SUMMARY On May 19, 2026, the Securities and Exchange Commission (SEC) issued a request for comment on its proposal to simplify filer status for public companies and to adjust the accommodations provided to emerging growth companies (SEC 2026). This comment letter summarizes the views of the participating members of the Auditing Standards Committee of the Auditing Section of the American Accounting Association with respect to the effect of the proposal on the application of the internal control over financial reporting audit requirement and resulting impact on the reliability of financial statements.
SUMMARY Auditors conducting risk assessment can use Generative AI (GenAI) to analyze large volumes of complex information from multiple sources. However, the technology underlying GenAI tools often struggles to retain and learn from feedback. This commentary proposes that auditors can address these limitations by organizing audit-relevant documents in knowledge graphs whose structured context persists across GenAI interactions. Auditors using knowledge graphs gain traceable reasoning paths that support explainability, constrain GenAI retrieval to relevant evidence, and reduce computational costs by limiting the documents processed. This commentary also discusses how knowledge graphs can be integrated into existing audit workflows under current auditing standards. JEL Classifications: M42.
SUMMARY The accounting profession is undergoing a period of rapid change in education requirements for CPA licensure. Many states and jurisdictions are reducing minimum required education for CPA licensure from 150 to 120 hours (Hood 2023; AICPA & National Association of State Boards of Accountancy (NASBA) 2024, 2025). However, little research has examined the relation between education level and CPA performance in practice. In this article, we summarize the published study by Barandi, Campbell, Guo, and Notbohm (2025), which finds a positive association between audit engagement partner graduate education and audit quality. The authors suggest that graduate programs enhance critical thinking, communication, and technical skills that are vital to auditing. As alternative pathways to licensure gain traction, these findings highlight the practice implications of graduate education. Public accounting firms, audit committees, and regulators could consider these results when making decisions and assessing the long-term effects of CPA licensure policy changes. JEL Classifications: M42.
On March 31, 2026, the Public Company Accounting Oversight Board (the Board or PCAOB) issued a request for comment on its strategic plan (PCAOB 2026). This comment letter summarizes the views of the participating members of the Auditing Standards Committee of the Auditing Section of the American Accounting Association. Our comments include responses to the questions listed in the request for comment. Our key recommendations are to prioritize inspections-particularly through expanded support for smaller firms, return to the supervisory model, advance standard setting in areas such as technology, ICFR, and complex estimates, and enhance transparency across inspections, quality control reporting, and PCAOB operations.
This study examines whether large language models can predict critical audit matters (CAMs) from management discussion and analysis (MD&A) disclosures in 10-K filings. We tested four models, OpenAI's O3-Pro and O3-Mini High, Anthropic's Claude Sonnet 4, and Google's Gemini 2.5 Flash, using zero-shot prompts against auditor-identified CAMs across 141 firm-year observations in technology, finance, consumer discretionary, and healthcare. We benchmarked predictive capability matching auditor CAMs and generative capacity, identifying audit-relevant risk matters from MD&A. O3-Mini High demonstrated the strongest predictive performance, whereas Gemini 2.5 Flash underperformed in both areas. Technology achieved the highest prediction accuracy, whereas healthcare ranked last. We also examined how management tone and algorithmic bias jointly affect prediction outcomes. These findings position artificial intelligence (AI) as a valuable screening tool to support auditor planning, while reinforcing that professional judgment remains essential to final CAM determination.
