<![CDATA[The rapid advancement of digital technologies has transformed public governance, evolving from e-government to more integrated digital government systems. However, the transition toward fully autonomous digital governance remains limited. This study aims to analyze how the integration of Artificial Intelligence (AI), data governance, and smart infrastructure can enable the development of autonomous digital governance systems. Using a mixed-method approach, this research combines a systematic literature review and case study analysis with quantitative survey data to examine the relationships between key variables, including AI capability, data governance quality, and infrastructure readiness. The findings indicate that the integration of these components significantly contributes to the formation of an autonomous decision-making system, which in turn enhances governance outcomes in terms of efficiency, transparency, and responsiveness. AI capability emerges as the most influential factor, particularly in enabling automation and predictive analytics, while data governance ensures the reliability and accountability of data-driven processes. Smart infrastructure supports real-time data collection and system connectivity, although disparities in infrastructure readiness remain a challenge. The study also identifies key benefits of autonomous digital governance, including faster decision-making, reduced human bias, and the development of predictive public services. However, several risks are highlighted, such as ethical concerns, privacy issues, and over-reliance on technology. This research proposes an integrated conceptual model of autonomous digital governance, emphasizing the need for synergy between technological and institutional components. The study contributes to the advancement of digital governance theory while providing practical insights for policymakers in designing future-ready governance systems.]]>
