Ethics and Regulations in Data-Driven and AI-Based Marketing: A Systematic Literature Review (2014-2025)

Abstract

The rapid integration of artificial intelligence (AI) and data-driven technologies in marketing has transformed consumer engagement, enabling unprecedented levels of personalization and targeting. However, these advancements have raised critical ethical and regulatory concerns regarding consumer privacy, algorithmic bias, fairness in targeting, and compliance with evolving data protection frameworks. This systematic literature review examines 173 peer-reviewed publications from 2014 to 2025, focusing on three core areas: (1) consumer privacy and data protection, (2) algorithmic bias and fairness in targeting, and (3) regulatory frameworks including GDPR, CCPA, and emerging compliance mechanisms. Our analysis reveals four primary ethical tensions: the personalization-privacy paradox, algorithmic discrimination in consumer segmentation, transparency deficits in automated decision-making, and accountability gaps in AI-driven marketing systems. Key findings indicate that while regulations like GDPR and CCPA have established foundational data protection standards, significant implementation challenges persist, including the difficulty of translating high-level ethical principles into practice, the opacity of "black box" AI systems, and the disconnect between regulatory compliance and consumer expectations. The review identifies critical research gaps in cross-border regulatory harmonization, bias mitigation in real-time targeting systems, and the development of practical ethical frameworks for generative AI in marketing. We propose a multi-stakeholder approach integrating technical solutions (bias detection tools, privacy-enhancing technologies), organizational practices (ethical leadership, algorithmic accountability), and policy interventions (dynamic governance frameworks, industry standards) to foster responsible AI-enabled marketing that balances innovation with consumer protection and societal values