Abstract
As artificially intelligent conversational agents (ICAs) become a popular customer service
solution for businesses, understanding the drivers of user acceptance of ICAs is critical to ensure
its successful implementation. To provide a comprehensive review of factors affecting
consumers’ adoption and use of ICAs, this study performs a systematic literature review of
extant empirical research on this topic. Based on a literature search performed in July 2019
followed by a snowballing approach, 18 relevant articles were analyzed. Factors found to
influence human-machine cognitive engagement were categorized into usage-related, agentrelated, user-related, attitude and evaluation, and other factors. This study proposed a collective
model of users’ acceptance and use of ICAs, whereby user acceptance is driven mainly by usage
benefits, which are influenced by agent and user characteristics. The study emphasizes the
proposed model’s context-dependency, as relevant factors depend on usage settings, and
provides several strategic business implications, including service design, personalization, and
customer relationship management.