AI in Financial Auditing: Addressing U.S. Audit Failures and Strengthening PCAOB/SEC Compliance

The adoption of Artificial Intelligence (AI) is transforming financial auditing by offering unprecedented opportunities to enhance audit quality, efficiency, and regulatory compliance. This paper examines the role of AI in addressing persistent audit failures in the United States and strengthening compliance with PCAOB and SEC standards. AI technologies, including machine learning, natural language processing, anomaly detection, and robotic process automation, enable auditors to analyze entire datasets, detect fraud, assess risks, and monitor compliance more effectively than traditional methods. Despite these benefits, adoption remains constrained by challenges such as algorithmic opacity, ethical concerns, data privacy risks, limited auditor expertise, and regulatory uncertainty. Using a systematic literature review of peer-reviewed academic studies and professional reports published between 2020 and 2025, this study highlights the potential of AI to mitigate recurring deficiencies identified in PCAOB inspections and support the SEC’s investor-protection mandate. The findings underscore the need for robust ethical frameworks, targeted auditor reskilling, curriculum redesign, and updated regulatory guidance to ensure responsible and effective integration of AI into audit practices. This paper contributes to the understanding of AI’s transformative potential in auditing and offers practical insights for auditors, regulators, and policymakers seeking to modernize financial reporting and restore public trust in the audit profession.