The role of artificial intelligence in advancing food safety: A strategic path to zero contamination

Abstract

Food safety is advancing toward zero contamination using artificial intelligence (AI) for supply chain management, quality control, contamination detection, and consumer safety. AI integrates with technologies like the Internet of Things (IoT), blockchain, and genomics to enhance traceability, predictive analytics, and pathogen identification across the food supply chain. AI applications in food safety range from detecting contaminants and monitoring supply chains to predicting potential risks and optimizing quality control processes. To attain zero contamination, the role of AI will be central in creating resilient, responsive, and efficient food safety systems that protect public health and foster consumer trust. AI promises significant benefits in mitigating risks and ensuring food integrity, challenges, including data quality, regulatory frameworks, and ethical considerations, require careful attention. Continuous innovation and strategic investments are crucial for realizing AI's full potential in addressing evolving food safety challenges and promoting global food security. Future research directions involve enhancing data-sharing practices, implementing transparent AI systems, and fostering interdisciplinary collaborations. These collaborations are keys to maximizing AI's potential in safeguarding public health and fostering a resilient food system.