ABSTRACT The integration of Generative Artificial Intelligence (AI) into digital marketing ecosystems has redefined content creation, personalization mechanisms, and customer engagement strategies. While AI-driven systems enhance operational efficiency and predictive targeting, their psychological and behavioral implications on consumers remain underexplored. This study investigates the impact of generative AI on consumer trust, perceived personalization, and purchase intention through an in-depth thematic analysis of contemporary academic literature and industry discourse (2020–2025). Drawing upon the Stimulus–Organism–Response (S-O-R) framework and Technology Acceptance Model (TAM), the study identifies five higher-order themes: (1) algorithmic hyper-personalization, (2) trust formation and explainability, (3) the personalization–privacy paradox, (4) automation versus authenticity tension, and (5) behavioral outcomes and purchase intention dynamics. Findings indicate that while AI significantly enhances perceived usefulness and engagement, trust operates as a critical mediating construct shaping purchase decisions. Ethical transparency and responsible data governance emerge as essential moderators. The study advances theoretical understanding of AI-mediated consumer behavior and proposes a conceptual framework integrating personalization, trust, privacy, and behavioral intention in digital marketing contexts. Managerial implications and future research directions are discussed. Keywords: Generative AI, Consumer Trust, Hyper-Personalization, Purchase Intention, Digital Marketing, S-O-R Framework, Technology Acceptance Model, Thematic Analysis.