Supply Chain Management Review

Manufacturing is entering a pivotal period as artificial intelligence, workforce shortages and renewed government interest in domestic production reshape how companies think about technology investments, according to QAD CEO Sanjay Brahmawar.

Ask a demand planning leader how often their statistical models get reviewed and recalibrated across the full item portfolio. The honest answer, in most organizations, is seldom. Some high-priority SKUs get regular attention. All the rest is based on whatever configuration was set up at implementation, gradually drifting out of alignment as markets shift and portfolios change. This is not a failure in effort. It’s not structurally possible.

Technology matters, but execution matters even more. That philosophy defines the 2026 NextGen Supply Chain Conference, where two of the world’s leading supply chain organizations will be recognized during the annual NextGen Supply Chain End User Awards for transforming operations through artificial intelligence, automation and operational excellence.

Supply chain AI is generating significant attention, and for good reason. Demand forecasting, supplier risk scoring, logistics optimization, inventory positioning, and procurement automation all benefit from the pattern-recognition and prediction capabilities that modern AI systems bring. Most of the early returns are real. What is less visible is the infrastructure that AI supply chain systems actually run on. Not the models, which receive most of the investment and attention.

When Jackie Zhu took over Schneider Electric’s North American Supply Chain earlier this year, he stepped into one of the industry’s most demanding leadership roles. Schneider Electric has topped Gartner’s Supply Chain Top 25 rankings for four consecutive years, earning global recognition for operational excellence, innovation and execution. For Zhu, the promotion wasn’t simply the culmination of more than two decades at Schneider Electric.

Editor’s note: This article first appeared on the Digital Supply Chain Institute website and is being republished here with permission. You can read the original article here. Supply chains have always evolved in response to new technologies, market disruptions, and changing customer expectations. Today, artificial intelligence (AI) and agentic AI represent another significant inflection point.

AI has created a new supply chain constraint hiding in plain sight: memory. The same DRAM and NAND components that power laptops, servers, storage arrays, smartphones, smart devices and networking equipment are now being pulled aggressively into AI data centers. As demand surges, memory prices have climbed sharply, putting pressure on enterprise technology budgets and procurement plans.

Innovation doesn’t happen in a laboratory. It happens when new ideas solve real business problems. That philosophy sits at the heart of the 2026 NextGen Supply Chain Conference, where three of the industry’s most innovative technology companies will be recognized during the annual NextGen Supply Chain Solution Provider Awards.

Rebecca Fannin and Rosemary Coates, Executive Director of the Reshoring Institute, discuss the technology race in China in this installment of the Frictionless Supply Chain. Fannin is a journalist, CNBC special contributor, and author of five books. She writes about technology, first in Asia and then in the Heartland of America, and now back to China.

There is little debate that trucks are critical in moving the goods that we need across the final pathways of supply chain journeys that often begin with air, sea, and rail transportation. Truckers face long hours behind the wheel, and don’t have enough safe places to pull over and park for rest stops as I reported in one of my own newsletters several years ago. Truck drivers really do deserve to be paid appropriately for the vital service that they provide.