Futurology of Artificial Intelligence Governance in a Smart Government for Achieving a Sustainable and Efficient Structure for Utilizing Advanced Technologies

Abstract

The primary objective of this study is to explore the impact of artificial intelligence (AI) on governance processes and to identify potential governance structures that could be implemented to manage AI effectively. This study aims to address the current research gap by examining the key variables influencing AI governance and proposing strategic scenarios based on a structured analysis. This research employs a descriptive design, utilizing an extensive literature review and MICMAC (Matrix of Cross-Impact Multiplications Applied to Classification) analysis. The literature review provided foundational data by identifying significant criteria and sub-criteria related to AI governance from academic journals, policy reports, and governmental publications. These variables were then analyzed using the MICMAC method, which involves constructing a cross-impact matrix to map the interdependencies among variables. The analysis classified variables into categories such as autonomous, dependent, linkage, and driving, providing a comprehensive understanding of the dynamics involved. Scenario development was also carried out to propose governance strategies. The MICMAC analysis revealed critical variables that drive AI governance, including transparency, data protection, ethical considerations, risk management, and sustainability. The study identified the significant interdependencies among these factors and classified them into categories that highlight their roles in governance. Strategic scenarios were developed, emphasizing the importance of continuous policy review, ethical frameworks, and collaboration among stakeholders. The findings suggest that effective AI governance requires adaptable strategies that support innovation while protecting public interests and ensuring long-term sustainability. This study concludes that AI governance in smart governments must be comprehensive and dynamic, addressing both technological advancements and societal needs. The proposed scenarios highlight the necessity of global coalitions, transparent information sharing, and proactive risk management. While this research provides a preliminary understanding of AI governance structures, further empirical studies are needed to validate and refine these strategies. The study emphasizes the importance of ongoing research and collaboration to ensure AI technologies are leveraged responsibly and effectively for societal benefit.