Building Digital Bonds: The Impact of AI-Driven Personalization on Customer Experience and AI Relationship Quality

This study aims to examine the impact of AI-driven personalization on AI-enabled customer experience and perceived AI relationship quality. It further investigates the mediating roles of trust in AI and perceived personal relevance, as well as the moderating effects of privacy concern and technology readiness within an integrated conceptual framework. A quantitative, cross-sectional research design was employed. Data were collected from 330 users who had prior experience with at least one of three specified AI-enabled digital platform categories: e-commerce recommendation platforms (e.g., online retail sites), streaming services (e.g., video or music platforms), and fintech applications (e.g., digital banking or payment apps). Respondents were screened using platform-specific filter questions to reduce heterogeneity. The proposed model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS. Reliability, validity, mediation, and moderation effects were evaluated using bootstrapping techniques. To address potential common method bias arising from single-source self-reported data, Harman's Single-Factor test was conducted. The test confirmed that no single factor accounted for the majority of variance, suggesting that CMB does not critically threaten the validity of the findings.