Consumer Adoption of AI-Powered Chatbots: Developing a Customized Adoption Model

Abstract

Recent advancements in Artificial Intelligence have transformed the business landscape, with AI-powered chatbots playing a crucial role in enhancing customer service and automating tasks. As current literature seems to predominantly focus on the use of AI-powered chatbots in organizational contexts, this study aims to fill this gap by creating an understanding of the factors driving AI-powered chatbot adoption from a consumer perspective. To achieve this, we utilize the Theory of Planned Behavior (TPB), the Technology Adoption Model (TAM), the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Diffusion of Innovations (DOI), as traditional technology adoption models. Along with the constructs from these traditional models, we add the AI-specific antecedents: Anthropomorphism, Trust, Privacy Risk and Personalization, which were found through conducting a literature review of AI- and chatbot adoption. This integration allowed us to develop a customized adoption model that provides an understanding of chatbot adoption from a consumer perspective. The study collects data through a questionnaire-based survey (n=126). Through several multiple regression analyses, significant drivers across all the models are revealed. Subjective Norm and Behavioral Control (TPB), Usefulness (TAM), Habit (UTAUT2) and Trialability (DOI) were all found to have a significant positive effect on the Intention to Use AI-powered chatbots. The Customized Model, created through stepwise estimation, includes Usefulness (TAM), Trialability (DOI), Habit (UTAUT2), and Anthropomorphism (Model Extensions). These four factors collectively explain 46.6% of the variance in consumers' Intention to Use AI-powered chatbots. In terms of explaining the adoption of AI-powered chatbots, the Customized Model outperforms traditional models by explaining the most variance while utilizing the fewest variables. This enhanced fit may make it a more effective tool for understanding how consumers adopt AI-powered chatbot technology. The study contributes to businesses’ understanding of the constructs influencing chatbot adoption and implementing effective strategies to enhance customer experiences.