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From Pen-and-Paper to Technology-Driven Analytics: Technology Usage in Internal Auditing

Martin Wagener et al.

Journal of Information Systems2025https://doi.org/10.2308/isys-2024-052article
AJG 1ABDC A
Weight
0.37

Abstract

Although thought leaders assume audit technology will enhance internal audit quality, research has provided limited evidence. This study surveys 285 chief audit executives (CAEs) in 2020 and compares their responses with those of 447 CAEs in 2023 to explore changes of internal audit quality from using software and data analytics over time. From 2020 to 2023, internal audit functions (IAFs) showed a steady shift toward more sophisticated and digitalized data analytics, with increased integration and reduced reliance on paper-based and spreadsheet tools, although full optimization remains limited. The findings also show that the use of audit management software (data analysis software) is positively associated with improvements in internal audit efficiency (effectiveness) across both time points. Notably, internal auditing’s data analytics maturity is associated with increased measures of internal audit quality, a trend that strengthens in the 2023 data. These findings provide evidence that software and data analytics are beneficial. Data Availability: The data that support the findings of this study are available from the authors upon reasonable request. JEL Classifications: M40; M42; G34; G32; M4; G3.

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https://doi.org/https://doi.org/10.2308/isys-2024-052

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@article{martin2025,
  title        = {{From Pen-and-Paper to Technology-Driven Analytics: Technology Usage in Internal Auditing}},
  author       = {Martin Wagener et al.},
  journal      = {Journal of Information Systems},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.2308/isys-2024-052},
}

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From Pen-and-Paper to Technology-Driven Analytics: Technology Usage in Internal Auditing

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
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.