THE PERSONALIZATION-PRIVACY PARADOX IN AI-DRIVEN MARKETING: A CONCEPTUAL FRAMEWORK FOR ENGAGING GENERATION Z CONSUMERS

Introduction: As Artificial Intelligence (AI) reshapes personalized marketing,Generation Z (Gen Z) faces a "personalization-privacy paradox." While AI-drivenrecommendations offer high perceived relevance, they simultaneously triggerconcerns regarding data surveillance and algorithmic control. This study explores theinterplay between perceived value, trust, and privacy in the Gen Z cohort.• Methodology: The research employs a structured narrative review, synthesizinginterdisciplinary literature from marketing, consumer behavior, and informationsystems. Theoretical grounding is provided by the Technology Acceptance Model(TAM) and Privacy Calculus Theory to examine the dual nature of AI engagement.• Results: The study proposes an integrative conceptual model highlighting that GenZ's purchase intentions are driven by a trade-off between the utilitarian benefits ofpersonalization and the perceived risks of data intrusion. Trust acts as a criticalmediator that can mitigate privacy fears and enhance value perception.• Discussion: Inferences suggest that marketers must balance algorithmic efficiencywith ethical transparency. Implications for the Indian e-commerce sector emphasize"privacy-by-design" as a competitive advantage to foster long-term loyalty amongdigitally native consumers.