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Based on service quality theory, this study constructs an AI-enabled cross-channel service quality analysis framework, systematically examining the differentiated roles of reliability, responsiveness, assurance, empathy, and tangibility in different retail contexts, and introducing generational groups as key moderating variables. Empirical results based on questionnaire data and structural equation modeling show that AI reshapes the action path of the SERVQUAL dimension, and the conversion mechanism of satisfaction to shopping preference differs significantly among different generational groups.