Kepercayaan Konsumen terhadap Iklan Personalisasi Berbasis AI di Media Sosial

Abstract

The synthesis reveals that algorithmic transparency, data security, and algorithmic fairness play interrelated and critical roles in shaping consumer perceptions of AI-based personalized ads. Algorithmic transparency generally enhances perceptions of openness and accountability; however, excessive or overly technical disclosure may trigger surveillance concerns and reduce consumer comfort. Data security and privacy emerge as the most influential factors, as privacy concerns consistently weaken consumer trust and diminish purchase intentions, even when advertising relevance is high. Algorithmic fairness significantly affects perceptions of system legitimacy, where perceived bias or discriminatory targeting undermines acceptance and fosters consumer resistance. Collectively, these ethical dimensions influence purchase decisions through consumers’ evaluations of perceived benefits, risks, and ethical legitimacy embedded in the personalization process. The study contributes theoretically by integrating transparency, data security, and fairness into a unified ethical framework for understanding consumer responses to AI-based advertising. Practically, the findings highlight the necessity for marketers, platform providers, and policymakers to implement transparent, secure, and fair AI systems to enhance consumer trust and improve the effectiveness of digital marketing strategies. Overall, this review underscores that ethical AI implementation is not merely a regulatory concern but a strategic determinant of consumer acceptance and purchasing behavior in digital advertising ecosystems.