Optimizing supply chains with AI: a systematic review through the lens of systems theory

This paper investigates the impact of Artificial Intelligence (AI) on supply chain integration and overall performance through a systematic literature review. Grounded in Systems Theory, the study analyzed 112 peer-reviewed articles published between 2010 and 2024, selected using well-defined inclusion criteria such as relevance to AI applications in supply chain management (SCM) and publication in high-quality journals. The review process involved a multi-stage screening procedure, including an initial assessment of titles and abstracts, followed by a detailed full-text evaluation conducted independently by two researchers to ensure reliability. Key information from the studies was extracted and analyzed using a thematic synthesis approach, enabling the identification of recurring patterns, relationships, and themes across the reviewed literature. The findings highlight AI’s potential to enhance supply chain processes, improve information sharing, and increase transparency. Significant performance improvements were identified in production, procurement, logistics, and inventory management, driven by AI’s ability to facilitate seamless integration and real-time decision-making. The thematic synthesis approach provided structured insights into the diverse findings, leading to the development of a comprehensive conceptual framework for strategic AI implementation in supply chain management. These insights contribute to both academic research and practical applications, demonstrating AI’s transformative role in optimizing supply chain operations.