Firms have been pushed to reassess their organizational frameworks and the procedures linked to recruitment as a result of recent breakthroughs in artificial intelligence (AI). The complex effects that AI has on talent acquisition tactics are investigated in this study. When it came to gathering primary data that was pertinent to the study, a quantitative methodology that utilized a cross-sectional design was utilized. The purpose of this study was to gain an understanding of the significance of utilizing AI technology in the process of formulating efficient strategies for talent acquisition by collecting data from 662 participants. According to the findings of research, AI-related aspects have a significant impact on talent acquisition management techniques. It incorporated techniques such as automated review phases in the recruitment process, which are places where artificial intelligence (AI) tools, such as chatbots, play an essential role. The findings unambiguously and unequivocally suggest that relational and transactional AI components in recruiting are equally vital for the delivery of good recruitment services. The application of technology results in a considerable improvement in the overall quality of the services provided by recruitment agencies. E-human resource management needs to make progress in three core areas in order to develop effective techniques for talent acquisition. These areas are context, various stakeholders, and sustainable outcomes. The results of this study demonstrate the need of taking into account a wide range of contextual factors while simultaneously investigating the complementary aspects of relational and transactional elements in the field of AI recruitment. In order to improve the efficiency and relevance of AI tools in the ever-changing talent market, it is vital to continually review and adapt them to the specific circumstances of the local environment.
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Wu TIANYOU
Oyyappan Duraipandi
Ma HAIMING
International Journal of Computational and Experimental Science and Engineering
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TIANYOU et al. (Mon,) studied this question.
www.synapsesocial.com/papers/68d4764731b076d99fa6e082 — DOI: https://doi.org/10.22399/ijcesen.3743
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