Artificial Intelligence in External Auditing: Opportunities and Challenges

Abstract

Artificial Intelligence (AI) is transforming the auditing profession by enhancing the efficiency, accuracy, and effectiveness of external audit processes. Through technologies such as machine learning, natural language processing, robotic process automation, and predictive analytics, AI enables auditors to analyze large volumes of financial and non-financial data, identify anomalies, assess risks, and improve audit quality. the opportunities and challenges associated with the adoption of Artificial Intelligence in external auditing by evaluating its impact on audit efficiency, fraud detection, risk assessment, audit quality, and professional judgment. A quantitative research design was employed, and data were collected through structured questionnaires administered to external auditors, accounting professionals, audit managers, and financial executives across various industries. Appropriate statistical techniques were used to analyze the relationship between AI adoption and external audit performance. Artificial Intelligence significantly improves audit accuracy, accelerates data analysis, strengthens fraud detection capabilities, enhances risk assessment, and supports evidence-based audit decisions. However, challenges such as high implementation costs, data privacy concerns, cybersecurity risks, regulatory uncertainty, algorithm transparency, and the need for continuous training and upskilling of audit professionals. Artificial Intelligence has the potential to revolutionize external auditing by complementing, rather than replacing, professional judgment and enhancing the overall quality of audit services. valuable insights for audit firms, regulators, policymakers, and accounting professionals seeking to integrate AI technologies into modern auditing practices while addressing associated implementation challenges.