From Ledgers to Learning Systems: The AI Revolution in Auditing

The auditing profession is undergoing a transformative shift as artificial intelligence (AI) moves from the periphery to the core of financial assurance processes. This paper explores the evolution of auditing practices from traditional, ledger-based methodologies to modern, intelligent systems driven by AI. It examines how machine learning algorithms, natural language processing, and data analytics are reshaping risk assessment, fraud detection, and decision-making within audit frameworks. While conventional audits rely heavily on sampling and retrospective analysis, AI-powered tools enable real-time examination of entire datasets, enhancing both efficiency and accuracy. The research delves into current applications of AI in auditing, including anomaly detection, predictive analytics, and the automation of repetitive tasks such as journal entry testing and compliance checks.