Artificial Intelligence in Frontline Service Encounters: A Systematic Review and Research Agenda

ABSTRACT Over recent years, the proliferation of artificial intelligence (AI) has enabled businesses worldwide to employ AI‐driven service agents to deliver frontline services to their customers. This paradigm shift has also increased scholarly attention to consumer behavior research in AI‐driven frontline service encounters. Nevertheless, the existing body of knowledge in this domain lacks coherence and consistency, with disparate findings scattered across numerous disciplines. In this context, a critical and comprehensive overview of the existing literature in this domain is essential. Therefore, to provide an updated and comprehensive understanding of consumer research in this fast‐growing domain, we systematically analyzed 157 articles. Using the popular TCCM framework, we offer a detailed overview of the theories, contexts, characteristics, and methodologies used in the prior studies in this domain. The research also presents an integrated framework considering the independent variables, mediators, and moderators influencing customer outcomes. This analysis identifies several research gaps and suggests potential opportunities for further investigation that pertain to major emerging topics and overlooked areas. This review enhances the understanding of consumer reactions to AI‐driven frontline service encounters and offers novel insights for both the literature and managerial practice regarding the implementation of AI in frontline services.