Online fashion business is flourishing and the use of various cutting-edge technologies is impacting consumer purchase behavior. Impulse buying as we know involves spontaneous and unplanned purchases which is a common phenomenon across online shopping platforms. Most of the times, it is a result of a complicated mix of several factors. In the context of online fashion retail, our research aims to explore the factors that are driven by Artificial Intelligence (AI), and affects the impulsive buying habits of customers. The current study uses a quantitative method and a structured questionnaire to gather data from a group of different online fashion buyers. A regression analysis is performed to capture the impact of various factors such as personalized recommendations, virtual try-ons, advertising strategies, chatbots, and navigation ease in determining the impulse buying behavior of online fashion shoppers. The study explores the mental processes behind impulsive decisions by analyzing the interaction between consumer purchase decisions and different AI-driven stimuli. Various retail organizations can use the potential of AI technologies to make better marketing strategies and boost sales, while consumers become increasingly aware about how AI-related technologies may affect their options for purchase.