The swift integration of artificial intelligence (AI) in the human resource field has changed conventional HR practices to data-driven and predictive systems. This paper investigates the effect of AI-based HR analytics and AI implementation on the retention of employees and their decision-making performance (the dependent variables) and employee engagement as a confounding factor. A quantitative research design was used, and 688 respondents in different sectors were used in India to collect primary data using a structured questionnaire. Data were processed with the help of Partial Least Squares Structural Equation Modelling (PLS-SEM). The results indicate that AI-driven HR analytics and AI integration are highly effective in raising the rates of employee engagement, which, in turn, positively affects employee retention and effectiveness in decision-making. The direct impact of AI-driven HR analytics on the effectiveness of decision-making, however, turned out to be insignificant, which means that the technological adoption in itself does not imply a better decision outcome. Moreover, the correlation between the integration of AI and the effectiveness of decision-making did not significantly rely on employee engagement, which also indicates the complexity of the decision processes within the organisation. The paper adds value to the body of knowledge by both offering empirical data from a developing economy and also by incorporating both technological and behavioural approaches into a single system. The results highlight the need to integrate AI and human-centred methods to deliver successful HR services.
Prasad et al. (Tue,) studied this question.
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