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Artificial intelligence (AI) - technology that mimics human cognition through learning and decision-making is transforming food safety management across multiple domains. This presentation examines the evolution of AI from its conceptual origins to its modern-day applications, driven by machine learning, big data, and automation. The strength of AI concerning food safety lies probably in the advanced data management and integration, e.g. integrating real-time and historical data across silo’s, handling unstructured data and identification of meaningful patterns humans would miss. AI can predict risks before they materialize and supports the shift from reactive quality control to risk-based prevention. Across all domains, AI is increasingly used for trend monitoring, identifying emerging risks and patterns in contamination, consumer complaints, and regulatory non-compliance. AI adds improved accuracy and consistency. This enables proactive interventions and more agile food safety strategies. Nevertheless, there are currently several limitations like data quality and availability, limited labelled training data, lack of standards and validation, and others. Relatore: Ronald Niemeijer, Global Brand Manager R-Biopharm AG