Understanding Consumer Acceptance of Artificial Intelligence in E-Commerce: The Role of Trust, Perceived Value, and User Experience

Abstract

Artificial Intelligence (AI) has significantly revolutionized how consumers find, assess and acquire products, when it comes to online retail.When it comes to online retail, the widespread adoption of Artificial Intelligence (AI) has transformed the way consumers discover, assess and purchase products. AI has seamlessly integrated into the digital shopping experience, from chatbots that facilitate customer interactions to recommendation systems that tailor product suggestions to individual preferences.AI tools have become crucial to the digital shopping experience, ranging from conversational bots to customer interaction, personalized recommendations to dynamic pricing models, and augmented reality try-on features. However, the adoption rate for AI-powered e-commerce capabilities among consumers is not uniform, with a myriad of cognitive, affective, and experiential elements influencing their receptivity. The purpose of this study is to examine the factors affecting the acceptance of AI in e-commerce and focus specifically on the influence of trust, perceived value, and user experience on behavioral intention. Based on an integrated model incorporating the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and trust-based consumer behavior theory, a structured survey was given to 300 online shoppers from various demographic groups. The data were analyzed by descriptive statistics, correlation analysis and multiple regression modelling. The results reveal that the perceived trust has the greatest positive effect on AI acceptance, followed by perceived value and user experience, and perceived risk has a significant negative effect. The findings also show that younger consumers and frequent online shoppers have more positive attitudes about the adoption of AI shopping assistants, and that trust concerns over data privacy and algorithmic transparency are the biggest challenges to wider uptake. The study adds to existing literature on the interaction between AI and consumers by providing a conceptual framework that integrates the key concepts, as well as managerial implications that can guide e-commerce practitioners in creating more trustworthy, value-providing, and user-centred AI systems. Restrictions and guidelines for further research are also addressed.