Proceedings of the 2025 International Conference on Financial Innovation and Marketing Management (FIMM 2025)

Research on Employee Skill Remodeling and Career Development Path of Enterprises in the Era of Artificial Intelligence

Authors
Mingchen Xu1, *
1School of Economics and Management, Northeast Normal University, Changchun, 130024, China
*Corresponding author. Email: xumc333@nenu.edu.cn
Corresponding Author
Mingchen Xu
Available Online 3 November 2025.
DOI
10.2991/978-94-6463-874-5_144How to use a DOI?
Keywords
Artificial Intelligence; Skill Reshaping; Career Paths; Human-Machine Collaboration; Employment Polarization
Abstract

The rapid evolution of artificial intelligence (AI) technology has had a multidimensional and dynamic impact on the global labor market, replacing low and middle-skill jobs through automation, as well as giving rise to emerging occupations and exacerbating structural shifts in skill demand. This study focuses on the interaction between employee skill reshaping and career development paths in enterprises in the era of AI and systematically reveals the disruptive impact of technological advancements on job competencies through literature analysis, empirical research, and industry case studies. It is found that AI technology promotes the transformation of skill demand from Programmed Operation to Data-Driven and Composite Data-Driven, and human-computer collaboration has become the core path of ability upgrading; the career development path presents the trend of vertical promotion complexity and horizontal flow innovation, and the personalized design needs to balance the algorithmic efficiency and occupational autonomy; there is a bi-directional interactive relationship between skill remodeling and career path, and the skill upgrading promotes the career transformation, while the career goal inversely guides the career development path. There is a two-way interaction between skill remodeling and career paths, with skill upgrading promoting career transformation and career goals reversing the direction of skill investment. The study further points out that in the future, it is necessary to deepen the analysis of micro-mechanisms, incorporate ethical considerations, and explore the path of collaboration between government and enterprises, to address the challenges of algorithmic bias and skill mismatch.

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.

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Volume Title
Proceedings of the 2025 International Conference on Financial Innovation and Marketing Management (FIMM 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
3 November 2025
ISBN
978-94-6463-874-5
ISSN
2352-5428
DOI
10.2991/978-94-6463-874-5_144How to use a DOI?
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  - Mingchen Xu
PY  - 2025
DA  - 2025/11/03
TI  - Research on Employee Skill Remodeling and Career Development Path of Enterprises in the Era of Artificial Intelligence
BT  - Proceedings of the 2025 International Conference on Financial Innovation and Marketing Management (FIMM 2025)
PB  - Atlantis Press
SP  - 1273
EP  - 1281
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-874-5_144
DO  - 10.2991/978-94-6463-874-5_144
ID  - Xu2025
ER  -