This study delves into the consumer adoption of AI within the realm of online apparel retail purchases, with a specific focus on the UTAUT2 model. The research explores the evolving landscape of e-commerce and Artificial Intelligence (AI)-driven personalization in the fashion industry. By employing the UTAUT2 model, the study examines how consumers interact with AI-driven features, such as product recommendations, virtual try-ons, and personalized styling advice, and the subsequent influence on their purchasing decisions. This study investigates customers’ adoption of AI-based online apparel websites by analysing 151 customer responses using Partial Least Square Structural equation model version 4. The results reveal that facilitating conditions, habit and hedonic motivation are positively associated with behavioural intention of AI-enabled websites for online apparel purchases, whereas the performance expectancy, social influence, effort expectancy doesn’t have impact on behavioural intention. Through quantitative analysis, the research offers insights into the factors that encourage or hinder AI adoption among online apparel shoppers. The results from this study provide valuable information for online apparel retailers and AI developers seeking to enhance consumer experience and boost sales through AI-driven solutions. Understanding the dynamics of consumer adoption of AI within online apparel retail is crucial in shaping the future of fashion e-commerce.