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

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.