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EMAC 2023 Annual

User Trust in AI Chatbot: A Review and Research Agenda

Published: May 24, 2023


AHMED GEEBREN, Northumbria University


The purpose of this paper is to review the existing AI chatbot literature to identify the key antecedents and consequences of user engagement with AI chatbots. This review enabled the researcher to identify and categorise factors affecting user trust in AI chatbot into three groups: (a) humanoid factors; (b) service quality factors; and (c) content factors. In addition, the consequences of user trust in AI chatbots were classified into two groups: (a) brand effects and (b) AI chatbot effects. This paper sheds light on the influences of a set of key factors on shaping the mediating role of trust in AI chatbots in consumer behaviour toward businesses and AI chatbots.