Artificial intelligence for improving management in industrial logistics: A Systematic Review

Becerra Cabrera C.L.; Córdova Canales E.G.; Roca Becerra J.L.; Rodriguez Álvarez S.R. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/laccei2025.1.1.549

Resumen

The increasing complexity of supply chains has driven the development of advanced technological solutions in logistics management. In this context, Artificial Intelligence (AI) has transformed the way logistics processes are optimized, enabling automation, massive data analysis, and improved decision-making. However, AI implementation faces challenges, such as methodological discrepancies, outdated studies, and barriers to training and technological integration. The main objective of this systematic review was to analyze the impact of AI on industrial logistics management. To do so, methods based on the PICOC strategy and the PRISMA methodology were used, selecting 137 relevant SCOPUS studies up to 2020 that analyzed best practices and the most effective approaches. The results revealed interesting findings in terms of productivity and competitiveness. However, areas for improvement and gaps in knowledge about some methods were also analyzed, highlighting the need to optimize the adoption of these technologies. The research provides valuable guidance to decision-makers, technology developers, and academics by providing an overview of strategic tools that address the diverse needs of logistics management work areas. It also presents quantitative data, commonly used methods, and key recommendations for maximizing the benefits of AI in supply chains, ensuring more efficient and sustainable implementation.

Instituciones: Universidad Tecnológica del Perú