From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration

Yifan Liu

doi:10.47297/taposatWSP2633-456931.20250612

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From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration

6卷第12期

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From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration
From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration
School of Management, Beijing Institute of Technology, Beijing, 100081, China
2025年6卷第12期页码：146-149
纸质出版：2025-12-30
DOI：10.47297/taposatWSP2633-456931.20250612
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Yifan Liu. (2025). From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration. 科技理论与实践（英文版）, 6(12), 146-149.

Liu Yifan.From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration[J].Theory and Practice of Science and Technology,2025,06(12):146-149.
Yifan Liu. (2025). From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration. 科技理论与实践（英文版）, 6(12), 146-149. DOI： 10.47297/taposatWSP2633-456931.20250612.

Liu Yifan.From Framework to Implementation: Practical Paths and In-depth Breakthroughs in the Integration of AI and MIS for Business Administration[J].Theory and Practice of Science and Technology,2025,06(12):146-149. DOI： 10.47297/taposatWSP2633-456931.20250612.

摘要

Abstract

Based on the theoretical framework of "AI Technology - MIS Support - Business Administration Optimization" established in previous studies

this paper explores the practical implementation dilemmas in the integration of Artificial Intelligence (AI) and Management Information Systems (MIS) within enterprises. It proposes differentiated implementation paths matching enterprise scales and industry characteristics

and designs customized solutions for core issues including data privacy

algorithmic bias

and the technology-business disconnect

drawing on specific enterprise cases. This research aims to narrow the gap between theoretical research and practical application

and provide guiding principles for enterprises to realize technological empowerment in their transformation processes.

关键词

Keywords

references

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McKinsey & Company. (2025). Global Survey on AI-MIS Integration: ROI Drivers and Barriers. Shanghai.

Zhang, X., & Watson, R. T. (2024). Federated Learning for Secure Data Sharing in MIS.

Wang, Y., & Chen, W. (2025). Generative AI and MIS Synergy: Automating Financial Reporting in Retail Enterprises. Supply Chain Management: An International Journal, 30(3), 89-107.

van der Aalst, W. M. P. (2023). Business Process Reengineering with AI-Enhanced MIS: A Methodology for Large Enterprises. IEEE Transactions on Engineering Management, 70(4), 1289-1302.

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Gupta, A., & George, J. F. (2025). Data Privacy Compliance in AI-Driven MIS: A Global Regulatory Perspective. Journal of Management Information Systems, 42(1), 210-245.

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