Research on the Impact of Artificial Intelligence on Human Resource Management in Listed Enterprises and Countermeasures

The integration of artificial intelligence into human resource management has accelerated significantly, particularly within listed enterprises that face unique pressures from investors, regulators, and public scrutiny. Drawing upon the resource-based view, signaling theory, and sociotechnical systems theory, this study develops a comprehensive theoretical framework to examine the multifaceted impact of AI on HRM in listed enterprises. The analysis identifies three primary impact pathways: algorithmic decision-making in recruitment and selection, predictive analytics in performance management and retention, and automation in HR service delivery. The study further explores organizational implications, including structural changes within HR functions, evolving workforce skill requirements, and transformations in employee-employer relationships. In response to these challenges, countermeasures are proposed across four domains: strategic alignment of AI with HR objectives, ethical governance frameworks, workforce reskilling initiatives, and hybrid human-AI work design. The framework provides theoretical contributions to the AI-HRM literature and offers practical guidance for executives, HR leaders, and boards in listed enterprises seeking to leverage AI for competitive advantage while managing associated risks.