This study aims to investigate the impact of AI-based personalized recommendation systems (AIPRS) on e-commerce buying intentions, driven by both rational and irrational motives. While these systems are known to enhance sales, their negative effects on user empowerment have been less explored. Employing a 3x3 experimental design, three levels of information load (low, medium, high) and three types of explainable AI (XAI) presentation (text-only, text-driven, visual-driven), we will examine how and why XAI can intervene in AI-induced user behaviors, especially in a way to reduce the negative impacts of AIPRS on users’ rational buying behavior. Our objective is to elucidate the complex interplay between AIPRS and various depths and types of XAI explanations, exploring their effects on user empowerment and decision-making. This research will enhance understanding of the roles of AIPRS and XAI in e-commerce, offering insights that can improve user experiences and guide ethical practices in digital marketplace design.