Examining the impact of anthropomorphism and AI-chatbots service quality on online customer flow experience – exploring the moderating role of telepresence

Purpose Artificial intelligence (AI)-enabled chatbots are considered one of the most intelligent applications with a high degree of anthropomorphism as they can make interactions and conversations with customers more human-like. Therefore, this study aims to discover how AI applications with high anthropomorphism shape different aspects of the online customer experience and reactions, such as emotional brand attachment and brand loyalty. Design/methodology/approach This study adopted the flow experience model as a theoretical base. The current study model was also extended by considering AI service agents service quality (AISAQUAL). A quantitative approach was adopted to validate the current research model and test the main hypotheses. Therefore, an online survey questionnaire was conducted with 500 customers with experience using AI-enabled chatbots in Jordan. Findings Statistical results supported a strong significant impact of AISAQUAL and anthropomorphism on online customer flow experience, which in turn significantly predicted both emotional brand attachment and brand loyalty. Research limitations/implications This conceptual model considers two main factors – AISAQUAL and anthropomorphism – as key drivers of online customer flow experience. In this regard, considering the R 2 value of 60% recorded in the online flow experience with AI-enabled chatbots, other factors may contribute to influencing customers’ online experience with AI-enabled chatbots. Some of the most important factors to be considered by future studies include emotional intelligence capabilities (Urbani et al. , 2024), cultural differences (Shams et al. , 2024), perceived credibility (Shin, 2022) and reciprocity (Adam and Benlian, 2023). Practical implications This study provides valuable guidelines for service providers, practitioners and designers. These guidelines can help build more successful AI-enabled chatbots that enhance customer interactions and create more attractive and unique user experiences. Originality/value The comprehensive model proposed offers a holistic understanding of how different psychological, personal and environmental factors contribute to the overall customer experience. From a methodological perspective, this study successfully used statistically and empirically validated metrics to measure the proposed model, particularly in the context of the Middle East (Jordan). Future studies can apply these robustly validated metrics to evaluate the effectiveness of anthropomorphic AI interactions in similar contexts. This study provides valuable guidelines for service providers, practitioners and designers. These guidelines can help build more successful AI-enabled chatbots that enhance customer interactions and create more attractive and unique user experiences.