At the recent SMC3 Jump Start conference, Mark Albrecht, vice president of artificial intelligence and enterprise strategy at C.H. Robinson, provided a detailed overview of how artificial intelligence (AI) is transforming logistics operations. Albrecht outlined how the industry is moving beyond traditional software-driven workflows toward a new era of agentic AI.
Albrecht described his role as “looking around corners”—tracking long-term technology megatrends and aligning them with business strategy. Today, he sees logistics at a critical inflection point. For years, he said, the industry has relied on computer-aided work, in which software digitized processes, but humans remained the logical engine. Transportation management systems and ERPs streamlined operations, yet still required people to define workflows and make decisions.
That model, Albrecht said, is now being disrupted by advances in general-purpose AI. As an example, he said that history offers clear parallels: the internal combustion engine reshaped cities and travel; and the electric motor transformed factory work. “When foundational technologies change, businesses must adapt,” he said. “AI represents that kind of shift, moving logistics from predefined workflows to agentic systems capable of deciding how work gets done.”
Earlier forms of AI supported this computer-aided model, continued Albrecht, adding that machine learning excelled at pattern recognition, enabling forecasting and dynamic pricing, but it did not alter the underlying workflow. Even the rise of large language models in 2022, while groundbreaking, produced largely reactive tools, as humans still provided the logic and sequencing.
Agentic AI changes that dynamic, according to Albrecht, because these systems can reason, determine next steps, and execute tasks independently—requiring a new kind of leadership.
Visionary leaders focus first on high-impact problems with clear return on investment—what he calls “not hobby AI.” They also recognize the importance of capturing the “why” behind decisions. “Traditional systems log actions, but they don’t record reasoning,” he said.
For AI agents to perform effectively, Albrecht noted that organizations must begin collecting and managing that reasoning data.
This evolution also reshapes organizational structures. As AI agents take over tactical tasks, Albrecht expects companies to move from pyramid-shaped organizations to diamond-shaped ones. In this model, fewer employees focus on execution, while more oversee AI agents, conduct higher-level reviews, and concentrate on strategy and value-added work.
According to Albrecht, C.H. Robinson is already seeing measurable results from this approach. One of the most immediate benefits has been simpler digital integration. Traditional EDI connections are complex, expensive, and difficult for smaller shippers to maintain.
“Agentic AI allows customers to interact through basic tools like e-mail while still receiving a fully digital experience,” said Albrecht. “E-mail-based quoting enables customers to request pricing in natural language, which AI converts into structured data and processes instantly—often helping customers avoid costly last-minute shipping premiums.”
Another major advantage is durability. Previous automation efforts frequently broke when document formats changed or edge cases emerged, requiring constant engineering support.
Agentic AI reasons from first principles, allowing it to interpret unfamiliar documents, extract relevant data, and complete workflows without manual intervention. This capability has increased automation rates from a traditional ceiling of 50% to 60% to more than 90%, enabling faster, around-the-clock processing in just-in-time supply chains.
When it comes to prioritizing AI investments amid competing customer demands and legacy systems, Albrecht emphasizes discipline. “You can’t scale chaos,” he noted, adding that C.H. Robinson first focused on strengthening its digital operating model—particularly the quote-to-cash process that powers the business. By stabilizing, standardizing, and scaling these core workflows, the company created a foundation for sustainable growth. AI investments followed a Lean mindset: stabilize, standardize, then scale.
For logistics organizations navigating similar challenges, Albrecht’s message is clear. Agentic AI is not simply another technology upgrade—it represents a fundamental shift in how work gets done. Companies that recognize and adapt to this new arc early will be best positioned to lead the industry forward.
