Subject urgency. In modern conditions of globalization and digital transformation, the food industry is at a stage of fundamental paradigm shift. The rapid development of artificial intelligence (AI) technologies is becoming a determining factor in ensuring the competitiveness of enterprises, which leads to an urgent need for scientific understanding of the processes of intellectualization of production. Problem statement. Despite significant interest in digitalization, the mechanisms of AI’s influence on specific industrial processes of the food industry, such as quality management, consumer demand forecasting, and ensuring preventive economic security, remain insufficiently systematized and require complex analysis. The objective of the study. The purpose of the article is a comprehensive study of the impact of AI on the development of the food industry, identifying strategic advantages from its implementation, and analyzing the technological aspects of the industry’s transformation. To achieve the goal, the task of identifying key vectors of AI influence and evaluating the effectiveness of its application on the example of global market leaders was solved. Methodology. The paper uses a set of scientific cognitive methods: systematic analysis – to study the structure of economic security; the method of theoretical generalization – for the definition of the concept of AI; statistical and predictive methods – for analyzing the robotics market; case–study method – for studying the practical experience of Nestlé Corporation. Research results. It has been established that the key vectors of AI influence are the optimization of production efficiency, automation of quality control through computer vision, predictive logistics, and hyper–personalization of nutrition. The role of AI in the formation of a preventive model of economic security of an enterprise, which allows minimizing internal fraud and optimizing energy consumption, is substantiated. The dynamics of implementation of robotics and «digital twin» technologies, which ensure faster time–to–market for new products, are analyzed. Scope of results. The results of the study can be used by top management of food industry enterprises to develop digital development strategies, as well as by scientists researching issues of innovation management and economic security. Conclusions. The implementation of AI ensures a transition to the «smart manufacturing» model, which maximizes the resource efficiency and strategic stability of the enterprise. Further research should focus on the ethical aspects of data processing and cybersecurity of intelligent systems.