International Journal of Management

The growing interdependence of digital ecosystems allows artificial intelligence (AI) systems to train on globally sourced datasets, enabling improvements in multilingual models, personalized services, and cross-border innovation. However, ethical concerns arise when data crosses national boundaries without legal clarity, informed consent, cultural sensitivity, or alignment with local governance norms. This paper examines ethical issues in internationally distributed data pipelines, including privacy violations, data colonialism, surveillance abuse, cultural misinterpretation, and power asymmetries. Using hypothetical datasets from five regions, we analyze how regulations such as GDPR, China’s PIPL, India’s DPDP Act, and U.S. sectoral privacy laws impact AI ethics. A Global Ethical Data Framework is proposed to ensure transparent, fair, culturally aware, and lawful AI systems.