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March 3, 2026Journal of risk and financial management2 citationsOpen Access

The Impact of Artificial Intelligence on Accounting Information and Earnings Management: Bibliometric Analysis

DADalenda Ben Ahmed

Key Points

  • Integrating artificial intelligence into accounting enhances the transparency of financial information, reducing information asymmetry.
  • The analysis identified 98 articles published from 2017 to 2025, highlighting a trend of increasing scientific output in this area.
  • Bibliometric analysis using the Bibliometrix package in RStudio recognized key authors, articles, and frequently used keywords in the literature.
  • Implications suggest that artificial intelligence may simultaneously limit and promote sophisticated forms of earnings management.

Abstract

Artificial intelligence technology has increased in popularity in the domain of accounting. Previous studies have focused on analysing the impact of AI integration on accounting in general and on work performance, with few researchers analysing the impact of AI on accounting information. Our study aims to determine the impact of AI on accounting information, on the one hand, and earnings management, on the other, using a bibliometric analysis that examines trends in scientific output. Our analysis was based on the use of the Bibliometrix package of RStudio software. The information is obtained from the “Web of Science” database, which identified 98 articles published in 37 journals that are the subject of our bibliometric analysis for the period 2017–2025. Our study shows that integrating AI into accounting can resolve the problem of information asymmetry, increase the transparency of financial information, and both limit earnings management practices and promote more sophisticated forms of earnings management. The bibliometric results show an increase in scientific output on our topic from 2023 onwards, reaching its peak in 2025. Bibliometric analysis presents productivity over time, identifies the most developed topics and the most cited authors and articles, and reveals the most frequently used keywords. This study provides guidance for future research directions.

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Cite This Study

Dalenda Ben Ahmed (2026) studied this question.

synapsesocial.com/papers/69a75a8bc6e9836116a20818https://doi.org/10.3390/jrfm19010090
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