Artificial Intelligence Applications in Asset Management: Structure, Strategy, and Governance

Shuo Wen

doi:10.47297/taposatWSP2633-456918.20260701

PDF
Export
Share
Collection
Album

Artificial Intelligence Applications in Asset Management: Structure, Strategy, and Governance

Volume 7, Issue 1

Views: 0 Downloads: 0

Artificial Intelligence Applications in Asset Management: Structure, Strategy, and Governance
Artificial Intelligence Applications in Asset Management: Structure, Strategy, and Governance
University of Sanya, Saxo Fintech Business School, Sanya, Hainan, 572022, China
Vol. 7, Issue 1, Pages: 87-89(2026)
Published：30 January 2026
DOI：10.47297/taposatWSP2633-456918.20260701
Accepted：

Scan QR Code

Wen Shuo.Artificial Intelligence Applications in Asset Management: Structure, Strategy, and Governance[J].Theory and Practice of Science and Technology,2026,07(01):87-89.
DOI：

Wen Shuo.Artificial Intelligence Applications in Asset Management: Structure, Strategy, and Governance[J].Theory and Practice of Science and Technology,2026,07(01):87-89. DOI： 10.47297/taposatWSP2633-456918.20260701.

摘要

Abstract

This study examines artificial intelligence applications in asset management through analysis of 178 peer-reviewed studies and industry implementations. We identify six core domains: AI-driven portfolio management

financial forecasting

robo-advisory services

risk management

strategic decision-making

and adoption enablers. Research demonstrates that AI enhances operational efficiency while reconfiguring strategic practices within financial institutions. Key findings reveal successful AI implementation requires hybrid approaches combining machine intelligence with human expertise

particularly in portfolio management where pure algorithmic signals can increase trading costs. However

challenges including algorithmic opacity

ethical concerns

and talent shortages hinder widespread adoption. This framework provides guidance for practitioners

regulators

and researchers in leveraging AI for modern investment management.

关键词

Keywords

references

Mertzanis, C. (2025). Artificial intelligence and investment management: Structure, strategy, and governance. International Review of Financial Analysis, Volume 107, Article 104599.

SMU Cox School of Business. (2025). Are AI and Big Data Creating Competitive Advantages in the Asset Management Industry? Research findings on mutual fund AI adoption trends.

Hu, X., Rohrer, M., & Zhang, H. (2025). Active Machine Learning Based Trading and Mutual Fund Performance. Working paper, Cox School of Business, Southern Methodist University.

SMU Cox empirical methodology for measuring genuine AI adoption in asset management. (2025). Cox School of Business Research Publication.

Broadridge Financial Solutions. (2025). Practical AI Applications in Asset Management: From Front to Back Office. ICI Leadership Summit 2025 Presentation.

Prometheus Group. (2025). Real-World Applications of AI in Asset Management. GWOS-AI Platform Documentation and Case Studies.