The Problem of Moral Agency in the Context of Accounting and Auditing Automation

The article analyzes the problem of moral agency of artificial intelligence in the context of accounting and auditing automation. Three interrelated issues are examined: the debate on artificial moral agency as applied to the professional ethics of accountants and auditors, distributed responsibility in “auditor–AI” systems, and the responsibility gap in the use of learning systems in audit practice. It is shown that traditional criteria of moral agency (free will, consciousness, intentionality) are directly related to the concepts of professional judgment and professional skepticism enshrined in international auditing standards. The necessity of updating professional standards, developing requirements for algorithm explainability, certifying AI audit tools, and creating educational programs for auditors is substantiated.

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Publication Details

Journal
Auditor
Published
2026-08-25
DOI
https://doi.org/10.12737/1998-0701-2026-12-8-16-22
Primary Topic
Agricultural and Financial Auditing
Type
article
Field-Weighted Citation Impact
0.00
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article

The Problem of Moral Agency in the Context of Accounting and Auditing Automation

Sofya N. Chernaya
Auditor
Agricultural and Financial Auditing
article

The Problem of Moral Agency in the Context of Accounting and Auditing Automation

Sofya N. Chernaya
article en

Abstract

The article analyzes the problem of moral agency of artificial intelligence in the context of accounting and auditing automation. Three interrelated issues are examined: the debate on artificial moral agency as applied to the professional ethics of accountants and auditors, distributed responsibility in “auditor–AI” systems, and the responsibility gap in the use of learning systems in audit practice. It is shown that traditional criteria of moral agency (free will, consciousness, intentionality) are directly related to the concepts of professional judgment and professional skepticism enshrined in international auditing standards. The necessity of updating professional standards, developing requirements for algorithm explainability, certifying AI audit tools, and creating educational programs for auditors is substantiated.

AuditorVol. 12(8)
Partnerships for the goals
Openalex Percentile: Top 4%
Agricultural and Financial Auditing
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