Artificial Intelligence as a Catalyst for Supply Chain Evolution: A Multi-Case Thematic Study

This study interrogates the transformative infusion of Artificial Intelligence (AI) into Supply Chain Management (SCM), with particular emphasis on its potential to elevate efficiency, fortify resilience, and advance sustainability. Employing a qualitative, exploratory design, the research adopts a multiple-case study methodology in conjunction with thematic synthesis to examine five multinational corporations—Coca-Cola, ITC, Procter & Gamble, Nestlé, and Unilever—that have strategically deployed AI across procurement, logistics, inventory control, and sustainability practices. The findings reveal heterogeneous adoption pathways—spanning Coca-Cola’s algorithmic procurement automation, ITC’s end-to-end platformization, P&G’s enterprise-wide data integration, Nestlé’s scenario-driven network modeling, and Unilever’s IoT-enabled eco-efficiency—yet convergence emerges in three cardinal domains: systemic efficiency, adaptive resilience, and emergent sustainability. Theoretically, the study contributes by delineating distinct archetypes of AI-enabled transformation in supply chains, thereby extending the discourse on digitalization in operations management. From a managerial standpoint, the research offers concrete managerial implications, emphasizing the alignment of AI adoption with organizational priorities, resource endowments, and digital maturity as prerequisites for unlocking strategic advantage. Notwithstanding its reliance on secondary data and focus on resource-intensive enterprises, the study positions AI as a strategic inflection point in SCM evolution and calls for future inquiry into its diffusion within small-to-medium enterprises, low-margin operational contexts, and the attendant ethical and socio-economic ramifications of technologically mediated supply chains.