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Artificial Intelligence (AI) in Accounting Education: A Scientometric Assessment

Nicolas Mendes Barbosa et al.

Journal of Information Systems and Technology Management2025https://doi.org/10.4301/s1807-1775202522014article
ABDC C
Weight
0.50

What the paper says

This study conducts a scientometric assessment of research on Artificial Intelligence (AI) in accounting education using data from the Web of Science and Scopus databases. A quanti-qualitative design was applied to 58 articles, analyzed through VOSviewer and Bibliometrix to map publication trends, collaboration networks, keyword structures, and scientometric regularities. Results reveal rapid growth since 2019, thematic consolidation around AI-driven pedagogical innovation, and strong contributions from the United States and China. Lotka’s and Bradford’s laws indicate author dispersion and journal concentration. The findings highlight emerging research fronts and provide implications for curriculum development, educational policy, and future scholarly inquiry.

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Cite this paper

https://doi.org/https://doi.org/10.4301/s1807-1775202522014

Or copy a formatted citation

@article{nicolas2025,
  title        = {{Artificial Intelligence (AI) in Accounting Education: A Scientometric Assessment}},
  author       = {Nicolas Mendes Barbosa et al.},
  journal      = {Journal of Information Systems and Technology Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4301/s1807-1775202522014},
}

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Artificial Intelligence (AI) in Accounting Education: A Scientometric Assessment

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.