India’s e-commerce growth has changed the buying habits of women for ready-to-wear clothes. Online fashion platforms provide ease, a wide range of products, competitive pricing and are becoming more and more personalised. When buying clothes without checking them out, though, there is uncertainty about the size, fit, fabric quality, colour and authenticity of the product. Meanwhile, artificial intelligence (AI) is proving to be a valuable piece of technology in the fashion retail landscape, enabling customisation, automating product discovery, virtual try-on, and intelligent sizing assistance. More than just recommending related products, such technologies are effective if consumers trust digital platforms and feel that there is no risk of the garment being a misfit. The paper formulates a conceptual model of women’s online shopping behaviour for ready-made garments based on the technology acceptance theory, online consumer trust theory, perceived risk theory, and AI research theory in the field of retail. The analysis indicates that AI personalisation can improve purchase decisions in the following ways: by providing relevant recommendations, by reducing the time spent searching, and by helping to evaluate the product. Whether consumers trust the recommendations, and even if they can purchase a convenient digital service, digital trust will affect their willingness to do so, as will perceived fit risk. The discussion also explores the dilemma of customisation versus privacy and the importance of a range of product images, precise size information, and return policies. This paper aims to provide a comprehensive understanding of how technology, psychology, and product factors influence women’s online shopping habits and how these insights can be applied to Indian fashion retailers