This study examines how Generative Artificial Intelligence (GenAI) agents transform Operational Research (OR) practices in enterprise settings. Using a grounded approach based on 38 archival case studies across various industries, we investigate how organisations integrate GenAI agents to augment or automate core OR functions. We rely on dynamic capabilities and sociomateriality theories as the theoretical foundation. Our findings reveal that the main impacts of GenAI agents are operational efficiency transformation, augmented human capability, scalable intelligence at the edge, sociomaterial co-production in OR decision-making, and GenAI-agent-enabled dynamic capabilities in OR practice. We also proposed a typology of GenAI agent usage mapped to four strategic zones: traditional tool, basic automation, automated assistance, and assisted augmentation. While none of the implementations meet the criteria for Artificial General Intelligence (AGI), many illustrate the trajectory towards hybrid, context-aware, and generatively intelligent decision systems. This article contributes to the growing literature at the intersection of OR and AI by providing theoretical insights and practical guidance on how GenAI agents can transform OR practices. We propose a framework that links the degree of automation and augmentation to their functional impacts and discusses its implications for theory development and managerial action.
Wamba-Taguimdje et al. (Fri,) studied this question.