Factors Driving Individuals’ Usage Intention of Artificial Intelligence (AI) Assistants in E-commerce: Perspectives of Users and Non-Users

Abstract

The ongoing revolution of e-commerce has brought about significant transformations in the global retail landscape, redefining how consumers interact with online platforms. In response to this transformative trend, businesses increasingly adopt and integrate artificial intelligence (AI) technologies, particularly AI assistants. AI assistants have gained significant traction to enhance customer engagement, improve personalised experience, and streamline various aspects of the e-commerce process. Companies across diverse industries and geographical regions have recognised the potential of AI assistants in fostering more profound connections with customers, providing real-time support, and bolstering sales through intelligent recommendations. Consequently, investment in AI research and development has surged, leading to remarkable advancements in AI assistants’ features and functionalities. Despite the growing interest of the scientific community and business stakeholders in the topic, scholarly research on the factors influencing e-commerce consumers’ attitudes and intentions toward using AI assistants is still limited and provides contradictory evidence regarding some factors. Moreover, no comparative studies in the e-commerce context empirically investigated the attitudes of non-users and users toward AI assistant use. Also, several consumers' demographics have been excluded from prior research, with no previous empirical research on AI assistant use across different cultural backgrounds. For these reasons, the study aimed to comprehend the factors influencing consumers' behavioural intention to utilise AI assistants and to recognise the significant user differences based on multiple perspectives. This study employed a unique research model based on the technology acceptance model. It extended it with external factors of AI assistants’ capabilities that still need to be tested together in AI assistant adoption for e-commerce consumers. This research conducted a mixed-method approach. In the first phase (Phase A), a quantitative method was employed to investigate the relationships between the constructs in the study model, and the Partial Least Square Structural Equation Modelling (PLS-SEM) and several statistical techniques were adopted. Furthermore, to account for cross-cultural differences and identify potential variations in usage intentions towards using AI assistants between Eastern and Western cultures, a multi-group analysis (MGA) was conducted. In the second phase (Phase B), a qualitative approach was conducted by applying machine learning and natural language processing techniques to analyse reviews of the Louis Vuitton brand's e-commerce applications. The objective of this stage was to obtain supporting evidence for the results of the VI first study and to gain deeper insights into consumer attitudes and experiences. Subsequently, the results were integrated to provide multiple insights to answer the research questions and strengthen the findings. This study has confirmed some previous studies' results and provided new findings. The attitude factor was the significant predictor of the intention to use AI assistants in non-users and users, with a direct and positive effect. Perceived usefulness was found to be the statistically significant predictor of attitudes in both non-users and users of AI assistants. The additions to the original TAM model, specifically incorporating interactive communication and personalisation, were statistically significant predictors of the attitudes of non-users and users to use AI assistants with positive effects. In contrast, perceived ease of use was a nonsignificant predictor of the non-users’ attitudes and positively impacted the users’ attitudes towards using AI assistants. Furthermore, no significant differences existed in the relationships among the primary factors influencing the intention to utilise AI assistants in e-commerce when comparing Western and Eastern cultural groups. This study contributes to both theory and practice by extending the TAM model with two external factors enabling the assessment of the factors affecting the intention to use AI assistants from consumer, social, and marketing perspectives and providing new empirical data on this topic in technology adoption studies. The study also enables further research on this topic and comparing study results, thus improving understanding of the phenomenon. It also provides various e-commerce practitioners with valuable information and recommendations regarding AI assistant use, enabling them to make better decisions in developing and implementing AI assistant technologies.