AI-driven forecasting only delivers real business value when organizations rigorously measure forecast value add (FVA) to ensure every model, agent, and human intervention improves operational decision-making.
Warehouse physical AI is closing the long-standing gap between digital systems and on-the-ground operations by passively capturing real-time inventory data, enabling higher accuracy, improved OTIF performance, and more efficient labor utilization without heavy capital investment.
Thursday, March 19, 2026 · Pierfrancesco Manenti, VP Analyst, Gartner Supply Chain Practice
AI is enabling CSCOs to shift from reactive cost cutting to proactive, data-driven cost management by uncovering hidden cost drivers, optimizing decisions in real time, and modeling financial trade-offs across the supply chain.
Agentic AI is transforming supply chains from deterministic, rule-based systems into adaptive, insight-driven networks that prioritize real-time decision-making, root-cause analysis, and capital-efficient innovation.
Supply chains are facing accelerating disruption, and companies must strategically adopt automation and emerging technologies to stay resilient, efficient, and prepared for what’s next.
Monday, March 16, 2026 · Eva Ponce, Vi Duong and Nic Holwerda
Dynamic Multi-Echelon Inventory Optimization enables supply chain leaders to balance service levels and working capital by optimizing inventory across the entire network rather than individual locations.
Procter & Gamble’s One Supply Chain strategy is an example of how aligning operations, forecasting, logistics, and supplier collaboration around the “Perfect Order” framework enables companies to deliver the right product, at the right time and cost, while turning…
True supply chain visibility in 2026 depends less on tracking shipments and more on synchronizing data across systems, ensuring a trusted single source of truth, and building AI-driven decision tools on high-quality, interoperable freight data.
Thursday, March 12, 2026 · Andrew Byer and Mike Dobslaw
Balancing demand and supply in supply chain planning means aligning demand forecasts with production, inventory, and distribution capabilities so companies can meet customer needs efficiently without costly operational disruptions.
Despite shifting headlines in the freight market, cargo theft, fraudulent carriers, regulatory enforcement, and tightening capacity are quietly increasing transportation risk, making continuous carrier vetting, human oversight, and proactive risk management essential for…
While enthusiasm for generative AI in supply chains is high, most companies remain trapped in pilot programs because successful deployment requires workflow-level problem definition, embedded agents, and disciplined governance rather than simply applying new AI models.
Pharmaceutical supply chains are among the most complex in the world, combining global sourcing dependencies, strict regulatory oversight, temperature-controlled logistics, and geopolitical and cybersecurity risks that make planning, manufacturing, and distribution far more…
Immersive, industry-embedded supply chain projects place students inside real operating systems, helping them build stronger applied capabilities in lean thinking, process mapping, and operational analysis than traditional textbook case studies.
Wednesday, March 4, 2026 · Amanda Dyson, VP of marketing, FourKites
As AI agents increasingly automate supply chain execution, companies must redesign talent strategies to prioritize relationship management, critical thinking, and organizational influence rather than traditional process-based operational skills.
Tuesday, March 3, 2026 · Paul Hong, Doug Reinart, and Steve Miller
As volatility, digital acceleration, and cross-functional complexity intensify, the CSCO is evolving from operational leader to enterprise orchestrator, aligning finance, technology, and market strategy into a unified system of resilience and growth.
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