Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation
Abstract
After decades of frustration with long “AI Winters,” various business industries are witnessing the arrival of AI's “Spring,” with its massive and compelling benefits. Auditing will also evolve with the application of AI. Recently, there has been a progressive evolution of technology aimed at creating “artificially intelligent” devices. Although this evolution has been permeated with false starts and exaggerated claims, there is some convergence on the fact that substantive progress has been obtained in the last few years with the adoption of deep learning in conjunction with much faster machines and dimensionally larger storage spaces (and samples). The area of auditing has lagged business adoption in the past (Oldhouser 2016), but is prime for partial automation due to its labor intensiveness and range of decision structures. Several accounting firms have disclosed substantive investments in the AI fields. This paper proposes various areas of AI-related research to examine where this emerging technology is most promising. Moreover, this paper raises a series of methodological and evolutionary research questions aiming to study the AI-driven transformation of today's world of audit into the assurance of the future.
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Issa, Sun, and Vasarhelyi mapped audit tasks most susceptible to automation and found they clustered in judgment-intensive areas: risk identification, anomaly detection, and evaluation of estimates.
“Issa, Sun, and Vasarhelyi (2016) mapped the audit tasks most susceptible to this form of automation and found that they clustered precisely in the areas the standards treat as judgment-intensive: risk identification, anomaly detection, and the evaluation of estimates.”
From Auditing the Black Box: Rethinking Audit Assurance and Professional Liability in the Age of Artificial Intelligence (2026) · cites this paper as Issa, Sun, and Vasarhelyi (2016)
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- Authors
- Issa, H., Sun, T., & Vasarhelyi, M. A.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Venue
- Journal of Emerging Technologies in Accounting
- Publisher
- American Accounting Association
- Published
- 2016-09-01
- Volume
- 13
- Issue
- 2
- Pages
- 1-20
- ISSN
- 1554-1908 (ISSN-L)
- 1558-7940
- OpenAlex
- W2591793331
- Cited by
- 491
- References
- 58
- Citations by year
- 2026: 103 · 2025: 80 · 2024: 77 · 2023: 56 · 2022: 40 · 2021: 47 · 2020: 44 · 2019: 24 · 2018: 14 · 2017: 6
- FWCI
- 19.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Emerging Technologies in Accounting (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Robotic Process Automation Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- artificial intelligence in auditing, audit automation, deep learning, assurance, research agenda
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