Is artificial intelligence improving the audit process?

Anastassia Fedyk (), James Hodson (), Natalya Khimich () and Tatiana Fedyk ()
Additional contact information
Anastassia Fedyk: University of California Berkeley, Haas School of Business
James Hodson: AI for Good Foundation
Natalya Khimich: Drexel University, LeBow College of Business
Tatiana Fedyk: University of San Francisco, School of Management

Review of Accounting Studies, 2022, vol. 27, issue 3, No 5, 938-985

Abstract: Abstract How does artificial intelligence (AI) impact audit quality and efficiency? We explore this question by leveraging a unique dataset of more than 310,000 detailed individual resumes for the 36 largest audit firms to identify audit firms’ employment of AI workers. We provide a first look into the AI workforce within the auditing sector. AI workers tend to be male and relatively young and hold mostly but not exclusively technical degrees. Importantly, AI is a centralized function within the firm, with workers concentrating in a handful of teams and geographic locations. Our results show that investing in AI helps improve audit quality, reduces fees, and ultimately displaces human auditors, although the effect on labor takes several years to materialize. Specifically, a one-standard-deviation change in recent AI investments is associated with a 5.0% reduction in the likelihood of an audit restatement, a 0.9% drop in audit fees, and a reduction in the number of accounting employees that reaches 3.6% after three years and 7.1% after four years. Our empirical analyses are supported by in-depth interviews with 17 audit partners representing the eight largest U.S. public accounting firms, which show that (1) AI is developed centrally; (2) AI is widely used in audit; and (3) the primary goal for using AI in audit is improved quality, followed by efficiency.

Keywords: Artificial intelligence; Technology adoption; Audit quality; Audit efficiency; Labor displacement (search for similar items in EconPapers)
JEL-codes: D22 E24 J24 M42 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://link.springer.com/10.1007/s11142-022-09697-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:reaccs:v:27:y:2022:i:3:d:10.1007_s11142-022-09697-x

Ordering information: This journal article can be ordered from
http://www.springer.com/accounting/journal/11142

DOI: 10.1007/s11142-022-09697-x

Access Statistics for this article

Review of Accounting Studies is currently edited by Paul Fischer

More articles in Review of Accounting Studies from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().