Natsir K, Irham
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ADOPTION OF AI IN RECRUITMENT: IMPLICATIONS FOR BIAS, EFFICIENCY, AND CANDIDATE EXPERIENCE Panggabean, Bungaran; Raldianingrat, Welis; Baharudin, Baharudin; Natsir K, Irham
Journal of Economic, Bussines and Accounting (COSTING) Vol. 8 No. 4 (2025): COSTING : Journal of Economic, Bussines and Accounting
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/m386pt53

Abstract

However, while the integration of AI into recruitment practices offers numerous potential benefits, it also raises critical concerns regarding fairness, transparency, and candidate experience. A central issue is the risk of algorithmic bias. The purpose of this study is to analyze the adoption of Artificial Intelligence (AI) in the recruitment process: its implications for bias, efficiency, and candidate experience. This study employs a literature review methodology to systematically analyze and synthesize existing research on the adoption of Artificial Intelligence (AI) in recruitment, with a particular focus on three interrelated aspects: bias, efficiency, and candidate experience. This literature review explored the multifaceted implications of Artificial Intelligence (AI) adoption in recruitment, focusing on three key dimensions: bias, efficiency, and candidate experience. The findings reveal that while AI technologies offer substantial benefits in terms of operational speed and cost reduction, they also introduce significant ethical, social, and psychological challenges.