Artificial Intelligence (AI) has fundamentally transformed marketing by enabling highly personalized customer experiences and enhancing organizational capabilities in data-driven decision-making. Personalized marketing leverages AI technologies such as machine learning, predictive analytics, and natural language processing to understand consumer preferences, predict behavior, and deliver tailored content, products, and services. While AI-driven personalization improves customer satisfaction, engagement, and loyalty, it also raises concerns about privacy, transparency, and ethical use of consumer data, which directly influence consumer trust. Consumer trust is a critical determinant of long-term customer relationships and business sustainability in the digital economy. This conceptual article examines the role of AI in personalized marketing and its influence on consumer trust by integrating relevant theories such as Relationship Marketing Theory, Technology Acceptance Model (TAM), Trust Theory, and Privacy Calculus Theory. The article proposes a conceptual framework explaining how AI-driven personalization affects consumer trust through perceived usefulness, transparency, privacy concerns, and perceived control. The study contributes to marketing literature by synthesizing existing research and identifying key factors influencing consumer trust in AI-enabled personalized marketing. The article concludes with theoretical and practical implications and directions for future research
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