Digital transformation: Artificial intelligence shaping the future of public sector

Abstract

This study delves into the profound influence of artificial intelligence (AI) on the fiscal dynamics of the public sector. It chiefly examines how AI can enhance aspects such as efficiency, precision, openness, and responsibility in public financial administration. Literature research is included in qualitative research methods. To conduct Public Sector Finance literature. This research was conducted by the SLR method or systematic literature review by collecting data through the PRISMA method sourced from the Scopus database case studies focusing on AI deployment across various nations. Data It integrates both quantitative and qualitative data analysis to assess AI's impact and efficacy within the sphere of public finance. The final number of data was chosen 27 data to be selected. The primary discoveries reveal that AI harbors considerable potential to refine financial procedures in the public sector. This includes augmenting automation, diminishing human error, and bolstering decision-making grounded in data analysis. However, the study acknowledges challenges like data security concerns, technological infrastructure prerequisites, and the scarcity of adequately skilled personnel. It proposes resolutions such as establishing robust policy frameworks and implementing human resources training initiatives to surmount these hurdles. The implications of this research hold substantial significance for policymakers and practitioners in the public domain. AI is reshaping not just the operational modalities of public financial entities but also influencing governmental policy-making, strategies for human resource development, and the interaction dynamics between citizens and the government. The article underscores the necessity for a proactive and responsive adaptation of AI technologies, advocating for their integration to guarantee effective and transparent governance in public finance for the future.

Keywords

• artificial intelligence
• public sector finance
• digital transformation
• data security