Artificial Intelligence in Financial Reporting and Auditing: Challenges and Future Opportunities
Year: 2026
Type: article
Abstract: Artificial Intelligence (AI) has become a game-changer in the world of financial reporting and auditing, revolutionizing the traditional methods of accounting and auditing by automating tasks, providing predictive insights, intelligent decision making, and real-time data processing. This research delves into the integration of AI into accounting systems, financial reporting and the auditing landscape, presenting challenges, governance issues and future prospects. The potential areas of the application of AI are covered, including automated bookkeeping, intelligent financial reporting, fraud detection, continuous auditing, blockchain-based assurance systems and AI-based sustainability reporting. Furthermore, the paper highlights several issues associated with algorithmic bias, transparency and explainability, cyber security, ethical implications and regulatory uncertainties in AI-powered accounting systems. In addition, the study examines key strategic implications for accounting firms, auditors, regulators, and policymakers on the use of AI, such as the importance of governance, the role of AI in human-AI partnerships, and the need for professional competency development. Moreover, the study identifies future trends and opportunities of autonomous accounting systems, generative AI, integrated ESG reporting and intelligent audit ecosystems. The results imply that AI can improve the quality of reporting, effectiveness of an audit, operational efficiency, and strategic financial decision-making. However, a balance is needed between technology innovation, ethical governance, regulatory supervision and professional judgment of humans for sustainable adoption of AI. The study offers a conceptual base for future research in intelligent financial reporting and auditing environment and also adds to the literature of intelligent accounting systems.
DOI: 10.1922/b30h8r08
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7222833085
FWCI:
Cites:
Cited by:
Related to:
