C.H. Robinson: Scaling AI for Faster Freight

The logistics industry is confronting a persistent challenge in less-than-truckload (LTL) shipping that could be costing companies millions in lost productivity.

Missed pickups have long plagued the LTL sector, creating cascading delays and forcing carriers to make costly return trips. However, new developments in AI suggest the industry could be approaching a turning point.

C.H. Robinson, which moves more LTL freight than any other third-party logistics provider in North America, has deployed AI agents designed to track missed pickups and apply advanced reasoning to determine how freight can continue moving. The technology is also collecting data which LTL carriers are using to improve their operations.

The initiative has produced notable efficiency gains. The company reports that 95% of checks on missed LTL pickups have been automated, saving more than 350 hours of manual work per day. Shippers' freight could move up to a day faster, while unnecessary return trips to collect missed freight have been reduced by 42%.

AI adoption reshapes productivity metrics

The productivity improvements align with broader industry trends. According to PwC's 2025 Global AI Jobs Barometer, industries most exposed to AI, including logistics, have seen productivity growth nearly quadruple, up 27% compared to those that have not adopted the technology.

However, adoption alone does not guarantee results. A McKinsey 2025 report found that while 88% of organisations use AI, only 6% are capturing meaningful enterprise value. These "high performers" are characterised by their ability to fundamentally redesign workflows, rather than simply overlaying AI onto existing processes.

The gap between adoption and value creation highlights a critical challenge facing the logistics sector. Companies that successfully integrate AI are not merely automating existing tasks but are reimagining entire operational frameworks to leverage the technology's capabilities.

Speed has emerged as a critical competitive factor. Gartner reports that 90% of supply chain leaders now rank speed as one of their top three most critical performance metrics.

The operational complexity of LTL

The LTL shipping model requires intricate coordination. With one lorry carrying freight from up to 20 different shippers, the process involves collecting multiple shipments, transporting them to a terminal and recombining them on other lorries heading in the same direction. This 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, which manages 37 million shipments annually representing US$23bn in freight, the new AI agents are resolving hundreds of shipments per day across more than 11,000 customers.

The system employs two AI agents working in tandem. One agent contacts carriers about missed pickups while another determines what steps to take. Because the agents can make 100 calls and 100 decisions simultaneously, missed pickups could be resolved faster and freight could get on the road 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 that all that time and capacity aren't being wasted, it keeps other shippers' freight from getting delayed."

The technology also provides carriers with operational insights they previously lacked, allowing them to identify which electronic communications could be improved and optimise their scheduling.

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The Lean AI approach

Mark Albrecht, VP for AI at C.H. Robinson, described the deployment as a demonstration of what the company calls Lean AI.

"We don't just throw AI at anything and everything," Mark comments.

"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."

The Lean AI methodology represents a strategic departure from conventional technology implementation. Rather than pursuing AI adoption for its own sake, the approach prioritises identifying specific operational pain points where intelligent automation can generate measurable returns.

This targeted strategy has enabled C.H. Robinson to build a portfolio of purpose-driven solutions. The missed-pickup agents join a fleet of more than 30 AI agents that C.H. Robinson has built, including others dedicated to LTL operations such as price quotes, orders, freight classification, shipment tracking and proof of delivery.

As the technology scales, it could signal a broader shift in how logistics providers address operational inefficiencies that have long been accepted as inevitable costs of doing business.