Leveraging AI decentralization for sustainable and ESG-compliant health-care supply chains: insights from strategic leadership and dynamic capabilities

Purpose This study aims to investigate how strategic leadership and dynamic capabilities influence clinicians’ adoption of decentralized artificial intelligence (dAI). It aims to quantify the impact of dAI on environmental, social and governance (ESG) performance in health-care supply chains and to identify the critical success factors for its scalable adoption. Design/methodology/approach The research uses a mixed-methods approach, triangulating data from four expert panel sessions with 21 seniors health-care professionals across five countries. The methodology integrates qualitative thematic analysis with quantitative, sentiment-enhanced survey data and illustrative key performance indicator (KPI) scenarios to build a comprehensive framework. Findings The results confirm that perceived usefulness and ease of use are significant predictors of dAI adoption. A key finding is that strategic leadership plays a significant amplifying role in the relationship between dynamic capabilities and technology adoption. The study also identifies six critical themes for successful implementation, including leadership vision, data trust and regulatory alignment. Practical implications This research provides health-care managers and policymakers with an actionable roadmap for deploying dAI to achieve tangible ESG benefits, such as waste reduction and enhanced supply chain resilience. The framework guides executives in translating pilot projects into scalable, high-impact solutions. Originality/value This paper addresses a notable gap in the literature by proposing an integrated framework that fuses strategic leadership, dynamic capabilities and technology acceptance theories in the context of dAI. It offers a novel, empirically-grounded guide for leveraging dAI to enhance operational efficiency and meet pressing ESG imperatives in health care.