C.H. Robinson: How AI Agents Keep Freight Moving

The logistics industry faces a persistent less-than-truckload (LTL) problem that drains productivity: missed pickups. These failures ripple through networks, delay freight and trigger costly return trips. New AI deployments suggest the sector may be at an inflection point.

C.H. Robinson, the largest mover of LTL freight among North American third-party logistics providers, has rolled out AI agents that track missed pickups and apply advanced reasoning to keep freight moving. The system also captures data carriers are using to sharpen operations.

Early results are significant. The company reports automating 95% of missed-pickup checks, saving more than 350 hours of manual work per day. Shippers’ freight could move up to a day faster and unnecessary return trips to collect missed freight have dropped 42%.

AI adoption reshapes productivity metrics

These gains echo broader trends. PwC’s 2025 Global AI Jobs Barometer finds industries most exposed to AI - logistics among them - have seen productivity growth nearly quadruple, up 27% compared to sectors that have not adopted the technology.

But adoption alone is not enough. A McKinsey 2025 report notes that while 88% of organisations use AI, only 6% capture meaningful enterprise value.

These high performers redesign workflows rather than layering AI onto existing processes. The gap underscores a central challenge for logistics: value comes from reimagining operations, not just automating tasks.

Speed has also become decisive. According to Gartner, 90% of supply chain leaders now rank speed among their top three performance metrics.

Why LTL misses matter

LTL shipping is operationally intricate. One truck can carry freight from up to 20 shippers, with shipments consolidated and recombined through terminals. That complexity creates multiple points where pickups can be missed.

“A missed pickup isn’t just a minor inconvenience,” says Greg West, Vice President for LTL at C.H. Robinson.

“When a truck arrives and the freight or packaging isn’t ready, or the carrier couldn’t make it because they got stuck in traffic, it forces another truck to come back the next day. That might not even be our shipper’s freight, but it creates a domino effect for other freight that was supposed to get picked up and for all the other trucks down the line.”

At C.H. Robinson - managing 37 million shipments annually and US$23bn in freight - the new agents are resolving hundreds of shipments per day for more than 11,000 customers.

Two-agent system, faster resolutions

The deployment uses two AI agents working in tandem: one contacts carriers about missed pickups; the other determines next steps. Because the agents can make 100 calls and 100 decisions at the same time, issues can be resolved faster and freight can move sooner.

“Before this transformational tech, teams of people spent over half the day chasing missed pickups – manually checking carrier websites, making calls, recording updates and notifying customers,” adds Greg. “Now all that time and capacity aren’t being wasted, it keeps other shippers’ freight from getting delayed.”

Carriers are also using the resulting insights to improve electronic communications and optimise scheduling.

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Lean AI approach

Mark Albrecht, VP for AI at C.H. Robinson, describes the strategy as Lean AI.

"We don’t just throw AI at anything and everything,” he says.

“We use AI agents only where they can deliver tangible business results. Our Lean AI processes helped us uncover the extent of time wasted in handling missed pickups and where artificial intelligence had the most potential to augment our automation software.”

This approach prioritises targeted interventions where intelligent automation can deliver measurable returns. The missed-pickup agents join a portfolio of more than 30 AI agents at C.H. Robinson, including LTL-focused tools for price quotes, orders, freight classification, shipment tracking and proof of delivery.

As these systems scale, they point to a broader shift in how logistics providers confront inefficiencies long treated as unavoidable costs.