Hanjie Li, Mengmeng Liu, Pengfei Wang, Zhenwei Shi
Kangwon National Universit; Shandong Vocational Animal Science and Veterinary College; Weifang
Industrial Development Group Co., Ltd.; Yonsei University
Abstract：
Against the backdrop of heightened global economic uncertainty and the deepening of digital
transformation, decision-making methods and risk control mechanisms in the field of business administration are
undergoing profound changes. Traditional management decisions rely heavily on experiential judgment and
limited data analysis, often resulting in sluggish responses, information asymmetry, and insufficient risk
identification. The rapid development of Artificial Intelligence (AI) offers new possibilities for enhancing the
scientific rigor, agility, and foresight of business management. This paper examines the connotations and
pathways of AI empowerment, exploring its mechanisms in improving decision-making efficiency and
strengthening risk control. Particular emphasis is placed on the application value of AI in data mining, predictive
modeling, risk warning, intelligent decision optimization, and organizational governance. Through the analysis of
typical cases and scenarios, the study demonstrates that AI significantly shortens decision-making cycles in
complex environments, improves rationality in resource allocation, and effectively identifies potential risks, thereby enabling enterprises to maintain steady growth amidst uncertainty. The paper also reflects on the
inherent limitations of AI-empowered decision-making, including data bias, algorithmic opacity, ethical risks, and
challenges to managerial competence. Based on these insights, several countermeasures are proposed:
strengthening data governance systems, fostering human-AI collaborative decision-making mechanisms, enhancing the transparency of risk management models, and improving legal and ethical frameworks. The
findings of this study contribute to the modernization of management theory while also providing practical
guidance for enterprises.
Key Words：
Artificial Intelligence; business administration; decision-making efficiency; risk control; human-AI
collaboration
