Artificial intelligence for improving management in industrial logistics: A systematic review. (#549)

Authors

Becerra Cabrera, Cristopher Luis

Cordova Canales, Elvis Giordano

Roca Becerra, Jorge Luis

Rodríguez Alvarez, Silvia Rita

Abstract

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, allowing automation, massive data analysis, and improved decision-making. However, the implementation of AI faces challenges, such as methodological discrepancies, outdated studies, and barriers with training and technological integration.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 studies from SCOPUS, 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 input in guiding decision makers, technology developers and academics, providing an overview of strategic tools that respond to the diverse needs in work areas in logistics management. In addition, it presents quantitative data, most used methods and key recommendations to maximize the benefits of AI in supply chains, ensuring a more efficient and sustainable implementation.