Abstract
The purpose of this paper is to provide a narrative review of the job demands‐resources (JD‐R) model in the context of the healthcare workforce increasingly adopting artificial intelligence (AI). The strengths and limitations of the demand‐control and the effort‐reward imbalance models in relation to employee well-being are discussed. The paper then considers challenges of burnout, staff shortages, and the need for AI capacity building to support patient safety and decent work. We evaluate studies that use the JD‐R model to inform the question: how can AI enable or exacerbate workforce well-being and what are the implications for line management and HR support? This review discusses the importance of a multi-level approach to integrate macro-, meso-, and micro-level perspectives on workforce well-being. This paper challenges existing rational models of technology adoption by focusing on ethics and decent work in the absence of established playbooks for implementing AI strategically and safely for healthcare practitioners. The literature highlights the importance of human intelligence to validate artificial intelligence ethically and critically. We contribute novel insights into AI-mediated care and JD-R theory first by arguing for a dynamic socio-technical approach to cognitive and administrative load, emotional labour, and autonomy and control that affect professional identity beyond a simple dichotomy of resources and demands. We propose that AI is inherently ambivalent as it simultaneously enables and constrains workloads with variable well-being outcomes moderated by AI literacy, organisational support, professional autonomy, and implementation success. The proposed semi-structured interviews in England, India, Saudi Arabia, and Singapore will provide a unique four-country comparison in low-, middle-, and high-income countries in the West, Middle East, and Asia.