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Conversational Artificial Intelligence (CAI) has become a pivotal tool for businesses to reshape customer service, offering personalized and scalable solutions. This study adopted a bibliometric analysis of 191 scholarly articles and a content analysis under a systematic literature review employing the TCCM framework for 45 articles. The findings from the bibliometric analyses categorize CAI research into three phases of thematic evolution: emergence (2018–2020), development (2021–2022), and maturity (2023–2024). Further, from the systematic review, a comprehensive content analysis of articles reveals that, the most prominent theories and models in the phenomenon, research contexts in terms of countries, industries, various CAI technologies, and characteristics of conceptual models in order to understand different outcomes, antecedents, and mediators/moderators. This study also observed three critical dimensions of CAI research that are adoption, implementation, and monitoring with relevance to organization and consumer. This paper argues that despite considerable evidence from the literature in CAI in recent years, there is a large scope for research to address successful factors to adopt CAI from the perspectives of organizations as well as consumers. It emphasizes the need for researchers to investigate the interaction and engagement between CAI and consumers, as well as the challenges that arise during implementation and the ways in which they can be mitigated in business firms. In the CAI monitoring, issues related to the security and privacy dimensions of CAI technology, aimed at benefiting customers and users, are emphasized.
Pradhan et al. (Fri,) studied this question.