2025, Vol. 5, Issue 2, Part D

As artificial intelligence (AI) continues to reshape the foundations of the global digital economy, the governance of AI systems has emerged as a critical determinant of ethical accountability, data privacy, and algorithmic transparency. The increasing integration of AI into sectors such as finance, healthcare, and public administration has amplified concerns surrounding bias, explainability, and regulatory oversight. This paper provides a comprehensive evaluation of contemporary AI governance frameworks, analyzing how different jurisdictions conceptualize and operationalize ethical AI principles within digital economies. At a macro level, it explores the interplay between global governance initiatives including the OECD AI Principles, UNESCO’s Ethical AI Guidelines, and the European Union’s AI Act and national data protection regimes such as the GDPR and the U.S. Algorithmic Accountability Act. The analysis identifies significant disparities in enforcement mechanisms, transparency requirements, and stakeholder participation, reflecting the fragmented nature of global AI governance. From a focused perspective, the paper investigates how emerging economies navigate the balance between innovation and compliance amid limited regulatory infrastructure. It also examines how corporate governance structures incorporate AI ethics boards, bias auditing, and data governance policies to strengthen accountability in algorithmic decision-making. By comparing legal, institutional, and technical frameworks across regions, the study highlights best practices and gaps in achieving interoperable, human-centric AI governance. The findings underscore the urgent need for harmonized global standards that safeguard data integrity, ensure algorithmic explainability, and promote equitable digital transformation. Ultimately, the paper proposes a model for cohesive, cross-border AI governance that aligns technological progress with ethical and societal responsibility.