Beyond Personalization: The Paradox of AI-Driven Marketing and Consumer Trust in the Age of Data Privacy Concerns

Abstract

This study examined the paradoxical relationship between AI-driven personalization and consumer trust in the context of escalating data privacy concerns. While advanced artificial intelligence technologies enabled highly tailored marketing experiences, they simultaneously intensified perceptions of surveillance and data misuse. The research aimed to investigate how AI capability influenced perceived personalization benefits, privacy concerns, and ultimately consumer trust and purchase intention. A quantitative approach was employed using survey data collected from 320 digital consumers, analyzed through structural equation modeling (SEM). The findings revealed that AI-driven personalization significantly enhanced perceived relevance and engagement; however, it also heightened privacy concerns, which negatively affected consumer trust. Notably, trust was found to mediate the relationship between personalization and purchase intention, highlighting a critical trade-off between personalization effectiveness and ethical data practices. Furthermore, transparency and perceived control over personal data moderated the negative effects of privacy concerns, suggesting that responsible AI governance could mitigate trust erosion. The study concluded that while AI-driven marketing strategies improved short-term engagement outcomes, long-term sustainability depended on balancing personalization with privacy assurance. These findings contributed to the emerging discourse on ethical AI marketing by proposing a trust-centered framework that reconciled technological advancement with consumer protection in the digital economy.

Keywords: AI-driven marketing; consumer trust; data privacy; personalization paradox