Analyzing the Impact on Talent Acquisition and Performance Management

Abstract

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.