The impact of artificial intelligence technologies on the economics of human resources in the government sector in Jouf region

Purpose This study investigates the association between AI-driven human resource (HR) automation and HR economics within the government service sector in the Jouf region of Saudi Arabia by measuring improvements in operational efficiency. Design/methodology/approach A total of 342 employees of the government service industry in the Jouf region of Saudi Arabia participated in the study. The data were analyzed, and the research variables were tested using SPSS software. Findings As demonstrated by increased operational efficiency, this study shows that HR economics is directly and favorably associated with the automation of HR procedures using AI technologies. Research limitations/implications The study’s conclusions are constrained by its emphasis on the Saudi public service industry, potentially affecting generalizability. Practically, it provides policymakers with empirical evidence that AI-driven HR automation supports Vision 2030s efficiency goals. Therefore, in order to show stronger causal relationships, future research should use longitudinal designs and replicate this model in a variety of domains. Practical implications For public sector leaders, this study provides empirical justification to invest in AI-driven HR automation as a direct strategy to enhance operational efficiency. It also offers a practical roadmap for aligning HR modernization with the national digital transformation goals of Saudi Vision 2030. Originality/value To the best of our knowledge, this study is one of the first to empirically examine the connection between AI-supported process automation and HR economics in the Saudi government sector. Crucially, it provides context-specific insights highly relevant to public sector modernization across the Arabian Gulf region. Consequently, researchers are encouraged to test this relationship in other socio-economic contexts.