AI in Auditing: A Comprehensive Review of Applications, Benefits and Challenges

Abstract

The rapid evolution of artificial intelligence (AI) technologies has brought about transformative changes in various industries, and the field of auditing is no exception. This research paper presents a comprehensive review of the integration of AI in auditing practices, highlighting its applications, benefits, and associated challenges. Auditing, a critical process for ensuring the accuracy and reliability of financial information, has traditionally been a labor-intensive and time-consuming endeavor. The emergence of AI technologies, such as machine learning, natural language processing, and data analytics, has revolutionized the way audits are conducted. AI-powered auditing tools offer advanced capabilities for data analysis, pattern recognition, anomaly detection, and risk assessment. These capabilities enhance the effectiveness and efficiency of audits by allowing auditors to focus on high-risk areas and perform more in-depth analysis. The paper explores various applications of AI in auditing, including: Automated Data Analysis, Predictive Analytics, Fraud Detection, and Natural Language Processing (NLP), Continuous Monitoring. While AI brings significant benefits to the auditing process, its adoption also presents certain challenges like Data Quality and Integration, Interpretability, Ethical Considerations, Technical Expertise, Regulatory Frame Work. In conclusion, AI has the potential to revolutionize auditing practices by enhancing efficiency, accuracy, and risk assessment. However, successful integration requires addressing challenges related to data quality, transparency, ethics, skills, and regulations. As AI technologies continue to evolve, auditors and stakeholders must collaborate to harness the full potential of AI while maintaining the integrity and credibility of the auditing process. This paper serves as a comprehensive resource for auditors, researchers, and policymakers seeking to understand the current landscape and future directions of AI in auditing.