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Is artificial intelligence improving the audit process?

Author

Listed:
  • 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)

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.

Suggested Citation

  • Anastassia Fedyk & James Hodson & Natalya Khimich & Tatiana Fedyk, 2022. "Is artificial intelligence improving the audit process?," Review of Accounting Studies, Springer, vol. 27(3), pages 938-985, September.
    • Handle: RePEc:spr:reaccs:v:27:y:2022:i:3:d:10.1007_s11142-022-09697-x
    DOI: 10.1007/s11142-022-09697-x
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    References listed on IDEAS

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    3. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    4. Delia DELIU, 2024. "Professional Judgment and Skepticism Amidst the Interaction of Artificial Intelligence and Human Intelligence," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 22(176), pages 724-741, October.
    5. Bastani, Spencer & Waldenström, Daniel, 2024. "AI, Automation and Taxation," IZA Policy Papers 212, Institute of Labor Economics (IZA).
    6. Marc Eulerich & Aida Sanatizadeh & Hamid Vakilzadeh & David A. Wood, 2024. "Is it all hype? ChatGPT’s performance and disruptive potential in the accounting and auditing industries," Review of Accounting Studies, Springer, vol. 29(3), pages 2318-2349, September.
    7. Cassandra Estep & Emily E. Griffith & Nikki L. MacKenzie, 2024. "How do financial executives respond to the use of artificial intelligence in financial reporting and auditing?," Review of Accounting Studies, Springer, vol. 29(3), pages 2798-2831, September.
    8. Vitali, Sonia & Giuliani, Marco, 2024. "Emerging digital technologies and auditing firms: Opportunities and challenges," International Journal of Accounting Information Systems, Elsevier, vol. 53(C).
    9. Angelica Buboi (Danaila), 2023. "Overall Impact of Specific Regulations on the Statutory Auditor's Behavior," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 265-275, August.
    10. Shuaiyu Chen & T. Clifton Green & Huseyin Gulen & Dexin Zhou, 2024. "What Does ChatGPT Make of Historical Stock Returns? Extrapolation and Miscalibration in LLM Stock Return Forecasts," Papers 2409.11540, arXiv.org.
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    More about this item

    Keywords

    Artificial intelligence; Technology adoption; Audit quality; Audit efficiency; Labor displacement;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing

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