<![CDATA[This paper offers a PRISMA-guided systematic literature review to examine how Artificial Intelligence (AI) is applied in e-commerce. The focus is on identifying key factors that influence customer purchasing decisions in AI-driven online transactions. It examines Information Systems (IS) theories relevant to the integration of AI and e-commerce, offering insights into frameworks used to analyze the relationship between AI and consumer behavior. Additionally, the paper identifies gaps in current research and provides recommendations for future studies, particularly in areas requiring further exploration to understand the evolving impact of AI on e-commerce. Through a review of existing literature, the study identifies critical factors such as perceived enjoyment, perceived usefulness, perceived ease of use, interactivity, consumer engagement, AI technology, and information quality, which significantly affect consumer purchase intentions. This review finds that Stimulus-Organism-Response (SOR) and Technology Acceptance Model (TAM) are the most commonly adopted theories, while Media Richness Theory is used less frequently. The findings provide a robust foundation for future research, enabling the formulation of empirically testable hypotheses. Furthermore, this study offers a more integrated perspective by organizing identified constructs into a multi-dimensional framework and suggests directions for future empirical research, such as developing research models and validating them through survey-based approaches and Structural Equation Modeling (SEM-PLS), as well as qualitative methods. The study aims to offer insights to AI developers and e-commerce practitioners, helping them enhance AI-powered systems to better meet consumer needs and expectations, ultimately improving customer satisfaction and increasing purchase rates.]]>
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