USING AI IN ACCOUNTING AND AUDITING: CHALLENGES OF HARMONIZATION WITH IFRS AND ISA

Abstract

The article examines the integration of artificial intelligence (AI) tools in accounting and auditing, highlighting both opportunities and challenges for aligning their application with International Financial Reporting Standards (IFRS) and International Standards on Auditing (ISA). AI in accounting is conceptualized as a set of methods capable of processing large volumes of data, identifying patterns, and generating forecasts to support managerial, accounting, and audit decisions. The study identifies the most widely used technologies, including machine learning, natural language processing, expert systems, and robotic process automation (RPA) with AI elements, and analyzes their practical applications in financial reporting, risk assessment, anomaly detection, and audit evidence collection. Particular attention is given to the challenges associated with AI implementation, including methodological risks, preservation of professional judgment, regulatory gaps, ethical considerations, and technical limitations. The article emphasizes the need for a systematic approach to AI adoption, integrating technological capabilities with compliance to IFRS and ISA, internal corporate policies, and auditor and accountant competencies. The Ukrainian experience is discussed, noting gradual adoption, existing regulatory and methodological constraints, and the importance of harmonization with international practices. Based on a TOWS analysis, strategic recommendations for leveraging AI in audit are proposed, while the roles of state authorities, professional organizations, and international bodies are outlined for standardization, methodological guidance, and competence development. The study concludes that AI serves as a decision-support tool, enhancing efficiency, accuracy, and data analysis capabilities while preserving the essential role of professional judgment in accounting and auditing.