The article explores innovative technologies based on artificial intelligence that enable processing large volumes of data in the operations of restaurant enterprises.A review of scientific works on the topic of the article is conducted.The relevance and necessity of using artificial intelligence for restaurant enterprises in the modern world are described.The opinion is substantiated that the implementation of innovative digital technologies in restaurant businesses will enable them to achieve the necessary level of competitiveness and economic efficiency.Successful directions of practical application of Big Data technologies in the operations of hospitality enterprises are discussed.The most popular techniques and methodologies for processing big data are presented.The article highlights the role of artificial intelligence (AI) in revolutionizing the restaurant business through the analysis of large volumes of data.The essay examines in detail how AI helps to optimize inventory management, increase the effectiveness of marketing campaigns, and improve customer service.Special attention is paid to innovative technologies, such as machine learning and natural language processing, which allow restaurants to analyze consumer behavior more deeply and optimize work processes.The essay also reveals the potential challenges of integrating AI into traditional restaurant management practices and offers suggestions for possible solutions.The article focuses on the analysis of the impact of artificial intelligence (AI) and big data analysis technologies on the restaurant business.The article reveals how AI helps businesses collect, process and analyze large volumes of information, resulting in increased management efficiency, optimization of work processes and improved customer service.The article examines practical examples of the application of AI for demand forecasting, service personalization and customer service automation, and also highlights the potential challenges and ethical aspects of using AI in the restaurant industry.
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Volodymyr Silchenko (2024) studied this question.
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