Data science and public sector accounting: Reviewing impacts on reporting, auditing, and accountability practices

This article provides a comprehensive review of the existing research on the use of algorithmic-based technologies, including artificial intelligence (AI) and machine learning, in public sector accounting, financial reporting, and auditing, deriving implications for the production and use of financial information, and accountability. There is a considerable shortage of research about data science on public sector financial information reporting, auditing and consequent accountability. Most studies lack theoretical background, focusing on the technical feasibility of data science applications, and presenting scarce empirical evidence on their organizational implications and on governance challenges. Future research should explore the ethical risks in financial management and reporting settings, accountability frameworks, and the evolving role of financial professionals in hybrid AI–human environments. Addressing these gaps will provide valuable insights into how data science can enhance—not undermine—public sector financial integrity, ensuring alignment with democratic values and governance principles.