How 442 supply chain leaders are building layered defenses, protecting freight in motion, and deciding how much authority to give AI over cargo-security decisions.
T I V E 2 0 2 6 M A R K E T S U R V E Y Cargo Theft Prevention in the Age of AI How 442 supply chain leaders are building layered defenses, protecting freight in motion, and deciding how much authority to give AI over cargo-security decisions.
SE CTION 0 1 E X ECU TIV E SU M MAR Y Executive Summary 442 RESPONDENTS ACROSS THREE REGIONS North America 55% Europe 27% Latin America 19% Percentages may not total 100 due to rounding. Cargo theft is becoming more sophisticated and harder to identify before freight has begun its journey. Identity fraud, fictitious pickups, and manipulated credentials can make an illegitimate pickup look legitimate at first, putting more weight on what happens once a shipment is in transit and whether an organization has real-time visibility or is relying on data that only surfaces after the fact. AI is also moving deeper into cargo-security operations, raising new questions about how threats are detected, how teams respond, and how much authority the technology should have over a live shipment. To understand how cargo security is changing under this new pressure, Tive surveyed 442 supply chain, transportation, operations, security, and executive leaders across North America, Europe, and Latin America and compared the practices companies use with the response, theft-confirmation, and recovery outcomes they report. Among the organizations represented, 78% changed or adjusted their cargo-security approach in late 2025 or early 2026, and 83% now use AI in their cargo security. Eighty percent of organizations using AI-assisted tools report either clear, measurable improvement or promising early results. With AI already widely adopted, the clearest differences in reported outcomes appear after pickup, while freight is in transit. Forty-five percent of organizations using active monitoring, meaning real- time visibility into a shipment while it’s moving, report recovering more than half of stolen cargo, compared with 30% of organizations relying on passive monitoring. Organizations using active monitoring also respond faster and confirm theft sooner. That post-pickup period becomes especially important when an illegitimate pickup appears legitimate at the outset. Fifty-five percent of respondents who could identify the method behind their latest theft cited identity-based fraud, spanning traditional identity and fictitious-pickup schemes as well as synthetic or AI- generated identities. Once freight leaves pickup, its location, route, and condition provide another source of information about whether the shipment is behaving as expected. Real-time route deviation detection has the strongest recovery rate of any individual AI- assisted application tested. Companies are also beginning to define how much authority AI should have inside those operations. Eighty-four percent of respondents would trust AI to perform at least one cargo-security function autonomously, without prior human approval. The research that follows examines a question the industry rarely measures: which cargo-security practices are associated with stronger prevention and/or recovery, and how AI is beginning to change the decisions made around a live shipment. 45% vs. 30% recover more than half of stolen cargo Organizations using active monitoring vs. those relying on passive monitoring. 53% vs. 29% recover more than half of stolen cargo Using real-time route deviation detection vs. not using it. 83% use AI in cargo-security operations today 84% would trust AI with at least one autonomous function in cargo security CARGO THEF T PRE VENTION IN THE AGE OF AI 02
SE CTION 0 2 AI ADOP TION & APPLICATION L AN DS CAPE M A R K E T C O N T E X T AI is Already Inside the Cargo-Security Operation AI adoption is already widespread across the market Tive surveyed. Real-time route deviation detection is the most common named application, used by 34% of organizations. Real-time route deviation detection tracks whether a shipment continues moving as expected and flags unexpected changes while freight is in transit, giving security teams a reason to investigate. Thirty-three percent use AI for pickup or driver identity verification, and 28% use it for in-transit monitoring and automated alerts. Companies are also beginning to see results. Among organizations using AI-assisted cargo-security tools, 37% report clear, measurable improvement and 44% report promising results that are not yet fully measurable. A D O P T I O N T O D AY 83% use AI in cargo-security operations today. R E S U LT S S O FA R Among organizations using AI-assisted cargo-security tools. 37% clear, measurable improvement 44% promising results, not yet fully measurable L E A D I N G A I A P P L I C AT I O N S I N C A R G O S E C U R I T Y Real-time route deviation detection 34% Pickup / driver identity verification 33% In-transit monitoring and automated alerts 28% Share of organizations naming each application. Respondents could select multiple applications. A I U S E B Y W H E T H E R T H E A P P R O A C H C H A N G E D AI adoption is far higher among companies that are actively evolving their cargo-security programs. Among organizations that changed their approach to cargo security in 2026, 92% use AI, versus the 51% of organizations that made no operational changes to their cargo-security operations over the past year. USE AI Changed or adjusted approach Made no changes USE REAL-TIME ROUTE DE VIATION DE TECTION Changed or adjusted approach Made no changes F R A U D AWA R E N E S S 67% of organizations have formally trained or briefed employees on identifying AI-driven fraud in the past six months. CARGO THEF T PRE VENTION IN THE AGE OF AI 03 92% 51% 39% 16%
