5. Customer Acceptance of AI in Service Encounters: Understanding Antecedents and Consequences

In this chapter, we take a customer-centric view of narrow artificial intelligence (AI), or task-specific AI applications. Because of the breadth and extent of AI applications, we limit our focus to service encounters—which are times when customers interact directly on the frontline with a service company or organization. The purpose is to illuminate the roles of AI in the context of frontline service encounters and to identify the potential benefits and negative consequences for customers of AI-supported, AI-augmented, and AI-performed services. We develop a conceptual framework of the antecedents and consequences of AI acceptance by customers grounded in previous research, theory, and practice. Previous research has examined the adoption of self-service technologies (SSTs) and established that innovation characteristics and individual differences predict role clarity, motivation and ability (RMA), which in turn predict adoption of SSTs (see Meuter et al. 2005; Blut et al. 2016). However, we believe that additional antecedents will come into play in predicting the acceptance of service encounter technologies tied to AI. Therefore, we expand the relevant set of antecedents beyond the established constructs and theories to include variables that are particularly relevant for AI applications such as privacy concerns, trust, and perceptions of “creepiness.” We also examine a broader set of potential consequences of customer acceptance of AI including what customers may experience (e.g., more personalized service encounters) and how AI may affect customers (e.g., lead to increased well-being due to more access to services). The chapter concludes with research questions and directions for the future tied directly to the conceptual framework.