AI in Accounting: Insights from a Bibliometric Analysis

Ani Stoykova
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Ani Stoykova: South-West University "Neofit Rilski", Blagoevgrad, Bulgaria

CECCAR Business Review, 2024, vol. 5, issue 8, 56-71

Abstract: Artificial intelligence has ushered in a new era of technological innovation, fundamentally transforming various sectors, including accounting. As businesses increasingly operate in a data-driven environment, the demand for real-time financial analysis and predictive insights has surged. This study aims to perform a bibliometric literature analysis focusing on significant literature, countries, authors, keywords, thematic evolution, citations, and documents, which researchers can reference in future studies related to the implementation of AI in accounting. VOSviewer software tool is used to create various maps based on the bibliographic data. The dataset was extracted from the Scopus database. Citation analysis, bibliographic coupling analysis, co-citation analysis, and co-occurrence analysis of author keywords are conducted. The analysis shows a sharp increase in research on AI and accounting from 2019, with 72 publications in 2023 and 66 publications by mid-2024, indicating rising interest and progress in this field. The bibliometric analysis reveals the dominant role of the United States in AI and accounting research. The co-occurrence analysis of author keywords shows important themes and their connections in AI and accounting, with artificial intelligence being the central theme, closely linked with other key concepts like accounting, machine learning, and big data. The findings underscore the practical implications of AI integration in accounting, emphasizing its potential to enhance efficiency, accuracy, and strategic decision-making in financial practices.

Keywords: accounting; artificial intelligence; bibliometric analysis; literature review (search for similar items in EconPapers)
JEL-codes: M40 M41 O33 Q55 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:ahd:journl:v:5:y:2024:i:8:p:56-71

DOI: 10.37945/cbr.2024.08.07

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