Emerging Technologies and Governance

This study examines how artificial intelligence (AI) governance takes shape within two contrasting administrative systems-Indonesia's decentralized structure and Malaysia's more centralized model.Despite both countries adopting ambitious national AI strategies, the consistency and effectiveness of implementation vary widely.Using a multi level comparative document analysis, the research traces how governance structures, institutional capacities, and data governance arrangements interact to influence policy coherence and administrative behavior.The analysis reveals a recurring pattern: coherent AI governance emerges not from strategy design alone, but from the alignment between institutional architectures and the robustness of underlying data systems.Malaysia demonstrates relatively stable alignment supported by centralized coordination, whereas Indonesia exhibits fragmented uptake shaped by provincial variation and uneven data infrastructures.These findings highlight institutional-data alignment as a mechanism that links policy ambition with operational reality, explaining why similar policies generate different outcomes across governance contexts.The study concludes that strengthening AI governance requires reinforcing multilevel coordination, investing in interoperable data systems, and tailoring regulatory instruments to underlying administrative structures.The results provide actionable guidance for policymakers seeking to design AI strategies that are both context sensitive and administratively executable.