AI-DRIVEN HRM AND EMPLOYEE INNOVATIVE BEHAVIOR THROUGH WORK ENGAGEMENT AND CREATIVE SELF-EFFICACY - Yixuan Li; Arti Pandey (LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta), 2026)
Abstract− The rapid advancement of artificial intelligence technology has accelerated the popularization of AI- Driven HRM among modern corporate organizations. Current academic literature predominantly concentrates on the efficiency advantages brought by this new-type human resource management model. Few scholarly works have further discussed how it influences employee Innovative behavior from the perspective of individual internal psychological mechanisms. Grounding on Self-Determination Theory (SDT), this study carries out quantitative questionnaire research targeting staff members from five Internet enterprises located in Zhengzhou City. The empirical results generated by PLS-SEM statistical analysis demonstrate that AI- Driven HRM can positively predict employee adaptability and employee Innovative behavior in the workplace, and adaptability presents a prominent mediating effect between the above two research variables. This research enriches the practical application scenarios of Self-Determination Theory in the intelligent human resource management field. It also offers feasible empirical references for enterprises to optimize internal innovative performance via the implementation of AI- Driven HRM. Keywords: AI-Driven HRM; Employee Innovative Behavior; Work Engagement; Creative Self-Efficacy; Adaptability