Artificial Intelligence and Accounting Profession Restructuring: Empirical Evidence from China’s Top 100 Accounting Firms
- DOI
- 10.2991/978-2-38476-456-3_12How to use a DOI?
- Keywords
- artificial intelligence; accounting profession restructuring; technological substitution; employment impact; skill transition
- Abstract
While artificial intelligence (AI) enhances accounting efficiency, it simultaneously exerts substitution pressure on traditional accounting roles. As intelligent technologies deepen their penetration into the accounting domain, the risk of automation replacing basic accounting positions rises significantly. To investigate AI’s restructuring effects on the accounting profession, this study analyzes empirical data from China’s top 100 accounting firms (2020–2023). The findings reveal that AI adoption intensifies role transition pressures for accounting professionals. However, firm size and operational complexity mitigate technological substitution, while highly specialized accountants demonstrate greater adaptability in functional transitions. By elucidating AI’s impact mechanisms, this research provides empirical insights for skill upgrading and career development pathways in the accounting profession.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qiufei Wang AU - Yuxin Shi AU - Xintong Zhang PY - 2025 DA - 2025/08/25 TI - Artificial Intelligence and Accounting Profession Restructuring: Empirical Evidence from China’s Top 100 Accounting Firms BT - Proceedings of the 5th International Conference on New Computational Social Science (ICNCSS 2025) PB - Atlantis Press SP - 104 EP - 110 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-456-3_12 DO - 10.2991/978-2-38476-456-3_12 ID - Wang2025 ER -