Artificial Intelligence and Operations: A Foundational Framework of Emerging Research and Practice

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.

• 저널Production and Operations Management
• 토픽Big Data and Business Intelligence · Management Information Systems
• DOI10.1177/10591478251412943
• 저자Tinglong Dai, Jayashankar M. Swaminathan