A BIBLIOMETRIC ANALYSIS ON THE ROLE OF ARTIFICIAL INTELLIGENCE-ENABLED RECRUITMENT TOWARDS SUSTAINABILITY: TRENDS AND FUTURE DIRECTIONS

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Purpose: By increasing productivity, decreasing bias, and promoting long-term workforce development, artificial intelligence (AI) in sustainable recruitment is revolutionizing talent acquisition. For HR experts, job seekers, employees, and AI developers, this study offers a thorough bibliometric review of AI-driven hiring processes. Through examination of research trends, methodologies, and applications of AI in sustainable recruitment, this study highlights key advancements, challenges, and future research directions. Design/ Methodology/ Approach: A comprehensive literature review using PRISMA was carried out, looking at 105 publications from the Scopus database that were published between 2015 and 2025. Multiple analytical software tools were utilized to conduct bibliometric and network analysis. Findings: According to the study's findings, the topic's considerable increase in researchers has led to a notable boom in research in recent years. The topic of “AI and Sustainable Recruitment” has seen expanding publications, now reaching a total of 49. Technological Forecasting and Social Change stands out as the leading contributing journal, having published four articles on the subject. India and the USA emerge as the most productive countries in this domain, challenging the traditional distinction between developed and developing nations. Additionally, the study identifies Malik A as the most prolific author, with three published papers and a total of 63 citations. Furthermore, the thematic analysis conducted in this study has helped outline epochal arenas for emerging research, offering priceless insights into forthcoming trends and directions within the field. Originality: This study offers a multi-dimensional analysis of AI-based sustainable recruitment literature. By employing advanced visualization techniques, this research provides a greater understanding on the topic. The perceptivity from this work bridges the gap between academic research and technology, fostering innovation, efficiency, and strategic decision-making in talent acquisition.

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