Impacts of Edge AI/agentic AI on supply chain management and operations research

Abstract

Edge AI refers to the deployment and execution of artificial intelligence (AI) algorithms on decentralized, local computing devices (e.g., Internet of Things) rather than relying on centralized cloud‐based computing infrastructures. The literature has addressed the increasing importance of AI in supply chain and operations management (SCOM), specifically in learning‐based, generative, and agentic AI, as well as digital twins. However, the area of Edge AI has not yet received a theoretical framing and conceptualization in SCOM. In this paper, we discuss the impacts of Edge AI on SCOM. We begin with an analysis of AI in SCOM, focusing on learning‐based, generative, agentic AI, and digital twins. We then detail Edge AI's impacts on SCOM across Digital SCOR functions: orchestration, fulfillment and ordering, planning, sourcing, regeneration, synchronization, and transformation. We also analyze organizational transformations that Edge AI might trigger. Specifically, we discuss interactions of agentic AI and Edge AI, an integration of local and centralized decision‐making, and deployment scenarios of Edge AI use in SCOM, focusing on production planning and control, intralogistics, and supply chain resilience. Risks and challenges of the new technology are considered as well. Impacts of Edge AI on supply chain and operations research are discussed. We conclude that Edge AI is a crucial part of the unfolding Industry 6.0 revolution that, in combination with agentic AI, provides a technology to implement decentralized, autonomously planned and controlled supply chain, production, and logistics processes, materializing in Industry 6.0 with AI across all layers of value‐added chains.