ADVANCING AI IN MARKETING THROUGH CROSS BORDER INTEGRATION ETHICAL CONSIDERATIONS AND POLICY IMPLICATIONS

Abstract

This study critically examines the advancement of artificial intelligence (AI) in marketing through the lens of cross-border integration, focusing on ethical considerations and policy implications. With AI-driven tools increasingly shaping global marketing strategies—ranging from personalization engines and predictive analytics to chatbots and real-time bidding systems—the ethical, cultural, and regulatory dimensions of these technologies have become more significant than ever. Drawing upon the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, this review systematically analyzed a total of 126 peer-reviewed scholarly articles and 23 international policy reports published between 2015 and 2022. The findings reveal that while AI technologies greatly enhance operational scalability and customer engagement across borders, they often fall short in addressing cultural sensitivity, linguistic accuracy, and fairness in algorithmic decision-making. Notably, issues such as algorithmic bias, emotional profiling, consent asymmetry, and data sovereignty emerged as critical concerns, especially in regions with fragmented regulatory landscapes. The study further identifies significant inconsistencies among global regulatory frameworks, including the European Union’s GDPR and AI Act, China’s PIPL, and the United States’ CCPA/CPRA, which complicate compliance and increase operational costs for multinational firms. In response, emerging governance models—such as algorithmic impact assessments, explainable AI tools, and multistakeholder frameworks—are gaining momentum but remain uneven in their global adoption. This review concludes that ethical and policy-aligned AI marketing requires not only technical sophistication but also cross-sectoral collaboration and culturally adaptive governance. As AI continues to redefine global consumer interaction, this study offers timely insights into how marketers, regulators, and technologists can collaboratively build transparent, accountable, and inclusive AI systems for cross-border marketing success.