THE MODERATING ROLE OF ARTIFICIAL INTELLIGENCE IN THE JOB DEMANDS–RESOURCES MODEL: IMPLICATIONS FOR WORK ENGAGEMENT, JOB SATISFACTION, AND FIRM PERFORMANCE
Authors/Creators
- 1. School of Management, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia College of Administration and Economics, University of Baghdad, Iraq Baghdad Al-Karkh First Education Directorate
Description
By viewing AI as both a job demand and a job resource, this study incorporates AI into the Job Demands–Resources (JD–R) framework. Automation, smart analytics, and decision-support systems are examples of AI technologies that lower routine workloads, increase accuracy, and facilitate better decision-making. But they also bring with them difficulties, such as technostress, heightened surveillance, and the requirement for ongoing skill improvement. Along with productivity benefits, workers must adjust to data-driven procedures and algorithmic systems, which create new emotional and cognitive demands. AI is a resource that supports competence development and engagement by improving autonomy, streamlining workflows, and offering personalised learning opportunities and real-time feedback. By lowering errors and providing performance insights, AI can increase job satisfaction; nevertheless, over-reliance on AI or inadequate training may erode confidence and autonomy. Similar to this, AI increases employee engagement at work by encouraging creativity and streamlining processes, but too much system control may diminish workers' sense of ownership. By boosting productivity, fostering creativity, and bolstering predictive capacities, AI also improves business success. AI improves service delivery, demand forecasting, and operational stability for Iraq's Ministry of Electricity. This study examines the relationships among job demands, job resources, job satisfaction, work engagement, and firm performance within the JD–R model. It suggests that the relationship between demands, resources, and work engagement—all of which have an impact on company performance—is mediated by job satisfaction. The study expands JD-R theory and provides useful insights for striking a balance between demands and resources to improve performance, engagement, and happiness by connecting employee-level issues to organisational outcomes.