
This article investigates the development of e-commerce in Uzbekistan through the lens of artificial intelligence (AI) technologies. The study analyzes the scientific foundations and the growing importance of AI in online trade, focusing on its application in data processing, consumer behavior analysis, sales process optimization, and personalized marketing strategies. Using empirical data from Uzbek e-commerce platforms, the research examines AI-driven demand forecasting, dynamic pricing policies, automation, and customer service enhancement. The results show that the implementation of AI technologies significantly improves sales efficiency, customer satisfaction, and decision-making accuracy. The article also identifies key challenges such as data quality issues, shortage of qualified personnel, high implementation costs, and insufficient legal and ethical regulations. Based on these findings, the study outlines the stages, problems, and prospects of AI integration in Uzbekistan’s e-commerce system.
digital technologies, Artificial intelligence, online trading platforms, demand forecast, personalized marketing, data analysis, e-commerce, the economy of Uzbekistan, digital economy
digital technologies, Artificial intelligence, online trading platforms, demand forecast, personalized marketing, data analysis, e-commerce, the economy of Uzbekistan, digital economy
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
