Authors: Assistant Professor Ms. Remeeja Behum J, Ms P Dhanalakshimi, Karthick Ganesh S
Abstract: Artificial intelligence is increasingly embedded in online retail through recommendation engines, conversational assistants, visual search, automated customer support and personalized product displays. These tools may improve consumer experience, but the effects depend on how shoppers engage with the platform, evaluate the value of AI-enabled services and assess the trustworthiness of automated interactions. This paper proposes an India-focused model to examine the relationship between AI-enabled online retail and consumer experience. Customer engagement and perceived value are specified as parallel mediators, while consumer trust is modelled as a moderator of the AI–experience relationship. The framework combines the Stimulus–Organism–Response perspective with technology acceptance and value-based adoption reasoning. A quantitative cross-sectional survey of Indian online shoppers is proposed, with PLS-SEM used to evaluate measurement quality, direct paths, indirect effects and moderation. The paper specifies hypotheses, construct definitions, questionnaire items and a reporting framework for demographic, measurement and structural-model results. Since primary data have not been supplied, no statistical findings are invented. The framework offers a reproducible basis for testing how AI-enabled retail features can be designed to deliver useful, engaging and trustworthy consumer experiences.
