The final days of November 2025 demonstrate a critical inflection point in global logistics, where established models are being aggressively reevaluated and digital investment is shifting from simple visibility to true intelligence. While the rail giants BNSF and CSX are rebuilding foundational long-haul intermodal connectivity—a throwback to efficient network strategies—leading retailers like Kroger are radically pivoting away from costly, dedicated automation (Ocado CFCs) toward hybrid, asset-light fulfillment models. This complex landscape is further defined by the growing understanding that supply chain automation efforts fail without a unifying semantic layer to connect disparate data systems, underscoring the necessity of high-level Decision Intelligence. Ultimately, the industry’s path forward is being paved by massive commitments to next-generation AI infrastructure from tech leaders like NVIDIA and Microsoft, promising to finally deliver the high-performance computing required for real-time, context-aware orchestration.
BNSF and CSX Expand Their Intermodal Partnership Across the Midwest and Northeast
BNSF Railway and CSX Transportation just took another significant step in rebuilding long-haul rail intermodal in the United States. As of November 17, the two carriers have expanded their joint service to connect the West Coast with major inland hubs across the Midwest and Northeast. This expansion extends their earlier Southwest-to-Southeast partnership and reinforces a broader shift: railroads are once again leaning into cooperative interline and intermodal operations. For BNSF, the deal deepens its reach into dense consumer markets in the Northeast. For CSX, it opens up new access to West Coast import flows at a time when shippers continue to rebalance their operations between ports. Both carriers regain something that has steadily eroded over the last twenty years: true long-haul rail-to-rail intermodal connectivity.
Why Supply Chain Automation Fails Before It Even Starts
True supply chain automation often fails not at the technological level, but at the organizational one, trapped by fragmented data. Visibility alone is not enough; knowing where a shipment is does not equal understanding the full business impact of its delay across procurement, merchandising, and final delivery. To move beyond incremental time savings to significant financial returns, organizations must invest in a semantic layer—a unified, machine-readable understanding of all business objects. This shared context is what allows AI and automation tools to move beyond simple flagging and suggesting to actually orchestrating end-to-end responses, ensuring that systems communicate the purpose and consequences of every action, rather than just isolated status updates.
How Decision Intelligence Plays a Role in Todays Global Supply Chain
Aera Technology’s Decision Intelligence (DI) is a platform and approach that digitalizes, augments, and automates decision-making across an enterprise. “The automation of decision-making.” Aera’s decision intelligence (DI) is comprised of three pillars: automation, data & analytics, and artificial intelligence. Aera shared that its platform helped make 25 million decisions in 2024, and expects this year to surpass the last. Decision intelligence comprises six core competencies: data acquisition, data analysis with AI, simulations, decision recommendations, execution, and monitoring. Decision intelligence impacts supply chain, operations, logistics, procurement, sales, marketing, finance, and IT. In an era of constant disruptions and ever-shifting geopolitics, decision intelligence can equip companies with information and tools to navigate todays global supply chain.
NVIDIA, Microsoft, and Anthropic Realign AI Infrastructure. What It Means for Supply Chain Leaders
The recent realignment of AI infrastructure between NVIDIA, Microsoft, and Anthropic marks a pivotal moment for supply chain technology. With massive commitments to compute capacity and deeper hardware-model co-design, this shift directly addresses the past bottleneck of AI scarcity, ensuring supply chain leaders will have better access to the high-performance computing needed for complex, high-frequency workloads like daily scenario analysis and advanced digital twins. Crucially, the expansion of models like Anthropic’s Claude across all major cloud platforms—Azure, AWS, and Google Cloud—simplifies enterprise integration, allowing logistics teams to build a unified, powerful AI layer regardless of their hosting environment, thereby accelerating the deployment of next-generation, context-aware planning and multi-agent systems.
Kroger to Close 3 Automated Fulfillment Centers
In a strategic pivot to drive e-commerce profitability by an estimated $400 million in 2026, Kroger is course-correcting its logistics strategy by closing three automated Customer Fulfillment Centers (CFCs) developed with Ocado. This shift acknowledges that highly automated, dedicated facilities are not a one-size-fits-all solution, especially in lower-density markets. The retailer is now prioritizing a hybrid model that involves ramping up capital-light, in-store fulfillment and deepening reliance on third-party delivery partners like Instacart, DoorDash, and Uber to leverage existing store assets and focus on profitable sales growth and flexible delivery options for customers.
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