Abstract

Artificial intelligence (AI) is promptly changing the nature of food production and processing to increase safety, efficiency, quality assurance, and sustainability throughout the farm-to-fork chain. This review discusses the recent developments in AI in the food manufacturing industry, such as machine learning (ML), deep learning (Dl), computer vision (CV), hyperspectral imaging (HSI), robotics, Internet-of-Things (IoT) integration, and natural language processing. These technologies allow detecting contamination and fraud in real-time, near-perfect predictive maintenance less 30% unplanned downtime, automated quality checks with up to 96%–100% accuracy, AI-enabled predictive maintenance (PdM) has demonstrated its effectiveness by decreasing unplanned downtime in industrial case studies through a reduction rate that reaches 30% of total downtime, resource-efficient smart factories, and creative AI-driven formulation of products. New paradigms include digital twins, explainable AI, computational gastronomy, and cultured meat production, highlighting the transformative power of AI. Some of the solutions include standardized datasets, lightweight architectures, federated learning, and scalable deployment training programs. When used responsibly, AI can help create food systems that meet regulatory requirements while achieving sustainable development goals and circular economy standards, and all three Sustainable Development Goals, like Zero Hunger (SDG 2), Responsible Consumption and Production (SDG 12), and Climate Action (SDG 13).