This week’s installment of Supply Chain and Logistics news includes stories about record increases in oil prices, Rivian’s autonomous taxis, and much more. Firstly, the Trump administration has issued a 60-day waiver of the Jones Act, a century-old regulation that requires goods moved between US ports to be transported by US-built vessels, etc. Additionally, this week Uber & Rivian announced a partnership for Rivian to build 50,000 autonomous robotaxis by 2031 with over a billion dollars in investment from Uber. Schneider Electric and EcoVadis announced a partnership to target emissions in the health care sector. Lastly, DHL announces 10 warehousing sites to be used for data center manufacturing capacity, and Mind Robotics raises 100 million in series A funding.

Your Biggest Stories in Supply Chain and Logistics here:

Trump Administration Issues Pause on Century-old Maritime Law to Ease Oil Prices

The Trump administration has issued a 60-day waiver of the Jones Act. This century-old regulation typically requires goods moved between US ports to be carried on vessels that are US-built, US-owned, and US-crewed. However, with oil prices surging toward $100 a barrel due to escalating conflict in the Middle East, the suspension aims to ease logistics for vital commodities like oil, natural gas, and fertilizer. While the move is intended to lower costs at the pump and support farmers during the spring planting season, it has sparked a debate between those seeking immediate economic relief and domestic maritime unions concerned about the long-term impact on American shipping and labor.

Uber and Rivian Partner to Deploy up to 50,000 Fully Autonomous Robotaxis

Uber and Rivian have announced a massive strategic partnership that signals a major shift in the future of autonomous logistics and urban mobility. Under the terms of the deal, Uber is set to invest up to $1.25 billion in Rivian through 2031, a move specifically tied to the achievement of key autonomous performance milestones. The primary focus of this collaboration is the deployment of a specialized fleet of fully autonomous R2 robotaxis, with an initial order of 10,000 vehicles and an option to scale up to 50,000 units. From a supply chain perspective, this represents a significant commitment to vertical integration; Rivian is managing the end-to-end production of the vehicle, the compute stack, and the sensor suite, including its in-house RAP1 AI chips, while Uber provides the scaled platform for deployment. Commercial operations are slated to begin in San Francisco and Miami in 2028, eventually expanding to 25 cities globally by 2031.

Schneider Electric and EcoVadis Announce Partnership to Decarbonize Global Healthcare Supply Chains

Schneider Electric, a major player in the digital transformation of energy management and automation, and EcoVadis, a provider of business sustainability ratings, have announced a strategic partnership aimed at accelerating decarbonization within the healthcare industry. “Energize” is a collective initiative to engage pharmaceutical industry suppliers in climate action. The collaboration focuses on addressing Scope 3 emissions, those generated within a company’s value chain, which often represent the largest portion of a healthcare organization’s carbon footprint. By combining Schneider Electric’s expertise in energy procurement and sustainability consulting with EcoVadis’s supplier monitoring and rating platform, the partnership provides a structured pathway for pharmaceutical and medical device companies to transition their global suppliers toward renewable energy.

Mind Robotics, a Rivian spin-off, raises $500 million in Series A Funding

RJ Scaringe, CEO of Rivian, is positioning his new $2 billion spin-off, Mind Robotics, as a technological solution to the chronic shortage of manufacturing labor in the Western world. By developing a “foundation model” that acts as an industrial brain alongside specialized mechatronic bodies, the company aims to move beyond the rigid, fixed-motion plans of traditional robotics toward systems capable of human-like reasoning and adaptation. Scaringe emphasizes that while these machines must perform with human-level dexterity, they don’t necessarily need to be humanoid in form; instead, the focus is on creating a data-driven “flywheel” within Rivian’s own facilities to lower production costs and help domestic manufacturing remain globally competitive.

DHL Expands North American Logistics Infrastructure Amid Growing Global Demand for Data Center Logistics Services

DHL is significantly scaling its data center logistics (DCL) footprint in North America, announcing the addition of 10 dedicated sites totaling over seven million square feet of warehousing capacity. This expansion is a direct response to the explosive demand for AI-driven infrastructure and the specific needs of hyperscale and colocation data center operators. By offering specialized services like rack pre-configuration, white-glove handling of sensitive IT hardware, and warehouse-to-site transportation, DHL is positioning itself as an end-to-end partner in a sector where 85% of operators express a preference for a single logistics provider. This move not only addresses the logistical complexities of moving high-value components like GPUs and cooling systems across global borders but also underscores the critical role of integrated supply chains in maintaining the build speed of the digital backbone.

