The Cognitive Supply Chain Data-Driven Resilience and AI augmented Decision-Making in Global Infrastructure Deployments
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V6I4P107Keywords:
Cognitive Supply Chain, Digital Infrastructure, Data Centers, Network Deployment, AI-Augmented Decision-Making, Multimodal Data Integration, Probabilistic Risk Propagation, Cognitive Digital Twin, Infrastructure Resilience, Predictive Analytics, Supply-Chain Intelligence, Telecom InfrastructureAbstract
The rapid expansion of global data-center regions, fiber backbones, submarine-cable systems, and edge-network clusters has exposed structural limits in traditional supply-chain models. These legacy systems built for predictable, linear manufacturing flows struggle to manage the volatility, interdependencies, and long-lead components that characterize modern digital-infrastructure deployments. Existing forecasting tools and operational platforms lack real-time visibility across procurement, logistics, engineering, and site-execution domains, resulting in delayed risk detection and fragmented decision-making. This paper introduces a Cognitive Supply Chain framework designed specifically for digital-infrastructure environments. The model integrates multimodal data, probabilistic risk propagation, AI-augmented decision pathways, and a cognitive digital twin to simulate deployment scenarios and anticipate disruptions. Through architectural analysis, implementation guidance, and a real-world case example, the paper demonstrates how cognitive decision systems can improve deployment accuracy, extend predictive lead time, and enhance resilience across multi-region infrastructure programs. The results highlight a path toward a more anticipatory and intelligence-driven supply chain capable of supporting the next decade of global digital-infrastructure growth.
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