Author
Abstract
In the context of global digital transformation, human resource management (HRM) is undergoing significant changes, requiring scientific understanding and adaptation of management practices. The article presents a comprehensive analysis of current digitalization trends in Russia, their impact on the efficiency of personnel processes, and the challenges faced by enterprises. The study is based on a systematic methodology, including content analysis of scientific publications, regulatory documents, and comparative analysis of data from Russian and international reports. The research results identified four key areas of HRM digitalization: the use of artificial intelligence (AI) for automating recruitment, personnel assessment, and workforce planning; the implementation of cloud technologies enabling flexible data storage and processing; the gamification of training and onboarding, enhancing employee engagement and accelerating their integration into the corporate environment; the development of digital platforms for managing internal communications, document flow, and personnel analytics. Despite evident advantages such as reduced operational costs and improved accuracy of HR decisions, the digitalization process faces several barriers. These include employee resistance to change, cybersecurity risks, the need to revise labor standards, and ethical concerns related to the use of AI algorithms. Special attention is given to regional specifics: while large companies actively adopt innovations, small and medium-sized businesses lag due to high technology costs and a shortage of qualified personnel. The findings of the article can be applied in shaping corporate strategies, government programs to support business digitalization, as well as in educational courses on HR management and IT.
Suggested Citation
Mikhail K. Chernyakov & Irina A. Chernyakova, 2025.
"Digitalization of human resource management: current trends and challenges for Russian enterprises,"
Siberian Journal of Economic and Business Studies, Science and Innovation Center Publishing House, vol. 14(2), pages 166-186.
Handle:
RePEc:cxm:rusebs:14:2:2025:166-186
DOI: 10.12731/2070-7568-2025-14-2-297
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