RECRUITMENT AND TALENT ACQUISITION: OPPORTUNITIES AND ETHICAL CONCERNS

Abstract

This study examines the applications of artificial intelligence in recruitment and talent acquisition, with a specific focus on opportunities and ethical concerns. As organizations increasingly adopt AI-based tools for resume screening, candidate ranking, automated shortlisting, and hiring decision support, it becomes important to evaluate both their practical benefits and potential risks. The study uses a quantitative approach to analyze candidate-level recruitment data consisting of 5,000 records and 18 variables, including AI resume score, AI bias score, skill-based indicators, demographic characteristics, educational background, work experience, and hiring outcomes. The findings show that AI resume score is strongly associated with hiring decisions, indicating that AI-supported screening can improve efficiency and assist organizations in identifying suitable candidates. Skill-related variables such as technical skill score, communication score, aptitude test score, coding test score, and years of experience also contribute to recruitment outcomes. However, the results reveal ethical concerns, particularly differences in hiring rates across gender and university tier. The association between AI bias score and hiring decisions further highlights the need for fairness monitoring, transparency, explainability, and human oversight in AI-assisted recruitment. The study concludes that AI can enhance recruitment efficiency and support data-driven talent acquisition, but it should be implemented responsibly to avoid unfair outcomes. The findings contribute to human resource management, business analytics, and ethical AI governance by emphasizing the balance between technological efficiency and fairness in recruitment practices.