Song of the Week:

The post Supply Chain and Logistics News March 16th-19th 2026 appeared first on Logistics Viewpoints.

This first in a blog series offers a review of discussion that occurred during ARC Advisory Group’s 2026 Industry Leadership Forum. Specifically, it details a keynote conversation held with senior executives from Rolls-Royce, BTX Precision, and MxD.

The New Fabric of Demand: Modernizing Collaboration and Transparency for Real-Time Production

Industrial leaders have been talking about tearing down workflow and data silos for decades. Yet here we are again. For most, the reality is that most operations and supply chains today typically don’t indicate much progress. A few leaders have figured out how to use digital tools to scale and build pathways forward, a whopping 12.9% according to our latest data (yes, that’s sarcasm). However, even as they struggle to coordinate, orchestrate, and innovate across their operations and enterprise, much less tightly collaborate outside their four walls. In a digital world, this continued capability gap, the inability to closely link market signals to responsive production and external supply chains, is very quickly becoming a liability.

Recently, at the 30th Annual ARC Industry Leadership Forum in Orlando, I had the privilege of leading a keynote discussion entitled The New Fabric of Demand: Modernizing Collaboration and Transparency for Real-Time Production. As part of that, I moderated an excellent conversation that included Global Commodity Executive Greg Davidson of Rolls-Royce, CEO Berardino Baratta of MxD, and CRO Jamie Goettler of BTX Precision.

In this four-part series, we will explore that conversation fully, digging into how the “fabric of market demand” has fundamentally changed, and why structural modernization, both human and technological, is no longer just an option. It is an industrial imperative that will increasingly determine who wins in disrupted markets.

Why Legacy Workflow Will Actually Get Modernized

If we examine the present through the lens of the past, the fundamental laws of supply and demand haven’t really changed. What has changed is the hyperconnectivity of the world and our compressed time to both reward and volatility.

The hard truth is that legacy linear workflows simply do not work in hyperconnected, digitally-driven environments, which are non-linear by nature. As our industrial environments become more digital, they naturally open up countless new ways for how things can get done and how risk can enter the organization. As a result, disruption has shifted from a rare event to a fairly continuous and pervasive reality. In this new reality, responsiveness differentiates you from the competition, and lag time kills.

To survive and thrive in non-linear environments, tighter, integrated ecosystems are required, where silos are actively torn down or redesigned so that barriers to value can be continuously identified and quickly eliminated. At the core, this concept is unfolding around data access, contextualization, and sharing. It provides the urgency behind the need for building industrial data fabrics.

This rewiring certainly extends beyond operations and enterprise processes, enabling the entirety of the supply chain to be judged on its collective responsiveness to the market, all the way down to the individual company level. In this scenario, data can quickly point out laggards who limit value. As the orchestrators of these supply chains identify these limitations on value, they quickly break off and discard the connection and move on without these weak links.

Pillars of the New Fabric of Demand

To achieve necessary level of operational and supply chain responsiveness, the roles of every entity within an ecosystem must be rethought. In the subsequent three blogs of this series, we will take a deep dive into the three distinct pillars that make up this modern architecture, but I’ll begin by laying them out here:

The Market Signal is the catalyst of the entire ecosystem. It dictates the “what” and the “when,” defining what value, success and risk look like in real-time. In blog 2, I’ll explore how to move from reactive assumptions to proactively capturing the market signals that actually matter.
The Demand Architect is moving beyond traditional order-taking. The Demand Architect designs and orchestrates the ecosystem, aligning external partners as true extensions of the enterprise. In blog 3, I’ll discuss the structural agility required to lead this response, rather than just manage a process.
The Agile Partner is the engine of execution. The Agile Partner links supply chain dynamics directly to the shop floor, differentiating themselves through their responsiveness to the market signal. In the final blog in the series, I’ll tackle how data transparency and trust become technical requirements, not just buzzwords, without exposing mission-critical IP.

Building the Modern Industrial Enterprise

Legacy workflows cannot survive in a non-linear world. Industrial organizations must re-architect operations and ecosystems for real-time responsiveness and secure, transparent collaboration. To do so, they will need to:

Improve the measurement of responsiveness: Efficiency and margin-squeezing are important, but they aren’t game-changers. Your competitive edge now relies on how quickly you can adapt to market signals.
Embrace transparency over secrecy: Modern collaboration requires providing a contextualized “lens” into production status without compromising proprietary IP or cybersecurity. Industrial data fabrics are key.
As always, view technology as a tool, not an outcome: Industrial data fabrics are needed to break silos and AI to manage complexity and improve accuracy and speed of decisions. However, the age-old adage remains true. Just because you can apply AI to something doesn’t mean you should. It must be grounded in measurable Value on Investment (VOI), not just return.

