A Study on the Transformative Effects of Artificial Intelligence Technology on Human Resource Management Models

Abstract

With the spread of artificial intelligence technology, the way traditional management in human resources management has been carried out is starting to change gradually. In line with the development logic of "deconstruction-transition-evolution", this paper will present the whole development process of artificial intelligence technology in human resources management systems. First, deconstruction refers to the movement of the boundary of algorithmic decision-making; second, it is the trend of disaggregation in job analysis; third, it is the mechanism of performance weight redistribution. Second, at the level of transition, this paper elaborates on the morphological reconstruction of management models from linear processes to dynamic networks, the migration path of managerial authority in human-machine collaboration, and the logic for setting elastic thresholds based on real-time data stream feedback. Finally, in terms of development, this paper has found that the matching accuracy of automated recruitment improves nonlinearly, there is a knowledge emergence effect due to intelligent recommendation systems, and there is a correction mechanism for turnover prediction models in human capital retention curves. In short, based on the above theoretical deduction, it can be concluded that AI technology will not only add to the existing functions of human resources management but will also change the internal logic of management models through a three-stage process of deconstruction, transition and evolution. Hopefully, this paper will provide some practical theoretical ideas and an analysis system for the subsequent empirical studies.