• Cargo security is exposing the limits of checkpoint-based tracking, with companies often knowing where a shipment should be without knowing whether the physical goods remain intact. High-value theft increasingly exploits gaps between scans, using impersonation, fraudulent documentation, insider knowledge and cyber-enabled tactics to divert cargo before problems are detected.
• Continuous, item-level visibility could shift cargo security from reactive to proactive intervention. Sensors attached to products, cases or pallets can provide persistent location and movement data between conventional GPS, RFID, barcode and TMS checkpoints, allowing operators to identify unexpected routes, dwell times or handoffs while there is still time to intervene.
• The emerging opportunity is to combine physical-world data with AI rather than simply generate more tracking information. Continuous signals can turn static shipment updates into actionable intelligence, helping distinguish normal logistics exceptions from suspicious activity and reducing the wider costs of theft, including expedited freight, replacement inventory, disruption, investigations and higher security or insurance costs.

The alleged theft of more than US$2 million worth of Nike merchandise highlights a persistent weakness in modern supply chains: companies may know where a shipment is supposed to be without knowing what is actually happening to the products inside it.

Supply chains have invested heavily in digitisation, but much of that investment has focused on transactions and logistics events, purchase orders, manifests, carrier updates and delivery confirmations, rather than continuous visibility of the physical goods themselves.

“These gaps in visibility leave significant periods of time where goods become untraceable,” Amir Khoshniyati, VP at Wiliot, said. “Between scans, there’s no way to know whether goods are moving as expected, sitting somewhere they shouldn’t be, or missing entirely. That creates an opportunity for theft, diversion, or misrouting to go undetected until the next checkpoint, or even until the shipment fails to arrive at its final destination.”

Tracking is not the same as visibility

The conventional model of supply-chain tracking is built around checkpoints. Goods are scanned when they leave a facility, recorded during handoffs and checked again at their destination. GPS can add visibility into the vehicle or container carrying them. But that does not necessarily establish that the correct products remain inside.

“The biggest limitation is that many systems tell you where a shipment should be, rather than providing continuous visibility into where the goods actually are,” Khoshniyati stated. “If a product moves somewhere it shouldn’t, there’s often not enough continuous data to recognise that as an anomaly in real time. This means that the first indication of a problem tends to be a missed delivery or an inventory discrepancy, well after the fact.”

A shipment can therefore appear to be progressing normally while its physical inventory has already been compromised. The first indication may be a missed delivery or inventory discrepancy, by which point the opportunity to intervene has largely disappeared.

The problem is compounded by the growing sophistication of organised cargo theft. Criminal networks are increasingly exploiting fraudulent documentation, carrier impersonation, insider knowledge and cyber-enabled tactics across the shipment lifecycle.

“Criminal networks have gotten considerably more sophisticated,” Khoshniyati outlined. “They’re exploiting vulnerabilities across the entire shipment lifecycle, not just at pickup or delivery. They’re using impersonation, fraudulent documentation, insider knowledge, and cyber-enabled tactics to intercept high-value shipments, and increasingly targeting specific commodities rather than opportunistically grabbing whatever’s available.”

In that environment, scheduled checkpoints can become predictable blind spots. “Systems that only capture status at scheduled checkpoints will always be a step behind criminals who know exactly where those blind spots are,” he added. “Continuous, item-level visibility gives businesses a much better chance of identifying anomalies as they occur, rather than discovering a theft after the fact.”

The cost extends beyond the stolen goods

The value of stolen merchandise is only part of the financial impact. Cargo theft can lead to expedited freight, replacement inventory, production disruption, customer service costs, investigations, higher insurance premiums and additional security spending.

“Those costs often outlast the incident itself and add up well beyond the headline dollar figure,” Khoshniyati explained. “Beyond the value of the stolen goods, cargo theft can trigger a much broader chain of financial and operational consequences, including shipment delays and expedited freight to cover the shortfall, production disruptions and replacement costs. Those costs can add up well beyond the initial loss.”

Earlier detection can therefore have value even when it does not prevent every theft. If a business identifies an unexpected movement while goods are still within the logistics network, it may have time to investigate, alert a carrier, intervene at a facility or involve law enforcement. Once the loss is discovered at delivery, those options are considerably narrower.

Putting intelligence on the product

This is where item-level visibility changes the proposition, such as using Wiliot’s low-cost, battery-free Bluetooth sensors, known as IoT Pixels, on products, cases or pallets. The aim is to give physical goods a persistent digital identity and generate information about their location and movement without relying solely on manual scans or fixed checkpoints.

“With IoT Pixels directly on products, cases, or pallets, companies can move toward continuous visibility without relying on manual scans or fixed checkpoints,” Khoshniyati highlighted. “That creates a much more complete chain of custody and gives operators the opportunity to intervene when an item’s movement deviates from the expected journey. It means companies can move towards continuous visibility without adding the operational burden of manual scanning at every stage.”

The distinction is important. Rather than simply asking whether a truck is where it should be, operators can begin asking whether the individual goods associated with that shipment are where they should be.

GPS, RFID, barcodes and transport management systems still have important roles. The difference is that continuous item-level sensing can fill some of the gaps between their checkpoints.

From tracking to physical AI

The concept of Physical AI takes this a step further. Physical objects can continuously generate data about their location, movement and condition, while AI interprets those signals to identify anomalies.

“Visibility is no longer a series of static snapshots, scans, and checkpoints, but a live, ongoing signal that AI systems can interpret in real time,” Khoshniyati says. “Physical AI is the idea that everyday physical items can continuously generate their own data about where they are, how they’re moving, and what condition they’re in. For cargo security, this represents a shift from reactive to proactive monitoring, changing what ‘knowing where something is’ actually means.”

For cargo security, the potential shift is from reactive investigation to proactive intervention. An unexpected movement, prolonged dwell or unusual handoff does not automatically indicate theft, but continuous data gives AI more opportunity to distinguish genuine exceptions from normal logistics activity.

“A deviation from an expected route, dwell time, or handoff can be recognised as it’s happening, rather than pieced together after the fact,” he laid out. “Companies can have the intelligence to identify suspicious activity and take action before a small exception becomes a major loss. That earlier warning changes the response from reactive cleanup to proactive intervention.”

That timing matters. The earlier a suspicious event is identified, the greater the range of responses available to the cargo owner.

The bigger problem is actionable intelligence

Supply chains already generate enormous quantities of data. The issue is that much of it describes transactions, planned movements and discrete events rather than the continuous physical reality of goods moving through the network.

That points to a broader change in supply-chain visibility. The next step may not be another dashboard or another tracking update, but a closer connection between digital systems and the physical products they represent.

The lesson from high-value cargo theft is straightforward: businesses cannot effectively protect what they cannot continuously see.

“The bigger challenge isn’t a lack of data, it’s a lack of continuous, physical-world data with AI that can actually interpret it,” Khoshniyati concluded. “When systems can continuously understand where goods are, how they’re moving, and what condition they’re in, they can move beyond reporting what happened to identifying what requires attention now. That is where continuous, physical-world intelligence can make a real difference to supply chain security.”

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