Integration of Artificial Intelligence in Food Processing Technologies

The food processing industry is undergoing a profound transformation with the integration of Artificial Intelligence (AI), evolving from traditional automation to intelligent, adaptive systems aligned with Industry 5. 0 principles. This review examines AI’s role across the food value chain, including supply chain management, quality control, process optimization in key unit operations, and emerging areas. Recent advancements in machine learning (ML), computer vision, and predictive analytics have significantly improved detection in food processing, achieving accuracy exceeding 98%. These technologies have also contributed to energy savings of 15–20% and reduced waste through real-time process optimization and predictive maintenance. The integration of blockchain and Internet of Things (IoT) technologies further strengthens traceability and sustainability across the supply chain, while generative AI accelerates the development of novel food products. Despite these benefits, several challenges persist, including substantial implementation costs, heterogeneous data sources, ethical considerations related to workforce displacement, and the opaque, “black box” nature of many AI models. Moreover, the effectiveness of AI solutions remains context-dependent; some studies report only marginal improvements in dynamic or data-poor environments. Looking ahead, the sector is expected to embrace autonomous manufacturing, edge computing, and bio-computing, with projections indicating that the AI market in food processing could approach 90 billion by 2030.