Cyberattacks used to be the biggest security issue surrounding AI infrastructure, but that could be changing. A recent cargo theft outside Chicago suggests another vulnerability — and it’s one that has nothing to do with malware or prompt injection.Just last week, the Cook County Sheriff’s Office recovered two stolen trailers containing roughly $1.3 million in data center equipment and copper wiring, taken from separate shipments originating hundreds of miles away. One trailer held about $300,000 worth of copper wire — reported stolen in Pine Hill, Alabama — destined for data center construction. The other carried roughly $1 million in data center infrastructure equipment, stolen out of Jacksonville, Florida. Both ended up at the same truck yard in Elk Grove Township, outside Chicago.Viewed in the context of the AI boom, it highlights that the physical supply chain itself is becoming a new target for bad actors.Viewed in the context of the AI boom, it highlights that the physical supply chain itself is becoming a new target for bad actors. A new high-value cargoWe’re all familiar with typical bottlenecks like GPU shortages, power constraints and cooling capacity, which have plagued the AI era since its inception. But we forget that building an AI data center requires an enormous volume of specialized hardware moving through freight networks. These include servers, networking gear, fiber, switchgear, cooling systems, power distribution equipment and thousands of pounds of copper. Each represents capital investment and potential deployment delays.As hyperscalers accelerate the construction of data centers, the exposure of these items between the factory and data center creates a risk category that the industry as largely ignored.When one delay cascadesLarge GPU clusters depend on the synchronized delivery of dozens of interconnected systems. A training cluster is a tightly coupled system of servers, switches, optics, power distribution, and cooling that must be installed together. Missing networking hardware can idle racks, delayed power equipment can postpone an entire deployment and stolen copper can stall electrical work. So when one component category disappears, the delay cascades across everything.So when one component category disappears, the delay cascades across everything.Cargo theft by the numbersInfrastructure resilience increasingly depends on whether critical hardware arrives at the construction site at all — and on schedule. Verisk CargoNet reported that U.S. and Canadian cargo theft losses jumped roughly 60% in 2025 to nearly $725 million, even as the total number of incidents held essentially flat — a sign that thieves are becoming more selective about high-value freight. Metal theft rose 77%, driven largely by demand for copper, while organized groups shifted toward enterprise computing hardware. CargoNet expects that focus on high-value technology — RAM modules, storage drives and enterprise computing equipment — to carry into 2026. For broader context, the Department of Homeland Security has estimated that cargo theft overall costs as much as $35 billion a year.The Chicago incident fits squarely inside that trend.Beyond firewalls and malwareObviously, cargo theft isn’t an engineer’s problem. But organizations building AI infrastructure may need to broaden their thinking about deploying AI capacity on aggressive timelines.Cloud providers, colocation operators and hardware vendors have already invested heavily in defending infrastructure from digital threats. As AI infrastructure becomes more valuable, protecting the physical systems behind it may deserve similar attention.The next supply-chain conversationThe AI boom has already forced the industry to rethink electricity, cooling, networking and semiconductor manufacturing. Physical logistics may be next.It starts long before the equipment reaches the data center.If the value of AI infrastructure continues to climb into the billions of dollars, the industry’s definition of “infrastructure security” is likely to expand beyond firewalls and identity management. It starts long before the equipment reaches the data center.The post The $1.3 million theft that exposed AI’s blind spot appeared first on The New Stack.