Application of artificial intelligence in forecasting consumer behavior and trends in E-commerce

This study explores the application of artificial intelligence (AI) and predictive analytics in e-commerce, focusing on forecasting consumer behavior and market trends. The research was conducted through a systematic literature review in recognized scientific databases such as Google Scholar, Scopus, and IEEE Xplore. The main objective was to identify the most recent approaches for using AI techniques, such as machine learning, natural language processing, and deep learning, in e-commerce. The analysis of articles, books, and academic materials allowed for the examination of the impact of AI in areas such as recommendation personalization, inventory optimization, and customer experience management. The findings indicate that the implementation of these technologies significantly improves the accuracy of consumer behavior predictions and contributes to more efficient inventory and marketing campaign management. Additionally, the studies reviewed highlight challenges such as data quality, privacy concerns, and the need for specialized skills. This work provides an in-depth view of the theoretical and practical contributions of AI in trend forecasting in e-commerce and suggests directions for future research in this field.