From familiarity to acceptance: The impact of Generative Artificial Intelligence on consumer adoption of retail chatbots

Abstract

This study investigates the influence of Generative Artificial Intelligence (GenAI) on consumer adoption of retail chatbots, focusing on how GenAI impacts key adoption determinants, the role of familiarity and assessing its effects across different stages of the customer journey. We conducted two waves of surveys, one pre- and one post-GenAI integration, to compare consumer perceptions across three customer service tasks. Using the Service Robot Acceptance Model (SRAM) as a framework, we found that GenAI enhances consumer perceptions of chatbot usefulness, human-likeness, and familiarity, thereby increasing adoption intentions. However, trust remains largely unchanged, and privacy concerns have risen post-GenAI. Additionally, the relationships remain stable across customer journey stages, with familiarity playing a key role. Our findings extend SRAM to the retail context with GenAI, offering new insights into the temporal stability of chatbot adoption factors. It underscores familiarity's dual role (direct and indirect) in fostering adoption, while highlighting that GenAI impacts specific aspects of consumer interaction. These findings provide insights for retailers to leverage GenAI-powered chatbots to enhance customer engagement and satisfaction.