Abstract
This study examines employee burnout in AI-integrated customer service roles within the Malaysian e-commerce sector, focusing on the influence of task shifting, organizational support, and perceived AI monitoring, grounded in the Job Demands-Resources model. A quantitative cross-sectional design was adopted, drawing on survey data collected from 172 employees working in customer service and related functions in medium-to-large e-commerce organizations located in the Klang Valley. The data were analyzed using descriptive statistics, reliability analysis, Pearson correlation, and multiple regression to assess the relationships between AI-related job demands, organizational resources, and burnout outcomes. The findings show that task shifting and perceived AI monitoring are significantly and positively associated with employee burnout, indicating higher levels of emotional exhaustion, disengagement, and reduced personal accomplishment when AI implementation is poorly managed. In contrast, organizational support exhibits a significant negative relationship with burnout, demonstrating its protective role in mitigating the adverse effects of increased job demands. Employees who reported access to adequate training, clearer communication, and responsive managerial support experienced lower levels of burnout despite exposure to AI-driven changes. The study offers practical implications for e-commerce organizations implementing AI in customer service functions, highlighting the need for structured task redistribution, transparent and non-intrusive monitoring practices, and sustained organizational support mechanisms. By adopting a human-centered approach to AI integration, organizations can balance operational efficiency with employee well-being, reduce burnout risks, and promote sustainable service performance in technology-intensive environments.