Challenges and Prevention Strategies for Internal Audits in AI and Blockchain-Based Accounting Information Systems
DOI:
https://doi.org/10.37385/ijedr.v6i6.9620Keywords:
Artificial Intelligence, blockchain, internal audit, accounting information systems, data security, digital regulationAbstract
This study aims to identify the main challenges and prevention strategies in the implementation of Artificial Intelligence (AI) and blockchain-based internal audits. The study used the Systematic Literature Review (SLR) method on 23 Scopus-indexed international articles published between 2015 and 2025. The analysis process was carried out through the stages of identification, selection, and synthesis of literature to obtain thematic patterns related to the challenges and strategies of implementing AI and blockchain-based internal audits. The results of the study indicate that the main challenges faced in the implementation of digital audits include data security and privacy risks, limitations in auditor competence regarding new technologies, regulatory and ethical gaps, and organisational resistance to change. The recommended strategies include improving the digital competence of auditors through continuous training, developing AI-based audit regulations and standards, implementing multi-layered security systems, and gradually integrating technology. This research provides new insights into mapping the relationship between human resource readiness, digital infrastructure, and organisational governance on the successful implementation of AI and blockchain in internal auditing. These findings confirm that the success of digital audit transformation depends not only on technological sophistication but also on organisational adaptation and the systematic development of auditor capacity.
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