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1. Introduction
A McKinsey survey shows that marketing, especially service operations, has the most AI use cases (Chui et al., 2022). Consumers use and experience AI-enabled services in daily life, such as predictive text features on smartphones or chatbot interaction on websites. Consequently, consumer experience with AI is an emerging theme in service research (Silva et al., 2021). Puntoni et al. (2021) suggest that while using any AI-enabled offering, consumers may experience AI during four common service encounters: data collection of consumers by AI, classifying consumers and making recommendations, performing tasks for consumers, or communicating with consumers.
During these commonly occurring service encounters with AI-enabled offerings, consumers generally have a positive experience due to AI's intelligence and benefits (Huang and Rust, 2022) such as personalization or convenience (Ameen et al., 2021). However, consumers may also have negative experiences while receiving services from AI. For instance, while sharing personal information with AI (vs human beings), consumers feel exploited due to a fear that AI will share their information with other parties (Lefkeli et al., 2021). Negative consumer-AI experience affects marketers incorporating AI in their offerings for they may lose almost one-third of consumers after just a single negative AI experience (Press, 2023). In contrast, positive consumer-AI experiences can lead to considerable revenue gains and competitive advantage (Edelman and Abraham, 2022). Altogether, improving consumer-AI experiences is a challenge, yet it offers a significant opportunity to marketers.
To address this challenge, relatively limited research attention has been given to the consumer experience with AI (Ameen et al., 2021; Choi et al., 2021; Puntoni et al., 2021). Prior studies have shown how some factors improve consumer experience with AI-enabled services, such as – emotional support and warmth (Choi et al., 2021; Gelbrich et al., 2021), and customizability (Butt et al., 2021) while other factors deteriorate consumer-AI experiences, such as – AI failure (Srinivasan and Sarial-Abi, 2021), and reduced autonomy (Sajtos et al., 2020). As research on consumer-AI experiences evolves, the effect of several other factors requires further exploration (Silva et al., 2021).
Among factors that affect consumer-AI experiences, perceived AI credibility is an understudied area of research. In simple terms, perceived AI credibility refers to the extent...