Organised crime groups are increasingly targeting the global supply chains that support artificial intelligence infrastructure, stealing high-value cargo including servers, semiconductors, copper wiring and data centre equipment as demand for AI-related assets continues to accelerate.

Industry experts have warned that the rapid expansion of AI infrastructure has created a lucrative black market for specialist technology shipments. Cargo theft losses are estimated to have reached US$725 million in 2025, with electronics representing a significant proportion of stolen goods. The trend signals a marked shift from traditional consumer products to specialised technology assets that are essential to data centres, cloud computing and AI deployment.

The growing value of AI infrastructure cargo has exposed new vulnerabilities across transport and logistics networks. Servers, processors, networking hardware, power systems, cooling equipment and copper cabling are often moved through complex supply chains involving manufacturers, freight forwarders, warehouses, ports, hauliers and installation contractors. Each handover point can create an opportunity for theft, diversion or tampering.

Security specialists say the risk is being amplified by predictable routes, unsecured layover points, limited shipment visibility and fragmented communication between logistics providers, security teams and law enforcement. In many cases, criminal groups are exploiting gaps between different parties in the supply chain, particularly when cargo is in transit or temporarily stored.

A senior security director for a leading logistics provider, speaking anonymously due to customer confidentiality, said the threat environment around technology cargo had changed significantly as AI infrastructure investment accelerated.

“What we are seeing is a much more targeted approach from organised criminal groups,” the director said. “These are not opportunistic thefts in many cases. Criminals understand which loads are valuable, where the weak points are and how quickly these assets can move into secondary markets.”

The director said customers transporting AI infrastructure components increasingly expect live visibility and faster escalation when a shipment behaves unusually.

“Our customers want assurance that their assets are not just being tracked, but actively monitored,” the director said. “With Argus IoT devices, we can see location, movement, dwell time, route deviation and potential tampering indicators in real time. That information is monitored through our fusion centre, where operators assess alerts, verify what is happening and coordinate the next step.”

Argus IoT devices can be deployed on containers, trailers, pallets or individual assets to provide live visibility over cargo location, movement, route deviation, door access, tampering, dwell time and other risk indicators. For sensitive AI infrastructure shipments, this data allows security teams to detect unusual activity quickly, including unauthorised stops, unexpected route changes, signal disruption or movement outside approved geofenced areas.

When integrated into a fusion centreÒ, the value of this information increases significantly. A fusion centre brings together data from IoT devices, transport management systems, driver communications, CCTV, access control, route intelligence, incident reports and external threat feeds. This enables operators to build a single operational picture of a shipment and coordinate faster, more informed responses.

For example, if an Argus IoT device detects that a shipment of servers has stopped unexpectedly outside an approved location, fusion centre operators can immediately assess the alert, contact the driver, verify the vehicle’s position against the planned route, review local risk intelligence and escalate the matter to logistics partners or law enforcement where required.

The security director said this ability to act quickly is becoming central to protecting high-value technology shipments.

“The critical issue is time,” the director said. “If you only discover a theft after a missed delivery, the cargo may already have been broken down, moved or sold. Real-time monitoring gives us the opportunity to intervene while the situation is still developing.”

This model moves cargo security away from reactive reporting and towards live intervention. Instead of discovering a theft after a missed delivery or delayed check-in, organisations can identify suspicious activity while an incident is still unfolding.

Fusion centreÒ monitoring also enables a more proactive approach to supply chain risk. By analysing theft patterns, high-risk corridors, repeat incident locations and shipment behaviour, security teams can adapt transport plans before cargo is exposed. Measures may include route changes, enhanced escort protocols, tighter handover procedures, additional IoT tracking, revised rest-stop policies and closer coordination with law enforcement.

The director said intelligence-led monitoring also helps customers make better decisions before shipments leave a facility.

“We are not just watching a dot on a map,” the director said. “We are looking at route risk, stop behaviour, driver communication, geofence breaches, device alerts and the wider threat picture. That allows us to advise customers on how to reduce exposure before a shipment reaches a vulnerable point.”

The targeting of AI infrastructure cargo reflects the broader commercial value now attached to the physical components behind digital transformation. While public attention often focuses on software, models and cloud platforms, the infrastructure required to power AI depends on highly specialised hardware that is expensive, scarce and difficult to replace quickly.

A stolen shipment of servers, chips or data centre components can create disruption far beyond the immediate value of the goods. Losses may delay construction schedules, affect customer commitments, increase insurance exposure and create reputational risk for manufacturers, logistics providers and infrastructure operators.

As AI investment continues to accelerate, supply chain security is becoming a strategic priority rather than a back-office logistics function. Traditional controls such as locks, seals and scheduled check-ins remain important, but they are no longer sufficient on their own against organised and increasingly sophisticated criminal networks.

The security director said customer confidentiality remains a key part of the monitoring process, particularly for technology clients moving sensitive or high-value assets.

“Discretion is essential,” the director said. “Many customers do not want shipment details, routes or security arrangements discussed publicly, and rightly so. Our role is to provide visibility, escalation and protection without exposing operational information that could increase their risk.”

Argus IoT devices and fusion centre monitoring offer a more intelligence-led approach, combining live cargo visibility with coordinated response capability. Together, they can help organisations protect high-value technology shipments, reduce theft exposure and strengthen resilience across the AI infrastructure supply chain.

With demand for servers, semiconductors, copper wiring and data centre equipment expected to remain high, the risks facing technology logistics networks are unlikely to ease. For companies involved in manufacturing, transporting, storing or deploying AI infrastructure, investment in real-time monitoring and centralised security operations may prove critical to protecting the assets that underpin the next generation of artificial intelligence.

Article by Janet Wong, Project Argus Founder & Operations Director