METHODOLOGY FOR INTEGRATING ARTIFICIAL INTELLIGENCE AND DIGITAL MONITORING TOOLS INTO THE FOOD SAFETY MANAGEMENT SYSTEM OF RESTAURANT INDUSTRY ESTABLISHMENTS
Abstract
The necessity of transforming the traditional HACCP model in restaurant industry establishments under conditions of increasing production process dynamism, product range variability, and the significant influence of the human factor is substantiated. It is shown that the current practice of HACCP implementation, based on documenting compliance with critical limits and maintaining records, does not ensure quantitative assessment of the cumulative impact of short-term and recurring deviations in technological parameters, which limits the analytical sensitivity of the system and its preventive potential. The aim of the study is to develop methodological principles for integrating artificial intelligence tools and digital monitoring into the HACCP system through the transition from a binary control model to a graded risk assessment model. The methodological framework is based on HACCP principles, ISO 31000 risk-based management approaches, and the concept of risk-based thinking in food safety management systems. The concept of AI-HACCP is proposed as an adaptive food safety management model based on a multicontour digital architecture integrating production, material, sanitation, human factor, and regulatory domains. An integrated Digital Hazard Risk Index (DHRI) is developed to normalize, weight, and aggregate heterogeneous indicators into a unified scale, enabling real-time quantitative assessment of system performance and supporting evidence-based management. It is demonstrated that continuous digital monitoring and analytical data processing allow the identification of hidden trends and cumulative risks not captured by the traditional binary “compliance/non-compliance” logic. The integration of artificial intelligence enables anomaly detection, risk forecasting, and optimization of decisionmaking. The proposed approach supports the transition from reactive to preventive food safety management in restaurant industry establishments.
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