Governing Artificial Intelligence in the Public Sector: Institutional Challenges and Regulatory Responses in Emerging Economies

The rapid adoption of artificial intelligence (AI) in the public sector offers significant opportunities to improve public service delivery, administrative efficiency, and evidence-based policymaking. At the same time, it raises complex governance challenges concerning regulation, accountability, transparency, and institutional readiness, particularly in emerging economies where regulatory frameworks continue to evolve. This study examines AI governance in the public sector through a comparative policy analysis of Indonesia and India. Guided by Institutional Theory and Regulatory Governance Theory, the research employs qualitative comparative policy analysis of national AI strategies, digital governance policies, data protection regulations, and government policy documents. The findings identify four key institutional challenges: regulatory fragmentation, limited institutional capacity, weaknesses in data governance, and ethical accountability issues. Despite differences in governance capacity and digital development, both countries have introduced important regulatory and policy initiatives to strengthen AI governance. The study argues that effective public-sector AI governance depends on the interaction between institutional capacity, regulatory readiness, ethical governance, and public trust rather than technological advancement alone. Based on these findings, the study proposes an Adaptive Public AI Governance Framework (APAIGF) as a conceptual model for strengthening adaptive, accountable, and sustainable AI governance in emerging economies. The proposed framework contributes to the literature by offering context-sensitive policy insights for governments seeking to balance technological innovation with institutional legitimacy and public accountability.