In the rise and proliferation of artificial intelligence (AI), more so applied in the context of online retail, it has changed the way businesses interact with consumers by offering personalized marketing strategies that spur impulsive buying. The AI personalization systems, such as predictive recommendation tools, chatbot assistants, and other forms of customized placements, increasingly intervene in consumer decision-making processes as in real time. The study seeks to understand how AI-driven personalization affects impulse buying with an emphasis on predictive algorithms in e-commerce settings. Through the combination of disparate literature, the study investigated different dimensions of AI applications and their interpretations from enhancement of user engagement, eliciting affect, and speeding-up decision-making, with a goal of increasing purchase intention and satisfaction. While finding that AI-based personalization greatly enhances consumers' purchase intention and satisfaction level, the study also raises concerns about the ethical issues of data privacy and behavior manipulation. With a critical synthesis of recent studies, a conceptual model that illustrates the ways AI induces impulsive behavior has been developed. Finally, implications for online retailers, marketers, and policymakers are also discussed to provide insight into the delineation of strategies that address the further development of personalization, while protecting consumer well-being.