The advent of artificial intelligence-driven chatbots has brought about a paradigm shift in online shopping. This study employs Structural Equation Modeling (SEM) to comprehensively investigate the transformative potential of AI chatbots in e-commerce. We delve into three critical dimensions: user satisfaction, choice dynamics, and web insights, with SEM serving as a robust analytical framework to understand the complex interplay of variables. Our findings reveal intricate relationships between AI chatbot interactions and user satisfaction, shedding light on the factors that significantly impact users' overall contentment. Moreover, we explore how AI chatbots influence the decision-making processes of online shoppers, uncovering the nuances of choice dynamics in the digital retail landscape. Furthermore, SEM allows us to extract valuable web insights from the data generated by chatbot interactions, offering actionable information for businesses to optimize their online shopping platforms. By integrating SEM analysis into our research, this study provides a holistic understanding of how AI chatbots are reshaping online shopping, offering insights that can guide businesses in enhancing customer experiences and driving success in the digital marketplace.