Open Access
Open access
Sustainability, volume 17, issue 3, pages 982

Transformation of the Dairy Supply Chain Through Artificial Intelligence: A Systematic Review

Gabriela Joseth Serrano-Torres 1
Alexandra Lorena López-Naranjo 2
Pedro Lucas Larrea-Cuadrado 2
Guido Mazón-Fierro 3
Publication typeJournal Article
Publication date2025-01-25
Journal: Sustainability
scimago Q1
SJR0.672
CiteScore6.8
Impact factor3.3
ISSN20711050
Abstract

The dairy supply chain encompasses all stages involved in the production, processing, distribution, and delivery of dairy products from farms to end consumers. Artificial intelligence (AI) refers to the use of advanced technologies to optimize processes and make informed decisions. Using the PRISMA methodology, this research analyzes AI technologies applied in the dairy supply chain, their impact on process optimization, the factors facilitating or hindering their adoption, and their potential to enhance sustainability and operational efficiency. The findings show that artificial intelligence (AI) is transforming dairy supply chain management through technologies such as artificial neural networks, deep learning, IoT sensors, and blockchain. These tools enable real-time planning and decision-making optimization, improve product quality and safety, and ensure traceability. The use of machine learning algorithms, such as Tabu Search, ACO, and SARIMA, is highlighted for predicting production, managing inventories, and optimizing logistics. Additionally, AI fosters sustainability by reducing environmental impact through more responsible farming practices and process automation, such as robotic milking. However, its adoption faces barriers such as high costs, lack of infrastructure, and technical training, particularly in small businesses. Despite these challenges, AI drives operational efficiency, strengthens food safety, and supports the transition toward a more sustainable and resilient supply chain. It is important to note that the study has limitations in analyzing long-term impacts, stakeholder resistance, and the lack of comparative studies on the effectiveness of different AI approaches.

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