CHRWC.H. Robinson Worldwide, Inc.

“So this year, we've committed to double-digit productivity across the enterprise, right? So both NAST and our Global Forwarding businesses. We've also commented that, that will be over-indexed to the second half of the year. And the way we think about productivity going forward, just to remind the audience is we've committed to single-digit productivity every year regardless of circumstances, right? So our operating model will generate productivity in the single digits, mid-single digits every single year. And then years like 2025 and 2026, where we have waves of innovation, so whether that be Gen AI adoption, agentic AI adoption, then we're committing to double-digit productivity when you compound those waves of innovation with baseline continuous improvement.”

“Across our NAST business, we're also making smarter use of our proprietary digital capabilities and getting actionable data and AI-powered tools into the hands of our freight experts faster, enabling them to make better decisions and to capture the optimal freight for us. These digital capabilities also enabled us to continue delivering double-digit productivity increases in NAST in Q1. Since the end of 2022, we have delivered a more than 50% increase in shipments per person per day, and this is measured across the entirety of our NAST organization.”

“This includes an expectation that we will generate double-digit productivity improvements in both NAST and Global Forwarding in 2026 as we continue to implement agentic AI solutions across our quote-to-cash lifecycle of an order. As we have stated previously, we expect these productivity improvements to be over-indexed to the second half of 2026”

“At the center of these efforts is our lean AI strategy, which combines our lean operating model with deep industry expertise and our proprietary custom-built AI agents embedded directly into the workflows within our quote-to-cash lifecycle. This strategy enables us to automate, scale and execute in a sustainable and repeatable way without letting external narratives blur the difference between perception and reality. We take a highly focused and disciplined approach to AI deployment, and there is no hobby AI at Robinson. We deploy AI where it delivers real-world results and measurable outcomes that show up in our P&L.”

“Through our human-in-the-loop process and extensive instrumentation, we collect institutional knowledge from workflows and tribal knowledge from our freight experts into a context layer that enables our AI agents to execute and continuously improve alongside our expert logisticians. In effect, our people teach our AI agents in the same way they would train a new operations employee. Routine work can then be executed autonomously, allowing our teams to handle nonroutine surges in volume and higher value, more strategic activities for our customers.”

“Our data and context advantage spans multiple modes such as dry van, flatbed, temp control, ocean and air. They also span multiple services such as short-haul, drop trailer, cross-border, expedited and customs as well as multiple geographies, customers and lanes. This level of granular disaggregated data cannot be purchased. And this depth of data, such as data on individual warehouses enables us to understand price and cost dynamics better than anyone in the industry.”

“In the AI ecosystem, there are broadly 3 layers. At the foundation is infrastructure, which provides compute and storage. Above that are AI models, which are increasingly accessible to everyone. Neither of these layers provides a durable competitive moat. The real differentiation and advantage exists at the third layer, which is the application layer. At C.H. Robinson, we own our application layer.”

“Economically, this model scales efficiently. After the initial build and implementation, our marginal costs are very low. The ongoing costs are primarily tied to AI token usage rather than having to pay by transaction to a Software-as-a-Service provider. So owning the technology and engineering it in such a way that we have a scalable model is a critical component to widening our competitive moat.”

“With more than 450 in-house engineers and data scientists who have domain expertise and deeply understand our business, we're able to deploy agents faster and with greater control than a buy and integrate model that relies on stitching together third-party solutions that are generic and lack the data set in context that represent the scale, complexity and nuance of our business and the industry.”

“with our Lean AI disciplines now, our tech being in our people's hands faster, they're able to see where the supply chains of our customers are having breaking points, where the health of that supply chain is impacted. And then we're able to have conversations with customers where we can make disciplined decisions together”

“For example, think about appointment automation and the breadth of customers, freight dimensions and dock management systems we deal with. Every one of these customers, dimensions and locations has policies and nuances that are known to the appointment agent by way of an engineered context layer.”

“This is the Lean AI strategy at work, and we reaffirm our 2026 operating income target that we raised in October of last year.”

“our ability to consistently outperform over the last 2-plus years is a result of focusing on controlling what we can control and the strength of our lean AI strategy. Lean AI is our unique disciplined approach to AI innovation that is transforming supply chains. It combines the principles of our Robinson operating model, rooted in lean methodology with the power of custom-built AI and the expertise of our people to maximize value, minimize waste, and drive better outcomes for customers and carriers.”

“Agentic AI operates with a degree of autonomy and unpredictability, making its progress nonlinear and requiring ongoing human-in-the-loop oversight as it advances through cycles of progress and retrenchment. Our Lean AI process of discovering, learning and building where missteps and resulting learnings are milestones is not only necessary, but is the best path to uncover what truly works.”

“we're actively deploying the same playbook that we use in NAST over in Global Forwarding. You'll start to see more of that kind of kick in the second half of this year. And just like NAST, you've seen the journey over the past few years, we've got a lot of runway in Global Forwarding.”

“Our fleet of AI agents is growing quickly as we continue to pioneer new ways to automate manual tasks and supercharge our industry-leading freight experts to solve for complexity and deliver high-quality service and outcomes to our customers and carriers.”

“our model with an industry-leading cost to serve is highly scalable, and we expect it will continue to improve further as we continue to harness the evolving power of AI to drive automation across the quote-to-cash lifecycle of a load.”

“we've automated only a fraction of the hundreds of processes and subprocesses that exist across the quote-to-cash lifecycle of an order.”

“Significant runway exists as we continue to deepen the lean mindset and scale custom-built AI agents across the enterprise.”

“I'm proud of the progress we've made collectively to transform C.H. Robinson into the global leader in Lean AI supply chains. With our lean operating model, our commitment to continuous improvement and our AI innovation is at the core of our transformation, I continue to be even more excited about what we believe we can deliver in the coming years.”