ISSN: 2222-6990
Open access
This study explores the role of Artificial Intelligence (AI) in human resources management in HR practices, particularly in the context of selecting and attracting human resources, involving 110 participants of HR departments and workers in HR management in all small and medium-sized companies and a random (probabilistic) sample was selected from various administrative levels (manager - supervisor - specialist - Other) from Jordan. The research utilized a questionnaire-based approach and SPSS analysis. The primary objectives of the study were to explore the concept and components of AI, elucidate its significance and role in HR management, and assess the extent of AI utilization within this domain. Methodologically, a descriptive analytical method was adopted, with data collected from directors and workers in HR management through a random distribution of 375 questionnaires via email. Of these, 110 responses were deemed usable for analysis. The results revealed a predominance of male respondents (74.5%), with the highest representation found in the 20-35 age group. Most participants held positions classified as 'other' in terms of academic rank and experience. Furthermore, the questionnaire exhibited high stability and coherence, as evidenced by a Cronbach alpha coefficient exceeding 0.70. Despite this, respondents expressed low agreement regarding the company's use of AI in HR management and the process of selecting and attracting HR. Factors influencing the use of hiring engines and software explained 72.6% of the variance, underscoring the significance of technological integration in HR practices. In conclusion, the study emphasizes the importance of understanding demographic factors and their impact on AI acceptance within HR management, while also recommending further research and cross-border collaboration to effectively harness AI's potential in addressing HR challenges. Notably, an increase in the company's use of hiring engines and software was positively associated with efficient processing of data and information about job seekers, with a ? value of 0.540.
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(Alkudah et al., 2024)
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