Critical Success Factors for Artificial Intelligence Application in Healthcare Supply Chain Management: A TOE-Based Study of Mubadala, UAE

Abstract

Artificial intelligence (AI) has become an important digital capability for improving organisational efficiency, decision-making, and operational performance across different sectors, including healthcare. However, while AI has been widely examined in clinical and general healthcare contexts, limited empirical evidence exists on the critical success factors influencing AI application in healthcare supply chain management (HSCM), particularly in the United Arab Emirates. This study investigates the critical success factors for AI application in HSCM using the Technology–Organisation–Environment (TOE) framework, with specific focus on healthcare organisations in Mubadala, UAE. The study examines the effects of technological, organisational, and environmental factors on AI application and evaluates the influence of AI application on four key HSCM outcomes: demand forecasting, inventory management, logistics optimisation, and risk management. A quantitative research approach was adopted, and data were collected through questionnaires from 323 respondents drawn from managerial, logistics, and technical roles within healthcare supply chain organisations in Mubadala, UAE. The data were analysed using partial least squares structural equation modelling (PLS-SEM). The findings revealed that technological factors had the strongest positive effect on AI application (β = 0.475, p < 0.05), followed by environmental factors (β = 0.312, p < 0.05) and organisational factors (β = 0.146, p < 0.05). Together, these factors explained 61.3% of the variance in AI application. Furthermore, AI application had significant positive effects on demand forecasting (β = 0.510, p < 0.05), risk management (β = 0.445, p < 0.05), inventory management (β = 0.430, p < 0.05), and logistics optimisation (β = 0.426, p < 0.05).The study concludes that technological, organisational, and environmental factors are significant critical success factors for AI application in HSCM, with technological readiness emerging as the strongest predictor. The findings also confirm that AI application improves key healthcare supply chain outcomes by enhancing forecasting accuracy, inventory control, logistics efficiency, and risk management capability. This study contributes to the literature by extending the TOE framework to AI-enabled healthcare supply chain management and by providing empirical evidence from the UAE context. Practically, the study offers insights for healthcare managers, policymakers, and supply chain professionals seeking to strengthen healthcare supply chain performance through effective AI application.