Artificial Intelligence Governance in Public Sector Decision Making

Abstract

The use of artificial intelligence in the public sector is increasingly becoming a strategic necessity to improve the effectiveness of decision-making and the quality of government services. However, the success of artificial intelligence implementation is determined not only by technological sophistication but also by governance readiness, institutional capacity, and public legitimacy. This article presents a narrative review of Google Scholar-indexed literature published in the past five years, focusing on the role of artificial intelligence in supporting responsive, accountable, and sustainable decision-making. The study findings indicate that artificial intelligence can strengthen government analytical capabilities, accelerate policy responses, and improve accuracy in large-scale data management, particularly in the public service sector, which requires responsive processes. However, key challenges identified include the risk of algorithmic bias, the lack of audit mechanisms, gaps in human resource capacity, and public resistance due to low transparency and concerns about data privacy. Therefore, a governance framework that emphasizes explainability, public participation, and algorithm auditing is essential to maintain accountability and public trust. This article emphasizes that artificial intelligence implementation strategies must be implemented in stages through pilot projects, investment in human resource capacity, and multi-stakeholder collaboration to ensure the sustainability of the technology’s benefits in digital governance.