Artificial Intelligence Applications in the Food Industry: Transforming Food Quality, Production, and Sustainable Food Systems

Abstract

Artificial intelligence (AI) is increasingly transforming the food industry by enabling data driven approaches to food quality assessment, safety management, product development, processing, packaging, storage, and supply chain operations. The growing availability of data from sensors, imaging systems, analytical instruments, and digital production platforms has created new opportunities for machine learning, deep learning, computer vision, and predictive analytics across the food chain. This chapter reviews the current applications of these technologies in food systems, with particular emphasis on quality and safety assessment, formulation and product development, process optimization, intelligent packaging, shelf life prediction, logistics, and supply chain management. The potential contribution of AI to sustainable food systems is also discussed, including food loss and waste reduction, resource optimization, and circular food production. In addition, emerging applications of generative AI are examined in areas such as food innovation, sensory and consumer research, and research support. Despite these opportunities, challenges related to data quality, model validation, interpretability, privacy, infrastructure, and human oversight remain important considerations. Overall, AI has considerable potential to support more efficient, responsive, and sustainable food systems when computational approaches are integrated with food science expertise and appropriate experimental validation.