Introduction. In the article, the authors systematize relevant scientific research in the field of omnichannel trade. The analysis shows that in modern conditions of high competition, in order to remain on the same level as marketplaces in terms of attractiveness, retail stores must change their trade policy and meet customer expectations as much as possible. Theoretical analysis. An analytical review of current publications allows the authors to identify key areas of scientific research and promising areas for their further development. The authors consider trading organizations’ business models transformation, new key metrics formation for evaluating the trading business’ effectiveness, methods for integrating online and offline channels, optimization of methods for delivering goods at various stages of the logistics cycle, and inventory management methods. Empirical analysis. To create an omnichannel retail information system, the key step is the decomposition of the system into separate classes. The domain model is represented by a visual representation of class data or objects expressed in terms corresponding to a specific field of knowledge. Using artificial intelligence technologies, the authors have developed a model of a trading system’s digital transformation for omnichannel trading, providing personalization and improvement of customer experience. Results. In the practical part, the information system was designed for the “Department Store of the Future”. A class diagram developed using generative artificial intelligence is presented. It visualizes the architecture of a single omnichannel platform, within which all sales channels are combined and synchronized. In the future, the developed class diagram can serve as the basis for creating a single platform that provides a seamless customer experience in an omnichannel system.