ARTIFICIAL INTELLIGENCE-DRIVEN HUMAN RESOURCE MANAGEMENT AND EMPLOYEE JOB PERFORMANCE IN THE UAE PUBLIC SECTOR: THE MEDIATING ROLE OF INNOVATION - Ebtesam Abdulla AlDhanhani; Ahmad Nur Aizat Bin Ahmad (International Journal of Computer Information Systems and Industrial Management Applications, 2026)
Artificial intelligence (AI) is increasingly embedded in human resource management (HRM), yet its performance consequences depend on whether employees perceive AI-enabled HR systems as fair, transparent, privacy-protective, and trustworthy. We examine the direct effects of four AI-HRM dimensions—algorithmic fairness (bias mitigation), transparency, privacy protection, and trust—on employee job performance and test innovation as a mediating mechanism in the United Arab Emirates (UAE) public sector. Guided by the Resource-Based View, we administered a cross-sectional survey to employees of Dubai Municipality. Of 382 returned questionnaires, 376 valid responses were analyzed using SPSS and Partial Least Squares Structural Equation Modeling. Fairness, transparency, and privacy produced statistically significant direct coefficients, but the effects were negligible in magnitude: fairness and transparency were negative, privacy was positive, and trust was nonsignificant. Innovation generated substantially larger indirect effects from fairness and transparency, with transparency producing the dominant pathway (β = .792, p < .001). Fairness and transparency exhibited competitive mediation, privacy showed a direct-only effect, and trust showed negative indirect-only mediation. These findings indicate that AI-HRM creates performance value primarily when ethical and governance capabilities are converted into innovative work practices. Because the job-performance model reached the boundary value R² = 1.000 and the innovation-to-performance effect size was exceptionally large, we interpret the model-quality statistics cautiously and treat them as priorities for robustness re-estimation.