This study explores the application of Artificial Intelligence (AI) in recruitment and selection, emphasizing both its effectiveness and ethical challenges. As organizations increasingly adopt AI driven tools to enhance hiring efficiency and decision accuracy, concerns regarding algorithmic bias, transparency, and candidate privacy continue to emerge. The research employs a qualitative literature review method to synthesize findings from recent scholarly publications, guided by frameworks such as the Technology Acceptance Model (TAM) and the Fairness, Accountability, and Transparency (FAT) principles. The study reveals that while AI significantly reduces recruitment time and improves role matching accuracy, it may also perpetuate systemic biases and undermine trust among applicants. Furthermore, the success of AI implementation depends not only on technical integration but also on ethical governance and candidate perception. Based on these insights, the research offers practical recommendations for organizations to adopt transparent, fair, and legally compliant AI recruitment practices. This paper contributes to the growing discourse on ethical digital transformation in human resource management and provides a multidimensional understanding of AI's role in shaping future recruitment strategies.
Raneo et al. (Thu,) studied this question.