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The aim of this research is to explore the mediating and moderating effects of various HR functions and regulatory environments on the relationship between AI integration and data-driven decision making in HRM. The study was conducted in a corporate sector in Malaysia, focusing on businesses actively integrating AI into their HRM functions. A total of 376 individuals successfully submitted the questionnaire, representing an 83.5% response rate. The direct and indirect effects of Workforce Planning (WP), Learning and Development (LD), Employee Engagement and Retention (EER), Performance Management (PM), Talent Acquisition (TA), and Data-Driven Decision Making (DDM) were examined through the partial least squares structural equation modeling approach (PLS-SEM). The results demonstrate that AI-enriched HR functions, including workforce planning, learning and development, employee engagement & retention, performance management, and talent acquisition, play a critical role in driving DDM.
Li et al. (Fri,) studied this question.