The evolving role of human resource management along side artificial intelligence is explored in this study. Organizations are more inclined towards emphasizing sustainability through long-term retention of employees in this era of digital transformation. Artificial intelligence and machine learning have subsumed almost all human resource functions which mandates this study further. A total of 86 articles were extracted from Scopus database and Biblioshiny along with VOS viewer software was employed to provide a comprehensive overview of the existing literature on this subject. The findings revealed four major clusters that collectively represent the current body of knowledge, further supported by the analysis conducted through Biblioshiny. The study has also proposed an A-M-M-O framework that categorizes the mediators, moderators, and outcomes identified through cluster analysis. Furthermore, the research identifies a significant gap in theoretical foundations and the absence of a comprehensive conceptual framework explaining the integration of artificial intelligence into HR functions. To address this gap, the study establishes the relevance of artificial intelligence in human resource management through the application of economic and sociological perspectives, including Human Capital Theory, Social Exchange Theory, and Job Embeddedness Theory. Additionally, the study identifies several emerging research areas that warrant further scholarly attention, such as predictive analytics, decision trees, random forests, employee engagement, job satisfaction, organizational performance management, and employee turnover.