Third-Party Logistics Providers Deploy Autonomous AI Agents to Handle Millions of Tasks
Freight brokers and contract logistics companies are moving beyond AI tools that analyze data to systems that act on it independently. Agentic AI - software that makes decisions and executes workflows without human intervention - is now automating processes that previously required hours or days to complete.
C.H. Robinson, the largest freight broker in North America, has built and deployed more than 30 AI agents that handle millions of shipping tasks. These agents price quotes, process orders, match freight to capacity, schedule appointments, track shipments and handle invoicing - all in seconds.
The automation rates tell the story. Earlier AI systems hit a ceiling around 50%-60% automation before limitations became apparent. AI agents routinely push past 90%, according to Mark Albrecht, vice president of artificial intelligence and enterprise strategy at C.H. Robinson.
"With agentic systems, we've routinely been able to break through the 90% automation level," Albrecht said. "That's why we're so focused on automating every tactical step we can from quote to cash."
Shifting Work Away From Routine Tasks
DHL Supply Chain partnered with startup HappyRobot to deploy AI agents that handle phone calls, emails and appointment scheduling. The company identified a specific pain point: workers spent time on calls to schedule warehouse appointments and driver follow-ups.
"It was soul-crushing work," said Jennifer Miller, vice president of integrated transportation at DHL Supply Chain. "Nobody wanted to make the phone calls. Nobody wanted to do this work. It just was not a value-added or rewarding part of their day."
Automating routine interactions frees employees to focus on exceptions - the unusual cases that fall outside standard workflows. DHL's workers now manage complex problems rather than executing basic transactions.
Pablo Palafox, HappyRobot's co-founder and CEO, said the agents can "plan, they can predict, and they can also raise their hand and ask for help from humans when they don't know how to solve the problem."
Christophe Theys, DHL Supply Chain's global head of AI, data and analytics, emphasized the distinction: "What we are doing is automating the manual, repetitive tasks in the job so that people can focus on more meaningful activities."
A Different Kind of AI
The shift to agentic AI represents a fundamental change in how software operates. Earlier systems - including generative AI like ChatGPT - remained reactive. Users asked questions; the system responded.
Agentic AI works differently. The systems reason through problems, make plans and decide their own workflows. They initiate action rather than wait for instructions.
"We are going from computer-aided work, where software digitized a process but a person operated the software, to agentic AI, where AI does the work and decides the workflow," Albrecht said.
New Roles Emerging
As AI agents handle tactical work, new positions are appearing in logistics operations. Managers will oversee teams of AI agents, orchestrating their work across different functions.
Miller expects the technology to accelerate decision-making across supply chains. "This is going to enable our supply chain, the data within our supply chain and the decision-making to move much faster than it does today," she said.
She added that faster operations should create space for employees to focus on customer relationships. "I genuinely hope that it will allow our people to focus on relationships with our customers."
Miller cautioned against waiting for perfect implementations. "We'll always have exceptions. Your data will always have pieces that you need to update. Do not let that stop you from taking that first step, because the value you can see on the back end is well worth the work."
For operations professionals, understanding how agentic AI reshapes workflows is becoming essential. An AI learning path for operations managers covers process optimization and supply chain automation in detail. You can also explore AI agents and automation more broadly to understand how autonomous systems fit into logistics operations.
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