Active monitoring linked with stronger cargo recovery

Tive has found a marked difference in reported cargo recovery between companies actively monitoring freight in transit and those relying on passive tracking, as identity fraud and increasingly automated security tools alter the way theft is detected and investigated.

The shipment visibility company surveyed 442 supply chain, transport, operations, security, and executive professionals across North America, Europe, and Latin America for its report Cargo Theft Prevention in the Age of AI. Forty-five per cent of organisations using active monitoring said they recover more than half of stolen cargo, compared with 30% of companies using passive monitoring.

The distinction is based on whether shipment data is being watched and acted upon while cargo is moving. Passive tracking can provide a useful record after an incident, but active monitoring is designed to trigger intervention while a shipment is still in transit and there remains a realistic possibility of recovering it.

That difference was also visible in response times. Seventy-two per cent of active-monitoring users said they normally respond to an alert or suspected theft within 60 minutes, compared with 55% of passive users. Fifty-nine per cent of organisations using active monitoring said their latest theft was confirmed within four hours, against 44% among passive-monitoring respondents.

Route deviation produced one of the strongest differences in the survey. Fifty-three per cent of companies using route-deviation alerts reported recovering more than half of stolen cargo, compared with 29% of organisations not using the capability. Among respondents already operating active monitoring, the corresponding figures were 60% and 34%.

The result is commercially plausible because route behaviour can expose a problem after a shipment has passed apparently legitimate collection checks. A vehicle that leaves the expected corridor, stops at an unusual location, or fails to progress towards the consignee gives security teams another signal to examine before the cargo reaches a point where recovery becomes considerably more difficult.

That matters because freight theft is increasingly exploiting identity and process weaknesses rather than relying only on physical interception. Tive found that 55% of respondents able to identify the primary method behind their most recent theft cited identity-based fraud, including fictitious pickups and synthetic or AI-generated identities.

Krenar Komoni, founder and CEO of Tive, said: “Cargo theft is becoming harder to catch at the point of pickup.” The implication is that collection controls remain necessary but cannot be the sole line of defence once fraudulent carriers or drivers become convincing enough to pass initial checks.

Monitoring then becomes a second layer. A shipment released to the wrong party may still be detectable if its route, stop pattern, trailer condition, or other monitored signals differ materially from the legitimate transport plan.

The survey does not prove that tracking technology alone causes stronger recovery rates. Companies investing in active monitoring may also have more mature security functions, tighter carrier onboarding, better escalation procedures, dedicated investigation teams, or stronger relationships with insurers and law enforcement.

The figures nevertheless point to an operational advantage in seeing a problem while it is developing. An alert reviewed during transit creates more options than a tracker record examined after a delivery deadline has passed and the load has already been transferred, broken down, or moved into another distribution channel.

Recent US cargo theft data has shown how physical and procedural vulnerabilities increasingly overlap. Verification at pickup remains critical, but the problem now extends across carrier identity, communications, route controls, warehouse procedures, and in-transit monitoring.

Tive’s findings also show how quickly artificial intelligence is entering that security chain. Eighty-three per cent of respondents said their organisations use AI in cargo security, while 80% of AI users reported either measurable improvement or promising early results.

The performance gap between active and passive monitoring remained when the company looked only at respondents using AI. Forty-eight per cent of organisations combining AI with active monitoring reported recovering more than half of stolen cargo, compared with 31% of AI users operating passive monitoring.

Automation becomes useful when security teams are dealing with large numbers of movements and alerts. Software can identify route anomalies, unusual dwell, unexpected door events, or patterns across several shipments more consistently than an operator manually watching every vehicle on a screen.

The difficulty begins when a system moves from identifying an anomaly to deciding what should happen next. Eighty-four per cent of respondents said they would trust AI to perform at least one cargo-security function autonomously, yet only around three in ten would allow it to place a shipment on hold, escalate an alert to law enforcement, or carry out both actions. Sixteen per cent said every AI recommendation should require human review.

That caution reflects the cost of false intervention. A route deviation can indicate theft, but it can also result from congestion, a diversion, a driver instruction, a changed delivery point, or inaccurate geofencing. A security system therefore has to react quickly enough to matter without disrupting legitimate freight every time a truck behaves unexpectedly.

The financial exposure explains why companies are willing to tolerate some additional operational complexity. Nearly one third of respondents estimated that a single cargo theft incident costs at least $100,000. Thirty-two per cent reported annual theft impacts of at least $250,000, while 9% put annual exposure at $1 million or more.

Those figures can extend well beyond the invoice value of the goods. A missing shipment may trigger production disruption, emergency replacement freight, retailer penalties, insurance costs, investigations, customer shortages, and reputational damage, particularly where the stolen cargo includes electronics, pharmaceuticals, food, or industrial components that cannot be replaced quickly.

Active monitoring is therefore only as valuable as the response process behind it. A high-quality alert received in minutes does little if nobody is responsible for checking the vehicle, contacting the driver, notifying the carrier, or escalating a confirmed theft.

The practical security model is becoming layered rather than dependent on one control. Carrier verification, identity checks, tracking, route monitoring, artificial intelligence, and human intervention increasingly need to work as part of the same process.

Tive’s research suggests companies with faster visibility are reporting better recovery outcomes. The more important operational question is whether that visibility reaches someone with the authority and procedures to act before a suspicious movement becomes a completed theft.