Agentic AI-Enabled Big Data Orchestration for Cloud-Native Supply Chain Optimization in National Food Service Wholesale Products

Abstract

Undertaking empirical research in the food service wholesale domain of national-scale (US) supply chains, this work focuses on agentic AI-enabled orchestration for cloud-native supply-chain optimization. Problems derive from heavyweight supply chains serving capital-­ and land-intensive industries, such as agriculture and forestry, with demand patterns poorly driven by underlying ecosystems yet bolstered by growth dynamics in surrounding food service markets. Discussion is framed around orchestration of big data pipelines for supply-chain analytics and decision support. An extended tenet of adaptive governance empowers business-level stakeholders to integrate data sources and keep their national networks in sync. Contributions articulate core supply-chain requirements and actors’ analytical needs, introduce a methodological framework for designing data-ingestion and orchestration mechanisms, and recommend a reference system architecture that generalizes to other national-scale economies. Spanning compliance, quality, safety, and cybersecurity, these considerations together speak to agentic AI’s accountability, transparency, and risk. The empirical core comprises synthesis case studies feeding into three use cases for cloud-enabled supply-chain dynamics: forecasting end-customer demand, integrating supplier inventories and resources, and optimizing transport. Even with only a few data sources, agentic AI-enhanced decision support promises genuine advantage: helping generate matching supplier networks and synchronizing transport operations not just for cost but also to mitigate product waste, quality loss, and spoilage. A supporting technical framework addresses the cloud-native supply-chain-analytics components of systems for national-scale economies—conducting core supply-chain planning in the food-service wholesale domain, such as forecasting, integrating supplier inventories, and synchronizing transport across capital-­ and land-intensive supply chains that depend on nature’s undulating growth cycle.