Theoretical and Practical Aspects of Using Artificial Intelligence and Big Data Technologies in the Audit Process

In the context of digital transformation, the audit profession is undergoing significant changes driven by the rapid development of Artificial Intelligence (AI) and Big Data technologies. This article examines the theoretical foundations and practical applications of AI and Big Data in the audit process. The study highlights how advanced data analytics, machine learning algorithms, and automated audit tools enhance audit quality, improve risk assessment, and increase the efficiency of detecting errors and fraud. Special attention is given to the transformation of traditional audit methods into continuous and real-time auditing models. The article also analyzes international best practices and identifies key challenges related to data security, professional judgment, and regulatory adaptation. Based on the analysis, recommendations are proposed for the effective integration of AI and Big Data technologies into modern audit systems, particularly in emerging economies.