DETERMINANTS OF JOURNALIST PERFORMANCE: AN INTEGRATED ANALYSIS IN THE AI-BASED DIGITAL ECOSYSTEM

Abstract The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed the media ecosystem and reshaped the work dynamics of journalists. This study examines the determinants of journalist performance by integrating key human resource variables while considering the mediating role of AI-based digitalization. Using a quantitative survey of journalists affiliated with the Indonesian Journalists Association (PWI) in North Sulawesi, Structural Equation Modeling (SEM) was employed to analyze direct and indirect relationships. Findings reveal that achievement motivation, compensation, and competence have a positive and significant effect on journalist performance, while emotional intelligence and LMX leadership show negative effects within the AI-driven work context. AI-based digitalization demonstrates a significant negative influence on journalist performance, suggesting emerging tensions between technological automation and traditional journalistic values. Mediation analysis indicates that AI does not consistently strengthen the influence of HR variables, and in some cases weakens performance, particularly for journalists with higher competence or emotional intelligence. These findings highlight sociotechnical misalignments within media organizations and emphasize the need for adaptive leadership, balanced AI integration, digital literacy development, and compensation systems aligned with technological change. The study contributes to HRM and media management literature by offering a holistic model of journalist performance in an AI-based digital ecosystem.