Purpose Artificial intelligence (AI) has brought major disruptions in the new generation human resources (HR) ecosystems. The research community as well as chief human resources officers (CHROs) have been taking strong initiatives to examine the use of AI in human resource management (HRM) function, including harmonious human–machine collaboration. The AI-HRM area is under-researched, and this study addresses an important research gap regarding the benefits and challenges of AI applications in HRM. Design/methodology/approach The study adopts a qualitative research methodology (abductive case research) and collects data from multiple sources in three Indian companies. These organizations span diverse sectors and were at different stages of AI adoption in HRM at the time of the study. The multi-data-sources strategy helps triangulation and establishes credibility of the research. Findings The findings provide a clear view about the benefits of AI applications in HRM, higher productivity, recruitment efficiency, adaptive learning and high-quality HR decisions. The study also underpins key challenges, including a lack of human touch, employees’ loss of control over jobs and the fear of losing jobs to AI. Originality/value The research provides a theoretical contribution to the growing AI-HRM literature in the context of the theory of cost economics in the context of recruitment efficiency as well as leveraging adaptive learning from the context of the multi-level organizational learning framework to improve the performance of the HR function. The research also provides significant managerial insights for CHROs recommending that they embrace humanized AI in the HRM function and institutionalize AI ethics.
Singh et al. (Tue,) studied this question.