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Muhammad Fajar Adi Nugroho
Master of Laws, Brawijaya University, Indonesia

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Beyond Regulatory Fragmentation: Developing a Global Administrative AI Governance Framework for Cross-Border Artificial Intelligence Systems Muhammad Fajar Adi Nugroho; Siti Nur Hanim; Luis Antonio Delgado
Justicia Insight Vol. 2 No. 2 (2026): Justicia Insight, May 2026
Publisher : Lembaga Publikasi Ilmiah Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70716/justin.v2i2.383

Abstract

The rapid expansion of cross-border artificial intelligence (AI) systems has exposed significant regulatory fragmentation across national, regional, and international governance regimes. Existing approaches to AI governance, including ethics-based frameworks, risk-based regulation, and digital constitutionalism, have contributed important normative principles but remain insufficient to address transnational accountability, oversight, and administrative coordination challenges. This article examines how Global Administrative Law (GAL) can provide a coherent legal foundation for governing AI systems that operate beyond territorial boundaries. Employing a normative socio-legal methodology, the study analyzes major AI governance instruments, including the European Union AI Act, OECD AI Principles, UNESCO Recommendation on the Ethics of Artificial Intelligence, Council of Europe initiatives, and relevant scholarly literature. The findings demonstrate that current governance models lack an integrated administrative architecture capable of ensuring transparency, participation, reviewability, accountability, and effective oversight across jurisdictions. In response, the article develops a Global Administrative AI Governance Framework (GAIGF), which integrates principles of GAL, digital constitutionalism, and algorithmic accountability into a multi-layered governance model for cross-border AI systems. The article argues that GAIGF offers a viable pathway toward regulatory interoperability and institutional coordination, thereby advancing both the theory and practice of global AI governance.