The advancement of Artificial Intelligence (AI) has significantly transformed the e-commerce landscape by enabling businesses to enhance operations, personalize customer experiences, and improve decision-making. Despite AI’s widespread adoption in online retailing, theoretical and empirical research assessing its impact on e-commerce performance remains limited. This study addresses this gap by leveraging the DeLone and McLean Information Systems (IS) Success Model as a conceptual framework to evaluate AI-driven e-commerce systems. By extending traditional IS success metrics, this research integrates AI-specific measures across system quality, information quality, and service quality. Using a structured dataset from Digital Commerce 360, complemented by web-scraped AI adoption data and user satisfaction scores from Trustpilot, this study applies Structural Equation Modeling (SEM) to analyze AI’s influence on platform use, user satisfaction, and net benefits. The findings provide a validated framework for measuring AI effectiveness in online retail, while offering insights for industry practitioners.