Artificial Intelligence in Financial Auditing: between Procedural Efficiency and Professional Reasoning

Svetlana MIHAILA & Galina Bãdicu

Audit Financiar2026https://doi.org/10.20869/auditf/2026/181/004article
ABDC C
Weight
0.50

What the paper says

The transformation of financial auditing through digitization, big data, and artificial intelligence is one of the most important challenges and opportunities for the contemporary accounting profession. The research aims to investigate how auditors and other professionals in the field of auditing and accounting in Moldova perceive the adoption of these technologies, with a focus on the level of digital skills, anticipated benefits, and barriers associated with implementation. Based on a systematic analysis of the international literature, five research hypotheses were formulated regarding the relationship between digital readiness, familiarity with artificial intelligence tools, perception of the human-technology partnership, ethical barriers, and experience in using AI solutions. The hypotheses were tested through a questionnaire applied to a sample of 63 respondents, including active auditors registered with audit entities, as well as other audit professionals (public auditors, internal auditors, audit trainees, accountants). Data analysis revealed correlations between the theoretically derived variables and the perceptions expressed, leading to the full confirmation of four hypotheses and the partial validation of one. The results showed that, although there is a clear association between digital skills and openness to the use of AI, reservations remain regarding familiarity and full confidence in its added value.

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https://doi.org/https://doi.org/10.20869/auditf/2026/181/004

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@article{svetlana2026,
  title        = {{Artificial Intelligence in Financial Auditing: between Procedural Efficiency and Professional Reasoning}},
  author       = {Svetlana MIHAILA & Galina Bãdicu},
  journal      = {Audit Financiar},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.20869/auditf/2026/181/004},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.