How does AI boost C.H. Robinson's freight performance?

C.H. Robinson Worldwide Inc., the global logistics company headquartered in Eden Prairie, Minnesota, generated more than $17 billion in revenue last year. The company operates across freight forwarding, brokered ground transportation, and managed transportation services, making it one of the largest asset light logistics providers in the world.

Those scale advantages have mattered in a freight market that has remained difficult. While volumes and pricing have been under pressure across much of the industry, C.H. Robinson has delivered multiple strong quarters.

In the most recent quarter, income from operations increased 23 percent. Operating margin expanded by 680 basis points. Diluted earnings per share rose 68 percent, while adjusted diluted EPS increased 9 percent. Cash generated by operations climbed 65 percent. From an operational standpoint, daily shipments per person have increased 40 percent since 2022. Executives attribute these outcomes to what the company refers to as its Lean AI journey, an effort that combines lean operating principles with artificial intelligence deployed directly into day to day workflows.

Management has been explicit that isolating the impact of AI alone is difficult. Lean process improvements and technology adoption have progressed together. The company’s internal estimate is that the lean operating model itself has driven single digit productivity improvements, while the addition of agentic AI has enabled the organization to target double digit productivity gains in 2026.

Leadership describes the effort as far from complete. In truckload and less than truckload brokerage, executives say the company is in the third inning of its transformation. In global freight forwarding, they view the effort as being in the first inning. More than 30 AI agents have already been operationalized and scaled across the business, with further deployments planned.

Culture and Workforce Changes

For President and Chief Executive Officer Dave Bozeman, the operational changes have required a corresponding shift in how the company communicates with employees. Bozeman has said the company has been transparent about the implications of AI adoption. Within two years, some roles will no longer exist, while others will change materially in scope and responsibility. At the same time, the company has encouraged employees to adapt to what the future of work inside the organization will require.

That includes becoming comfortable using AI tools as well as learning lean methodologies such as Gemba walks, the five whys, and the Socratic method. Bozeman has emphasized that transparency has been central to keeping employees engaged during the transition.

He has also pointed to a competitive reality. People want to be part of a winning organization. Lean AI, he has said, has helped restore that sense of momentum internally.

The freight industry’s order to cash process remains heavily manual, with multiple handoffs across functions. According to Bozeman, those handoffs introduce waste that customers are not willing to pay for. One objective of AI adoption has been to reduce repetitive work that adds little value while improving output quality.

Automated quoting illustrates that approach. Previously, C.H. Robinson responded to approximately 65 percent of incoming requests for quotes. That meant a significant share of potential freight opportunities went unanswered. By combining generative AI with AI agents, the company now responds to 100 percent of quotes in its North American surface business. Quotes are delivered around the clock, typically within 30 seconds, and in a conversational format.

Bozeman has said the company was not consistently bringing its best work to the quoting process in the past. The move to full coverage has changed outcomes materially.

Financial Impact and Margin Expansion

Chief Financial Officer Damon Lee has described the company’s recent performance as unusual within the freight brokerage industry.

For years, conventional wisdom held that companies in the sector could focus either on growth or on profitability, but not both at the same time. Lee said C.H. Robinson has been able to outgrow the market while expanding margins for several consecutive quarters. The move from responding to 65 percent of quotes to responding to 100 percent has increased the number of opportunities the company can pursue. At the same time, win rates have improved.

Lee has attributed that improvement to the quality of AI assisted responses. Historically, a human operator might assemble a quote using five or six data points before responding. Today, AI agents working alongside employees can incorporate hundreds of data points to generate more precise and sophisticated quotes in real time.

The company is also using AI agents for revenue management. One such agent looks for price arbitrage opportunities across the shipping lanes the company serves. Lee has challenged the long held belief that gross margins in freight brokerage are structurally capped. He said the company has been expanding gross margins for nearly two years.

Technology Foundations

C.H. Robinson operates an asset light logistics model. It does not own a significant amount of transportation equipment. Instead, it connects shippers with a global network of contract carriers across truckload, less than truckload, intermodal rail, ocean, and air freight.

That model has always depended on technology. The company began building its Navisphere platform in 2012. An enhanced version with broader visibility and tracking capabilities was developed in 2016, in partnership with Microsoft, which served as both a technology partner and an early customer. Based on approximately 37 million shipments booked each year, along with extensive data from bids the company does not win, management believes it has assembled the most comprehensive dataset in the freight industry. That data is clean, contextualized, and embedded directly into operating workflows.

The company employs roughly 450 engineers. Many have deep domain expertise in freight and logistics. Executives say that knowledge allows C.H. Robinson to move from concept to deployment quickly, without relying heavily on system integrators that require lengthy knowledge transfer. The company does not operate separate innovation labs or centers of excellence focused on emerging technologies. Leadership has described the absence of exploratory spending as a discipline that accelerates execution.

Two years ago, leadership challenged the technology organization to find ways to improve performance across both strong and weak freight markets while expanding margins and gaining share. According to Lee, the team initially acknowledged uncertainty, then returned within weeks identifying agentic AI as the next step.

From that point, operational deployment took roughly 30 to 45 days. Scaling new concepts typically takes 12 to 18 months. Lee has described the company’s productivity improvements as occurring in waves, first from lean processes, then from generative AI, and now from agentic systems.

C.H. Robinson Worldwide Inc. serves more than 15,000 customers and works with approximately 200,000 carriers globally. The company earns most of its revenue from transaction based gross profit on brokerage services, supplemented by customs brokerage, warehousing, managed transportation services, and technology subscriptions tied to Navisphere.

Operations are organized into two primary segments. North American surface transportation accounts for roughly 70 percent of revenue and focuses on truckload and less than truckload brokerage. Global forwarding manages cross border ocean, air, and customs services. Executives acknowledge that competitors can adopt similar AI technologies. However, they argue that replicating the company’s operating model, data scale, engineering capability, and execution speed simultaneously is difficult.

As Lee has said, it is not a single advantage but multiple ones working together.