Applications of artificial intelligence in supply chain forecasting in the food industry: A systematic review

Veliz Guzman A.S.; Oropeza Aguilar F.D.; Mejia-Ayala D.; Méndez-Gutiérrez L.L. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/leird2025.1.1.452

Resumen

In recent years, the food processing industry has experienced an increase in challenges related to operational efficiency, sustainability, and responsiveness to ever-changing demands. In this scenario, artificial intelligence (AI) has emerged as a key tool with great potential to revolutionize the food supply chain by addressing fundamental issues such as demand forecasting, process improvement, quality control, and waste reduction. This Systematic Literature Review (SLR) aims to identify and examine the most significant studies published between 2020 and 2025 that investigate the use of AI—including techniques such as machine learning, deep learning, and explainable models—in prediction and optimization tasks within the food sector. The methodology adopted is based on the PICOC approach, which allowed specific search criteria to be defined within the Scopus database, thus ensuring the relevance and scientific rigor of the selected articles. In total, 50 studies were examined that demonstrate how artificial intelligence can be applied at various stages of the supply chain: from estimating the shelf life, demand, or deterioration of perishable products, to automating processes using computer vision and digital twins for real-time monitoring. The findings indicate that the implementation of predictive models and intelligent systems not only increases operational efficiency but also promotes the sustainability of the agri-food system. This review provides a structured overview of the current state of research, identifies the most widely used technologies, and highlights existing gaps, proposing future lines of work focused on technological accessibility, the integration of explainable AI, and scalability for small and medium-sized enterprises in the sector. © LEIRD 2025.All rights reserved.

Instituciones: Universidad Tecnológica del Perú