ChatGPT and the Financial Statement Audit: Can Staff Level Employees at Audit Clients Use ChatGPT to Answer Auditor Inquiries?

Gregory P. Tapis et al.

Journal of Emerging Technologies in Accounting2026https://doi.org/10.2308/jeta-2024-040article
AJG 1ABDC B
Weight
0.50

Abstract

Munshi (2024) describes how ChatGPT is transforming and disrupting the audit profession. Although some studies have examined the use of ChatGPT by auditors, little research has focused on its use by clients in financial statement audits. Given the importance of inquiry in the audit process, erroneous or unsupported client responses generated by ChatGPT could lead to inefficiencies and compromise audit quality. We investigate whether ChatGPT 4.0 can provide plausible responses to audit fieldwork inquiries and explore the implications of clients using AI to answer auditor questions. Our preliminary results show ChatGPT can generate plausible responses to basic inquiries and provides guidance for answering more complex questions. This paper highlights the potential for artificial intelligence to disrupt traditional audit procedures and stresses the need for auditors to adapt inquiry methods to mitigate risks associated with AI-generated responses. These findings offer significant implications for practitioners and present new research avenues for academics.

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https://doi.org/https://doi.org/10.2308/jeta-2024-040

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@article{gregory2026,
  title        = {{ChatGPT and the Financial Statement Audit: Can Staff Level Employees at Audit Clients Use ChatGPT to Answer Auditor Inquiries?}},
  author       = {Gregory P. Tapis et al.},
  journal      = {Journal of Emerging Technologies in Accounting},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.2308/jeta-2024-040},
}

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ChatGPT and the Financial Statement Audit: Can Staff Level Employees at Audit Clients Use ChatGPT to Answer Auditor Inquiries?

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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.