FROM BASICS TO INTELLIGENT TOOLS: ACCOUNTING INFORMATION AND AI IN PUBLIC‐SECTOR INTERNAL AUDITING
Ivan Dionisijev (),
Zorica Bozhinovska Lazarevska () and
Todor Tocev ()
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Ivan Dionisijev: Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, North Macedonia
Zorica Bozhinovska Lazarevska: Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, North Macedonia
Todor Tocev: Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, North Macedonia
No 2, Proceedings of the 5th International Conference "Economic and Business Trends Shaping the Future" 2024 from Faculty of Economics-Skopje, Ss Cyril and Methodius University in Skopje
Abstract:
This study examines the integration of artificial intelligence (AI) in public sector internal auditing, focusing on the extent of AI adoption, the types of AI tools used, and the challenges faced by auditors in implementation. The research employs both descriptive statistical analysis and inferential techniques, including Spearman’s correlation and ANOVA, to assess the relationships between AI adoption and institutional factors. Findings indicate that while data analytics is the most commonly used AI tool, a significant proportion of respondents do not utilize AI in their auditing practices. The primary barriers to AI adoption include a lack of training, high costs, and concerns regarding data privacy. The study further reveals that AI usage varies depending on the type of institution in which they work. These insights contribute to the ongoing discussion on digital transformation in auditing, emphasizing the need for enhanced training programs and strategic investments to facilitate AI integration.
Keywords: Internal auditing; Accounting information; Artificial Intelligence (AI); Public sector (search for similar items in EconPapers)
JEL-codes: H83 M42 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2025-12-15
New Economics Papers: this item is included in nep-inv
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Persistent link: https://EconPapers.repec.org/RePEc:aoh:conpro:2025:i:6:p:22-45
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