THE IMPACT OF ARTIFICIAL INTELLIGENCE ON GENERATION Z’S ONLINE FASHION PURCHASE INTENTIONS

Abstract

This study examines how Artificial Intelligence affects consumer buying intentions in the online fashion industry. The main objective of this study is to understand how AI-related factors impact attitudes toward using AI and decisions when buying fashion products online. The study expanded the Technology Acceptance Model (TAM) by adding two key elements: AI-driven Personalization and Trust in AI. This additional focus helps investigate the buying intentions of Gen Z in relation to online fashion. A quantitative approach was taken, using a cross-sectional research design. Data collected from consumers who had recently purchased fashion products through online. The analysis employed Partial Least Squares Structural Equation Modelling (PLS-SEM) using Smart PLS 4 software. The results indicate that AI-driven personalization, perceived ease of use, perceived usefulness, and trust in AI all significantly affected consumers’ attitudes toward AI and influenced their buying intentions. Among these variables, Trust in AI had the strongest direct and indirect effect on buying intentions. The study also showed that attitude plays a partial mediating role between AI factors and purchase decisions. The findings suggest that AI technologies should be personalized, easy to use, beneficial, and trustworthy to positively influence online shopping behaviour. This research is important for online fashion retailers as it offers practical advice to improve AI systems for better consumer engagement and greater purchasing intentions. Overall, the study provides valuable insights by expanding the TAM model and demonstrating how AI can shape modern consumer behaviour in digital retail environments.