📄 Abstract
The emergence of Generative Artificial Intelligence (GenAI) has transformed digital marketing by enabling highly personalized advertising experiences at an unprecedented scale. Unlike traditional machine learning systems that primarily predict consumer behavior, GenAI creates customized content, including text, images, videos, and interactive experiences tailored to individual preferences. This study examines the efficacy of Generative AI in personalized advertising by analyzing its impact on consumer engagement, purchase intention, brand perception, and advertising effectiveness. Drawing upon contemporary literature, industry reports, and theoretical frameworks such as the Technology Acceptance Model (TAM), Personalization Theory, and Consumer Trust Theory, the paper explores both the opportunities and challenges associated with AI-generated advertising. Findings indicate that GenAI significantly enhances consumer engagement, click-through rates, and conversion outcomes when personalization is perceived as relevant and non-intrusive. However, concerns regarding privacy, algorithmic bias, transparency, and ethical governance remain critical barriers to widespread acceptance. The study concludes that while Generative AI represents a paradigm shift in personalized advertising, its long-term effectiveness depends on balancing personalization with consumer trust, transparency, and regulatory compliance.
🏷️ Keywords
📚 How to Cite:
Indira S. , BEYOND THE ALGORITHM: ASSESSING THE EFFICACY OF GENERATIVE AI IN PERSONALIZED ADVERTISING , Volume 12 , Issue 6, June 2026, EPRA International Journal of Multidisciplinary Research (IJMR) , Pages: 424 - 427 ,