AI-Driven Hyper-Personalization in Online Retail: A Systematic Review of Consumer Ethical and Behavioral Responses

Abstract

Context and Research Gap: Artificial intelligence (AI) has transformed social media marketing and online retail by enabling hyper-personalization, delivering highly tailored consumer experiences that significantly influence purchase behavior. Recent studies emphasize that AI-driven personalization enhances engagement, satisfaction, and conversion rates. Simultaneously, another body of research underscores ethical concerns such as privacy invasion, perceived risks, trust erosion, and threats to consumer autonomy. While these studies provide foundational insights, an important gap persists as little is known about how individual-level factors like digital literacy and consumer tech-savviness moderate ethical perceptions and behavioral responses to hyper-personalized marketing. Addressing this gap is critical for understanding the complex spectrum of consumer responses, which range from enthusiasm and loyalty to skepticism and resistance. Methodology: To address this, the present study conducts a systematic literature review (SLR) of scholarly research published over the past decade (2015 to 2025), synthesizing evidence on consumer behavioral and ethical responses to AI-driven hyper-personalization in online retail. Following PRISMA guidelines, the review will identify, appraise, and integrate findings from peer-reviewed empirical studies examining key variables such as consumer trust, perceived privacy invasion, and perceived risk. Special attention will be given to how these mediating factors interact with moderators like digital literacy and tech-savviness to shape consumer purchase behavior and brand engagement. Expected Contribution: This research project seeks to contribute to the literature on AI use in digital and social media marketing by developing a comprehensive conceptual framework that maps the ethical and behavioral dynamics of hyper-personalization, offering both theoretical clarity and practical guidance. The framework should reflect the dual nature of AI-driven personalization: its capacity to drive value and its potential to provoke ethical concerns. Ultimately, this study aims to inform marketers and scholars on strategies for implementing AI responsibly.