The New Fabric of Demand Blog Series

This is the first in a series of four on The New Fabric of Demand: Modernizing Collaboration and Transparency for Real-Time Production. Over the coming days, I’ll publish a perspective from each of the three pillars of the new fabric of demand:

Pillar 1: The Market Signal
Pillar 2: The Demand Architect
Pillar 3: The Agile Partner

By Mike Guilfoyle, Vice President.

For more than two decades, Michael has assisted organizations, including numerous Fortune 500 companies, in identifying and capitalizing on growth opportunities and market disruption presented by the effects of digital economies, energy transition, and industrial sustainability on the energy, manufacturing, and technology industries.

The post How to Capitalize Quickly to Address Hyperconnected Industrial Demand appeared first on Logistics Viewpoints.

Descartes Systems Group (Nasdaq:DSGX) (TSX:DSG), the global leader in uniting logistics-intensive businesses in commerce, announced expanded artificial intelligence (AI) capabilities on its multimodal Global Logistics Network (GLN) with the introduction of Descartes MacroPoint™ OpsForce, a suite of AI agents designed to automate freight visibility workflows, maintain tracking continuity and improve execution across complex, inter-enterprise supply chains.

Built on the scale and real-time data of the GLN, OpsForce leverages trusted, clean and formatted network intelligence to power automated driver engagement, exception management and documentation workflows for shippers, brokers, carriers and logistics service providers. In just months, over 435,000 more drivers have been connected to the GLN through 720,000+ AI-powered driver outreaches. In addition, since first launched, OpsForce has helped our customers eliminate up to 100% of manual check calls and achieve, on average, a 30% increase in no-touch tracking automation, 1.5x productivity gains for tracking teams, and 15% faster settlement through automated proof of delivery (POD) capture.

“AI innovations in our real-time visibility solution are designed to improve accuracy and responsiveness across freight execution,” said Dan Cicerchi, General Manager, Transportation Management at Descartes. “Even with electronic logging devices (ELD), transportation management system (TMS) connections, and geofencing, brokers and shippers still face manual follow-ups, tracking drops, uncertain arrival events and missing documentation. By applying intelligent agents to these exception workflows, OpsForce eliminates repetitive tasks while connecting brokers and shippers to more carriers, improving data accuracy, strengthening customer satisfaction and accelerating order to cash cycles with no action required from their people.”

As part of the GLN, Descartes MacroPoint connects to hundreds of thousands of carriers and logistics service providers globally, along with millions of individual drivers to deliver real-time shipment visibility. When needed, the solution’s AI agents are automatically activated to:

Guide mobile app onboarding to expand tracking coverage

Restore tracking if it fails to start or stops unexpectedly

Confirm arrival and departure milestones when geofence data is uncertain

Collect missing proof-of-delivery documentation

By automating these exception-based workflows, OpsForce reduces manual check calls, increases no-touch tracking, and enhances tracking compliance against customer visibility mandates.

“As customers expand their own AI strategies, the need for large volumes of trusted, real-time inter-enterprise data becomes even more critical,” said Ken Wood, EVP Product Management at Descartes. “The GLN delivers that data at scale, connecting hundreds of thousands of trading partners and continuously processing real-world transactions to keep goods moving efficiently and securely. By combining agentic AI with the reach and collective intelligence of the GLN, we’re helping customers automate execution while strengthening the data foundation that powers smarter supply chain decisions.”

Learn more about Descartes’ transportation management solution suite, including Descartes MacroPoint OpsForce.

About Descartes

Descartes powers more responsive, efficient, secure and sustainable international and domestic supply chains by uniting logistics-intensive businesses on its Global Logistics Network (GLN). Shippers, carriers, and logistics service providers connect and collaborate on the GLN leveraging technology, data and AI to manage last mile deliveries, domestic and international shipments, transportation rating and payment, global trade research, customs compliance and a variety of regulatory processes. Learn more about Descartes (Nasdaq:DSGX) (TSX:DSG) at www.descartes.com and connect on LinkedIn and X.

Global Media Contact

Cara Strohack
Tel: 226-750-8050
cstrohack@descartes.com

The post Descartes Expands AI Innovation on Global Logistics Network with AI Agents for Freight Visibility appeared first on Logistics Viewpoints.