Examining the Role of Artificial Intelligence in Influencing Consumer Preferences and Purchase Intentions toward Green Fashion

The study investigates pivotal function of artificial intelligence (AI) in promoting sustainable fashion practices and influencing customer behavior. The garment business contributes 10% of global carbon emissions and produces substantial textile waste; thus, AI is a vital answer for mitigating environmental impact while preserving profitability. The study examines AI applications in industry (predictive analytics diminishing overproduction by 20-30%), design (virtual sampling minimizing material waste by 80%), and retail (AI-driven recommendations enhancing sustainable purchasing by 35%). The study uses Structural Equation Modeling (PLS-SEM) with information from 212 fashion customers to test a framework based on the Theory of Planned Behavior and the Stimulus-Organism-Response model. The important results show that what consumers know (β=0.482, p=0.045) and their trust (β=0.536, p=0.013) are key factors in their sustainable preferences, along with a very strong link between preference and intention (β=20.139, p<0.001). The measuring model has robust reliability (Cronbach's α > 0.88) and validity (AVE > 0.74); however, motivation displays minimal direct impact (β = 0.031, p = 0.735). The practical consequences underscore the necessity for honest AI communication, tailored sustainability suggestions, and investment in circular design tools. The limitations encompass the cross-sectional methodology and possible cultural disparities in AI adoption. Future studies should investigate longitudinal behavioural effects and do net sustainability evaluations of AI installations.