Author(s): Rahul Kumar Choudhary, Abhijeet Singh, Monika Singh
The growing infusion of artificial intelligence (AI) into Human Resource Management (HRM) promises to reshape the way organizations recruit, develop, and manage employees. However, evidence about whether AI truly enhances organizational effectiveness remains inconclusive. This paper develops and empirically examines a model in which AI adoption in HRM affects organizational effectiveness both directly and indirectly through two mediators: organizational learning capability and technological trust. Grounded in socio-technical systems theory, the knowledge-based view, and the technology acceptance literature, we argue that AI improves outcomes when organizations possess the capacity to learn from new data-driven insights and when stakeholders trust the systems that generate them. Using a two-wave survey of medium and large firms, we test the model with Partial Least Squares Structural Equation Modeling (PLS-SEM) and complement it with fuzzy-set Qualitative Comparative Analysis (fsQCA) to explore equifinal pathways. Results show that organizational learning capability and technological trust are both significant mediators, suggesting that AI is not a plug-in solution but rather a socio-technical transformation. The study contributes to theory by integrating technological and organizational perspectives, and to practice by highlighting that managers must invest not only in AI systems but also in trust-building and learning infrastructures to realize their benefits.