Automation and artificial intelligence in accounting: a comprehensive bibliometric analysis and future trends

Purpose This paper aims to provide a comprehensive bibliometric approach to analyze the integration of automation and artificial intelligence (AI) in accounting. The study identifies key trends, influential works and future directions to help academics, practitioners and regulators maximize the potential of automation and AI in accounting. Design/methodology/approach This paper conducted a bibliometric analysis, using performance analysis and science mapping techniques to examine 343 articles from the Scopus database covering the period from 2001 to 2024. Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocol was used to ensure a systematic and objective process for identifying, screening and including relevant studies. The analysis used Biblioshiny to generate bibliometric indicators, such as publication trends, thematic maps and insights into co-citation patterns, thematic evolution and the intellectual framework outlining the scope of automation and AI in accounting. Findings The results reveal that the research area is structured around four main conceptual clusters: automation and AI as tools for enhancing accounting practices, the shift toward digital management accounting processes, emerging technologies such as blockchain and Internet of Things for process automation in accounting and auditing and machine learning (ML) and advanced data analytics for fraud detection, real-time reporting and cost optimization. Also, the analysis of theme evolution demonstrates a clear shift from automation (2001–2010) to AI and ML (2011–2020) with digital transformation, big data and data analytics as dominant themes in 2023–2024. Originality/value To the best of the authors’ knowledge, this study is the first comprehensive bibliometric analysis of the available literature on automation and AI in accounting. This analysis fills a critical gap by providing insights into unexpected areas such as the intellectual and social structure of the research area. Using PRISMA and Biblioshiny, this study outlines key trends and gaps, providing guidance for further studies in the digital era.

Authors

Publication Details

Journal
Journal of financial reporting & accounting
Published
2025-03-17
DOI
https://doi.org/10.1108/jfra-09-2024-0639
Citations
15
Primary Topic
Financial Reporting and XBRL
Type
article
Field-Weighted Citation Impact
34.26
Controls
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article

Automation and artificial intelligence in accounting: a comprehensive bibliometric analysis and future trends

Sahar Elnakeeb, Heba Saad Hassan Elawadly
15 citations
Journal of financial reporting & accounting
Financial Reporting and XBRL
34.26
article

Automation and artificial intelligence in accounting: a comprehensive bibliometric analysis and future trends

Sahar Elnakeeb, Heba Saad Hassan Elawadly
article en
15 citations

Abstract

Purpose This paper aims to provide a comprehensive bibliometric approach to analyze the integration of automation and artificial intelligence (AI) in accounting. The study identifies key trends, influential works and future directions to help academics, practitioners and regulators maximize the potential of automation and AI in accounting. Design/methodology/approach This paper conducted a bibliometric analysis, using performance analysis and science mapping techniques to examine 343 articles from the Scopus database covering the period from 2001 to 2024. Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) protocol was used to ensure a systematic and objective process for identifying, screening and including relevant studies. The analysis used Biblioshiny to generate bibliometric indicators, such as publication trends, thematic maps and insights into co-citation patterns, thematic evolution and the intellectual framework outlining the scope of automation and AI in accounting. Findings The results reveal that the research area is structured around four main conceptual clusters: automation and AI as tools for enhancing accounting practices, the shift toward digital management accounting processes, emerging technologies such as blockchain and Internet of Things for process automation in accounting and auditing and machine learning (ML) and advanced data analytics for fraud detection, real-time reporting and cost optimization. Also, the analysis of theme evolution demonstrates a clear shift from automation (2001–2010) to AI and ML (2011–2020) with digital transformation, big data and data analytics as dominant themes in 2023–2024. Originality/value To the best of the authors’ knowledge, this study is the first comprehensive bibliometric analysis of the available literature on automation and AI in accounting. This analysis fills a critical gap by providing insights into unexpected areas such as the intellectual and social structure of the research area. Using PRISMA and Biblioshiny, this study outlines key trends and gaps, providing guidance for further studies in the digital era.

Journal of financial reporting & accounting
Openalex Percentile: Top 0%
Financial Reporting and XBRL
34.26
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