The impact of Artificial Intelligence (AI), accounting analytics and machine learning on auditing: Enhancing internal control and fraud detection in public sector organizations

Abstract

Over the years, there has been an inclined growth in technology such that artificial intelligence (AI), accounting analytics, and machine learning have revolved in the practice of auditing in accounting field. Numerous substantial possibilities are presented by the above-mentioned technologies which include creating a robust framework of internal control and optimizing fraud detecting activities especially in the public organizational sector, where accountability and clarity are a necessity. The study examined the Impact of Artificial Intelligence (AI), Accounting Analytics and Machine Learning on Auditing: Enhancing Internal control and Fraud Detection in public sector organizations. This study employed a mixed-methods approach. It analyzed quantitative and qualitative data collected from: Government audit reports and financial statements, AI-driven risk assessment models and machine learning fraud detection datasets, Auditor and financial expert surveys (to gauge perception and practical AI implementation challenges), and Case studies from public sector organizations worldwide. The findings demonstrate that AI powered audit tools significantly reduce human errors, accelerate financial audits, and improve financial accuracy. Moreso, AI-based fraud detection models outperform traditional auditing methods, identifying fraudulent transactions with an 87% accuracy rate, compared to the 60-70% success rate of conventional audits. Keywords: Artificial Intelligence, Machine Learning, Accounting Analytics, Fraud Detection, Internal Control, Public Sector.