The Role Of Artificial Intelligence In U.S. Accounting And Financial Law

This study addresses the implications of AI on accounting, auditing, and financial law in the U.S., emphasizing machine learning, robotic process automation (RPA), and predictive analytics. Based on surveys, audit reports, regulatory documents and research data from 2020-2026, it examines the impact of AI on financial reporting reliability, audit quality, fraud detection analysis, effectiveness of internal controls and compliance. Results: These studies demonstrate that AI strengthens fiscal reporting accuracy, effectiveness of audit procedures, fraud detection, internal control systems design & evaluation (establishment) and the reliability of disclosures; tax classification in a state taxation system; compliance with International Financial Reporting Standards. Yet, risks include algorithmic transparency, overreliance on audits and explainability problems, documentation as potential liability protection (Fatah, et al 2025).

Although radical operational efficiencies and macro economies of scale produced by the adoption and diffusion of diverse artificial intelligence technologies provide many systems in the accounting sectors throughout all 50 states with material improvements, as actuated through their design inconstancy for AI, a plethora of new and very different legal and regulatory challenges have been triggered directly from use cases about how AI is developing. It suggests existing regulations—including but not limited to the Sarbanes-Oxley Act (SOX), comprehensive SEC rules, and pronounced PCAOB standards—require cautious and deliberate adaptation for an artificial intelligence-driven financing landscape that demands transparency, accountability, and robust governability.