Applications, Opportunities, and Challenges of Artificial Intelligence in Human Resource Management

Artificial Intelligence has become a core driving force for the digital transformation of human resource management. Artificial intelligence technologies are widely deployed across full-spectrum HR workflows including talent recruitment, staff training, performance appraisal and talent development, helping enterprises streamline operational efficiency, realize data-supported scientific decision-making and optimize workforce governance. Nevertheless, the large-scale rollout of AI also brings prominent risks such as algorithmic bias, employee data privacy leakage, opaque decision logic and ethical governance dilemmas. Taking scoping literature review and case analysis as dual research approaches, this review systematically sorts out the practical application value, inherent bottlenecks and sustainable development paths of AI in all scenarios of human resource management, balancing theoretical depth and practical operability. The research results reveal that AI can remarkably lift HR operation efficiency, optimize person-job matching accuracy and underpin data-driven management decisions. However, multiple prominent obstacles remain unsolved, including algorithmic discrimination, privacy infringement, black-box decision-making mechanisms and AI's deficiency in capturing human emotional nuances. This review proposes that organizations ought to perfect algorithm governance systems, tighten data security protection, boost decision transparency and retain human supervision links to achieve responsible AI implementation. In the long run, the future development direction of human resource management will center on effective human-AI collaboration, striking a dynamic balance between technological innovation and people-oriented management philosophy.