<![CDATA[The growing use of generative artificial intelligence in marketing has transformed how content is produced and evaluated, raising critical concerns regarding how consumers perceive authenticity when authorship extends beyond human creators. While prior research has largely focused on technological adoption and trust, limited attention has been given to how consumers construct meaning and evaluate authenticity in AI-mediated environments. This study addresses this gap by developing a conceptual framework that positions perceived authenticity as a central mechanism linking AI involvement in content creation to consumer psychological and behavioral responses. Drawing on authenticity theory, consumer behavior, and artificial intelligence literature, the study adopts a theory integration approach to synthesize fragmented insights into a unified model. The proposed framework reconceptualizes authenticity as a hybrid construct emerging from the perceived interaction between human intention and algorithmic generation, and explains how this perception shapes trust, emotional engagement, and behavioral outcomes. By offering a multi-level and process-oriented perspective, the study contributes to extending authenticity theory and advancing AI marketing research toward meaning-based evaluation, while providing a foundation for future empirical investigation in human–AI collaborative contexts.]]>
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