The Dark Side of AI-Driven Hyper-Personalization: Customer Irritation, Affective Accumulation, and Value Co-Destruction
DOI:
https://doi.org/10.47065/imj.v6i2.541Keywords:
Customer Irritation, Artificial Intelligence, Hyper-Personalization, Affective Customer Experience, Value Co-DestructionAbstract
Firms increasingly invest in AI-driven hyper-personalization to enhance customer experience (CX), yet emerging evidence indicates that these technologies may also generate unintended negative emotional outcomes. This study aims to develop a conceptual framework explaining how failures in AI-driven hyper-personalization lead to customer irritation and subsequent value co-destruction in AI-mediated service interactions. Using a conceptual research approach based on an integrative review and synthesis of recent literature, the study draws upon Expectation–Disconfirmation Theory, Psychological Reactance Theory, and Affective Events Theory to construct a theoretically grounded framework. The proposed framework identifies AI response irrelevance and perceived intrusiveness as key antecedents of customer irritation, which subsequently mediates the effects of hyper-personalization failure on diminished trust, switching intention, and customer disengagement. The framework further advances five research propositions, identifies six boundary-condition moderators, and explains three structural paradoxes that clarify how hyper-personalization may systematically generate negative customer experiences despite its intended benefits. These findings extend value co-destruction theory by positioning customer irritation as a distinct cumulative affective mechanism underlying CX degradation and provide a stronger theoretical foundation for future empirical research on AI-mediated services. Future studies are recommended to empirically validate the proposed framework using longitudinal, experimental, or cross-cultural research designs across diverse AI-enabled service contexts.
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