Generative artificial intelligence and managerial cognition in turbulent supply chains: a real-time empirical analysis

Generative artificial intelligence (GenAI) promises to transform supply chain disruption management, yet its cognitive benefits and associated governance tensions remain insufficiently understood. This study conceptualises and empirically examines a cognitive paradox whereby GenAI accelerates managerial sensemaking, expands response options, and facilitates adaptive reframing while increasing verification demands, accountability uncertainty, and coordination difficulties. Using a scenario-based mixed-methods design, the research integrates an experiment with 200 senior supply chain managers randomly assigned to GenAI-supported and unsupported decision environments and 25 executive interviews. The study examines cognitive agility, operationalised through rapid reframing, information integration, and evaluative flexibility, as the managerial mechanism linking GenAI support to disruption-response effectiveness. Experimental findings associate GenAI support with greater cognitive agility and improved decision accuracy, adaptability, and timeliness. Exploratory Bayesian network analysis identifies complementary probabilistic dependencies without establishing causality. Qualitative evidence demonstrates that these benefits depend on data integration, verification practices, calibrated trust, managerial competence, and explicit decision rights. The study contributes to supply chain scholarship by establishing cognitive agility as a microfoundation of GenAI-enabled disruption response and identifying governance maturity as a boundary condition distinguishing cognitive augmentation from accelerated error, accountability ambiguity, and coordination failure.