Algorithmic Accountability and Digital Sovereignty: Implementation Pathways for AI Legal Frameworks in Developing Nations

Аннотация

Building upon the foundational analysis of international AI regulatory frameworks, this research addresses the
critical implementation gap between legislative design and operational reality. While prior scholarship has established the
theoretical primacy of the risk-based approach and the normative influence of the EU AI Act–whose full high-risk obligations
entered into force in 2026–, the practical question of how developing nations can operationalize these standards
remains insufficiently theorized. The study examines four core implementation challenges: institutional capacity deficits,
cross-border data governance conflicts, the algorithmization of public administration, and the protection of fundamental
rights within automated decision-making systems. Employing an institutional analysis framework, complemented by comparative
case studies from Singapore, Brazil, Vietnam, and the Gulf Cooperation Council states, the research proposes a
context-sensitive “Graduated Implementation Model” (GIM) for nations navigating the tension between regulatory harmonization
and sovereign digital development. The analysis is grounded in recent empirical developments, including Uzbekistan’s
adoption of the Strategy for the Development of Artificial Intelligence Technologies until 2030 (Cabinet of Ministers
Resolution No. 425, October-2025), its rise from 70th to 62nd place in the AI Readiness Index between 2024–2025, and
the anticipated launch of national AI regulatory sandboxes by mid-2026. The findings affirm that effective AI governance
is not merely a legislative endeavor but a systemic institutional transformation–one that Uzbekistan and its Central Asian
neighbors are increasingly positioned to undertake.