EconPapers    
Economics at your fingertips  
 

Artificial Intelligence in Auditing and Financial Reporting: A Scoping Review of Current Practices and Future Directions

Ikemefula Oriaku (), Oluwafemi Bamidele, Thomas Mensah, Richmond Konadu and George Thomas
Additional contact information
Ikemefula Oriaku: Business and Management Department, University of Sunderland in London, England.
Oluwafemi Bamidele: College of Engineering, Prairie View A&M University, USA.
Thomas Mensah: Department of Computing and Information Technology, College of Southern Nevada, USA.
Richmond Konadu: Political Sciences, Communication & International Relations, University of Macerata, Italy.
George Thomas: College of Engineering, Iowa State University, Ames, Iowa, USA.

Post-Print from HAL

Abstract: AI is transforming auditing and financial reporting by improving audit efficiency, reporting accuracy, data analytics, risk assessment, fraud detection, and decision-making. Understanding present practices, problems, and future consequences is crucial as firms use AI-driven technology to simplify complicated audit procedures and improve reporting accuracy. This scoping review focuses on adoption of AI in auditing and financial reporting. This study followed a scoping review study design. The studies included in this study were retrieved through a comprehensive literature search conducted in Google Scholar and Dimensions to find recent studies from 2020 to September 12, 2025. A detailed analysis of selected works revealed key topics, including AI adoption trends, ethical and legal challenges, auditor obligations, and AI integration into audit processes. AI has enhanced audit quality and data reliability, but professional mistrust, ethical concerns, legal limitations, and data privacy issues still prevent total integration. This analysis finds that integrating AI into audits and financial reporting requires a balance between technology and expertise. Improved regulatory frameworks, auditor training, and cross-disciplinary collaboration are needed to foster transparency, accountability, and trust in AI-assisted financial systems. Future research must empirically validate AI technologies in audit contexts and across industries and create ethical norms for financial reporting.

Date: 2026-01-03
References: Add references at CitEc
Citations:

Published in Journal of Economics and Trade, 2026, 11 (1), pp.1 - 13

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05446327

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().

 
Page updated 2026-01-13
Handle: RePEc:hal:journl:hal-05446327