Published Paper Details:

The proliferation of artificial intelligence (AI) in retail has transformed customer interactions from transactional to highly personalized experiences. This study aims to investigate the direct and indirect effects of AI-powered personalization on consumer purchase intention within an omnichannel retail context. It specifically examines the mediating roles of perceived value and consumer trust. A structured questionnaire was developed and administered online to a sample of 327 Indian consumers who have experienced personalized recommendations on e-commerce platforms and in-store digital kiosks. Data analysis was conducted using SPSS for descriptive statistics and SmartPLS 4.0 for Structural Equation Modeling (SEM) to test the proposed hypotheses. The results indicate that AI-powered personalization has a significant positive direct effect on purchase intention. Furthermore, perceived value and trust were found to be significant partial mediators. Perceived value emerged as the stronger mediator, suggesting that consumers are primarily driven by the functional benefits of personalization. The study is limited by its cross-sectional design and geographic focus on urban Indian consumers. Future research could employ longitudinal designs and explore cultural differences. The findings offer practical implications for retailers to invest in AI systems that enhance perceived value (e.g., through relevant product discovery) while being transparent to build trust. This research contributes to the literature by integrating Technology Acceptance Model (TAM) and Stimulus-Organism-Response (S-O-R) framework to provide a holistic model that explains how personalization influences purchase decisions through key psychological mechanisms (perceived value and trust) in an omnichannel setting.