• ISSN: 2301-3567 (Print), 2972-3981 (Online)
    • Abbreviated Title: J. Econ. Bus. Manag.
    • Frequency: Quarterly
    • DOI: 10.18178/JOEBM
    • Editor-in-Chief: Prof. Eunjin Hwang
    • Executive Editor: Ms. Fiona Chu
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HOME > Archive > 2026 > Volume 14 Number 3 (2026) >
JOEBM 2026 Vol.14(3): 269-270
DOI: 10.18178/joebm.2026.14.3.954

Research on the Impact of AI-Assisted Decision-Making on Enterprise Management Efficiency and Employee Collaborative Innovation Capability

Xiang Pan
Xiang Pan
Newyork University, 383 Lafayette Street, New York, NY 10003, USA
Email: xp2227@nyu.edu

Manuscript received June 21, 2026; accepted August 23, 2026; published September 23, 2026.

Abstract—With the development of the digital economy, Artificial Intelligence (AI) has gradually become a key pillar of corporate digital transformation. This paper examines the impact of AI on management efficiency and employees’ collaborative innovation capabilities from the perspectives of business management and organizational innovation, drawing on relevant corporate case studies. The research finds that AI can improve information processing efficiency, optimize decision-making processes, and promote knowledge sharing, thereby enhancing corporate management standards and innovation performance. However, its implementation still faces challenges such as data quality issues, algorithmic bias, insufficient digital literacy among employees, and information security concerns. To fully leverage its potential, enterprises should strengthen data governance and talent development while promoting the establishment of human-machine collaborative management models.

Keywords—Artificial Intelligence (AI), decision support, business management, collaborative innovation, digital transformation 

Cite: Xiang Pan, "Research on the Impact of AI-Assisted Decision-Making on Enterprise Management Efficiency and Employee Collaborative Innovation Capability," Journal of Economics, Business and Management, vol. 14, no. 3, pp. 269-270, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
 
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