工作流程
相互依存
知识管理
交叉口(航空)
计算机科学
芯(光纤)
过程(计算)
人工智能应用
过程管理
人工智能
管理科学
基础(证据)
商业智能
管理
社会学
意会
核心竞争力
业务流程管理
有可能
双灵巧性
代表(政治)
实践共同体
业务流程
作者
Tinglong Dai,Jayashankar M. Swaminathan
标识
DOI:10.1177/10591478251412943
摘要
Artificial intelligence (AI) is poised to reshape operations across industries. Yet its real-world impact reveals a jagged and uneven implementation frontier. To make sense of this emerging landscape, we develop a foundational framework that synthesizes research and practice at the intersection of AI and Operations Management (OM), anchored in three interdependent pillars: (1) AI for OM, (2) OM for AI, and (3) Human–AI Interaction. First, AI for OM analyzes how AI enhances core operational processes, including design, procurement, production, and delivery. Second, OM for AI argues that scaling AI safely and effectively stands to benefit from core OM principles, including workflow design, capacity management, process control, drift detection, and continuous improvement, all of which are central to AI development and deployment. Third, Human–AI Interaction emphasizes the role of trust, incentives, and organizational design in mediating how humans and machines learn from and collaborate with each other. This triadic framework provides a foundation for organizing research on AI and OM and offers practical guidance for integrating AI into business and societal systems.
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