The expeditious growth of artificial intelligence (AI) is revamping human resource management (HRM), specifically in the context of growing organizational emphasis on sustainability. Although previous studies have examined AI in HRM and sustainable HRM independently, less attention has been given to their integration and its implications for employee outcomes. This study develops a conceptual framework that integrates AI capabilities with sustainable HRM practices to describe their combined influence on multidimensional employee performance. Based on the Resource Based View (RBV), Ability Motivation Opportunity (AMO) theory, and Socio-Technical Systems theory, the study conceptualizes AI as a strategic enabler of ecological (green HRM), social (diversity, equity, and inclusion and employee well-being), and economic HRM practices. The framework proposes that sustainable HRM practices mediate the relationship between AI integration and employee performance outcomes, including productivity, innovation, engagement, well-being, retention, and pro-environmental behaviors. Furthermore, ethical AI governance and transformational leadership are identified as key boundary conditions shaping these relationships. The study advances theory by extending current frameworks of employee performance into a multifaceted, sustainability-oriented construct and bridging the gap between AI-enabled HRM and sustainable HRM literatures. Basically, it offers a structured roadmap for organizations looking to use AI responsibly and improve long term employee results. The paradigm offers a foundation for future empirical studies across different organizational and institutional contexts.
Nidhi Singh (2026) studied this question.