Understanding strategic leadership strategy related to artificial intelligence (AI) applications in supply chain pandemic logistics
DOI:
https://doi.org/10.34140/bjbv8n1-016Palavras-chave:
supply chain management, strategic leadership, public health, logistics, health administration, pandemic response, artificial intelligence, emergency responseResumo
The COVID-19 pandemic exposed critical vulnerabilities in healthcare supply chains, revealing the limitations of efficiency-driven logistics models under conditions of extreme uncertainty, demand volatility, and ethical strain. This qualitative study examines how leadership practices, organizational culture, and team dynamics shape the implementation and sustained use of artificial intelligence (AI) technologies in healthcare logistics during pandemics and large-scale healthcare emergencies. Drawing on semi-structured interviews with 15 participants, including healthcare logistics officers, AI application experts, and organizational development professionals, the study conceptualizes AI implementation as a socio-technical transformation rather than a purely technological intervention. Findings indicate that AI-enhanced logistics systems significantly improved situational awareness, accelerated decision cycles, reduced waste, and enabled scenario-based planning. However, these benefits were realized only when AI tools were embedded within leadership practices characterized by transparency, ethical accountability, and collaborative sensemaking. Participants emphasized that trust, explainability, and perceived fairness were critical conditions for adoption, particularly when AI supported allocation of scarce, life-saving resources. Conversely, inadequate leadership readiness, role ambiguity, poor user experience, and change fatigue undermined AI effectiveness and eroded workforce trust. The study further demonstrates that AI amplified existing cultural patterns: learning-oriented cultures leveraged AI to strengthen resilience and organizational learning, while blame-oriented cultures experienced resistance and fragmentation. Overall, the findings underscore that successful AI deployment in healthcare logistics during crises depends less on algorithmic sophistication than on leadership behavior, cultural alignment, and ethical governance. The study contributes to both theory and practice by offering a human-centered framework for integrating AI into healthcare supply chains to enhance resilience, legitimacy, and preparedness for future emergencies.
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