This study explores AI in enterprise HR to address manual fragmentation and boost digital transformation. It reviews key theories and models like rule-based systems, machine learning, deep learning, and hybrid methods. The research examines AI's HR advantages and limitations, including bias, opacity, and privacy issues. A multidimensional AI-HR framework was validated on recruitment, performance, and training data, using predictive analytics and human feedback. Results show significant gains in selection accuracy, performance forecasting, and personalized training, but also highlight challenges in interpretability, data security, and organizational readiness. AI-driven HR can enhance efficiency, transparency, and employee engagement with stronger data infrastructure, algorithmic transparency, and adaptive governance.
Wang et al. (2025) studied this question.