<p>This study investigates the adoption of artificial intelligence (AI) in the United Arab Emirates (UAE) healthcare supply chains (HSC) and the priority domains for implementation. A conceptual framework was adapted from the literature and used to prioritize adoption determinants via a hybrid Analytic Hierarchy Process–Entropy (AHP–Entropy) approach. Application domains were also ranked using expert judgements. Empirical data were collected from senior UAE healthcare supply-chain professionals. The integrated AHP–Entropy weighting yields a robust prioritization that balances expert judgements with objective dispersion measures. Results highlight the salience of a customer satisfaction focus, change-management initiatives, and real-time intelligence capabilities in driving AI adoption. Distribution and transport optimization, followed by sales and operations planning, emerged as the most suitable domains for early AI deployment. The findings provide policymakers and healthcare leaders with an evidence-based roadmap to strengthen resilience, efficiency, and sustainability in healthcare logistics through targeted AI adoption. Methodologically, this study represents one of the first UAE-focused applications of a hybrid AHP–Entropy approach to jointly prioritize determinants and domains in HSCs.</p>