| Issue |
SHS Web Conf.
Volume 225, 2025
2025 3rd International Conference on Financial Management and the Digital Economy (ICFMDE 2025)
|
|
|---|---|---|
| Article Number | 01032 | |
| Number of page(s) | 6 | |
| Section | Digital Economics & Behavior | |
| DOI | https://doi.org/10.1051/shsconf/202522501032 | |
| Published online | 13 November 2025 | |
The Impact of Artificial Intelligence on the Allocation of Financial Personnel in Enterprises - Taking Deloitte as an Example
Chengyi College, Jimei University, Xiamen, China
* Corresponding author: 3221003623@stu.fjmu.edu.cn
With the rapid development of artificial intelligence technology, its application in the field of enterprise financial management is becoming increasingly widespread, which has had a profound impact on the allocation of financial personnel. This article takes Deloitte’s financial robots as a starting point to explore in depth how artificial intelligence can change the allocation pattern of financial personnel in enterprises. By analyzing the functional characteristics and application scenarios of Deloitte’s financial robots, combined with relevant theories and practical cases, this study investigates the impact of artificial intelligence on basic financial positions, managerial financial positions, and the overall structure of financial teams, revealing the phenomena of job substitution, functional transformation, team restructuring, and so on that it brings. At the same time, in response to the challenges faced by financial personnel allocation in 6555863the context of artificial intelligence, strategies for enterprises and financial personnel are proposed, aiming to provide theoretical support and practical guidance for enterprises to optimize financial personnel allocation, improve financial management efficiency, and promote the transformation and upgrading of financial management in the era of artificial intelligence.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