SE CTION 0 3 TH E 13-L AYER SECU R I T Y STACK Cargo Security is a Layered Discipline Cargo-security programs have become highly layered. Tive asked companies about 13 measures spanning pickup verification, shipment visibility, monitoring, physical security, automated workflows, and response. ACTIVE / CONTINUOUS L AYER Five of the 13 measures keep producing information while freight is in transit. They are marked with a filled dot and analyzed on the following page. S E C U R I T Y M E A S U R E S H A R E W I T H M E A S U R E I N P L A C E I N P L A C E F O U N D AT I O N A L S E C U R I T Y + R E S P O N S E Staff training for insider threat or employee compromise 45% Formal cargo-theft response plan and recovery process 26% Law-enforcement coordination protocols 20% C A R R I E R , D R I V E R + P I C K U P V E R I F I C AT I O N Pickup verification 56% Carrier verification 53% Driver verification 52% Security seals 34% I N -T R A N S I T V I S I B I L I T Y + T R A C K I N G Real-time shipment visibility / in-transit sensor monitoring 35% In-transit monitoring with automated alerts 26% ELD / truck tracking 24% Smart route deviation alerts 19% A C T I V E M O N I T O R I N G + A U T O M AT I O N 24/7 security monitoring operations center 35% AI-powered workflow automation 22% Included in the active/continuous-layer analysis on the next page. Respondents could select multiple measures. That breadth means companies can now layer a significant number of controls around a single shipment. CARGO THEF T PRE VENTION IN THE AGE OF AI 04
SE CTION 0 4 TOTAL L AYER S VS . AC TIV E / C ON TI N UO US L AYER S C O M PA R I S O N The Number of Security Layers in Place Doesn’t Always Indicate How Those Layers Will Operate Cargo-security programs can include a long list of controls, but those controls play different roles once a shipment leaves pickup. Some verify the carrier, driver, or load at specific points in the journey. Others continue producing information while freight is moving, through real-time visibility, automated alerts, route monitoring, and 24/7 oversight. The survey looked specifically at the five layers designed to remain active or continuous around freight in transit: real-time shipment visibility, in-transit monitoring with automated alerts, smart route deviation alerts, 24/7 security monitoring, and AI- enabled workflows. 4 or more active/continuous layers 1 or fewer active/continuous layers S H A R E R E P O R T I N G T H R E E O R M O R E T H E F T O R D I V E R S I O N I N C I D E N T S I N T H E PA S T YE A R 31% of organizations with 4 or more active/continuous layers reported 3+ incidents 39% of organizations with 1 or fewer active/continuous layers reported 3+ incidents The two groups are separate and do not add to 100%. Bars share a 0–50% scale. D E S C R I B E T H E I R C A R G O - S E C U R I T Y P R O G R A M A S A D VA N C E D 65% 4 or more active/continuous layers 23% 1 or fewer Nearly three times as likely to describe their cargo-security program as advanced. Among organizations using four or more active or continuous layers, 31% report three or more incidents, compared with 39% among organizations using one or fewer. Organizations using four or more of these layers are also nearly three times as likely to describe their cargo-security program as advanced: 65% versus 23%. What these five capabilities share is that they continue generating information while the shipment is moving. Location, route behavior, automated alerts, and monitoring operations give security teams additional signals to evaluate after the initial pickup checks are complete. That operating layer becomes especially important when looking at how individual shipments are monitored in transit. CARGO THEF T PRE VENTION IN THE AGE OF AI 05
SE CTION 0 5 AC TIV E VS . PA S SIV E MON I TOR I NG The Clearest Divide is Real-Time Insight 45% of organizations using active monitoring recover more than half of stolen cargo, compared with 30% who rely on passive monitoring. R E C O V E R M O R E T H A N H A L F O F S T O L E N C A R G O 45% Organizations using active monitoring vs. 30% Organizations relying on passive monitoring Real-time tools give organizations continuous visibility into where a shipment is and what’s happening to it while in transit. That visibility is only one part of the equation, though: the survey also looked at what happens around an individual shipment once those tools are in place. That real-time visibility is what defines active monitoring: the opportunity to identify and address issues while a shipment is still moving, rather than discovering them after it arrives. Reviewing information as it comes in lets organizations catch conditions and risk indicators, such as light exposure, en route. From there, teams can use driver check-ins, escalation protocols, and other response steps to investigate and act in real time. The difference this active monitoring makes shows up across three separate measures: response speed, theft confirmation, and recovery. Respond to an alert or theft indicator within 60 minutes 72% 55% Confirmed their latest theft within four hours 59% 44% White bars: organizations using active monitoring. Pale blue bars: organizations relying on passive monitoring. A C T I V E M O N I T O R I N G Real-time visibility into a shipment while it’s moving. PA S S I V E M O N I T O R I N G Reliance on data that only surfaces after the fact. CARGO THEF T PRE VENTION IN THE AGE OF AI 06
SE CTION 0 5 AC TIV E VS . PA S SIV E MON I TOR I NG — C ON TI N U ED The same pattern remains even among companies already using AI. Organizations using active monitoring Organizations relying on passive monitoring Within that population, 48% of organizations using active monitoring report recovering more than half of stolen cargo, compared with 31% of organizations who rely on passive monitoring. For theft confirmation, 59% of organizations using active monitoring confirmed their latest incident within a four-hour timeframe, compared with 42% of organizations relying on passive monitoring. Formal pre-theft protocols (the standing procedures for spotting and responding to warning signs before a theft happens) are in place at 46% of organizations surveyed. Among organizations with formal protocols for detecting and responding to potential pre-theft surveillance, 49% report recovering more than half of stolen cargo, compared with 27% among organizations without formal protocols. Cyber and cargo security are fully integrated at only 37% of the organizations surveyed. Where they are integrated, 48% report recovering more than half of stolen cargo, compared with 32% where they are not. A M O N G O R G A N I Z AT I O N S A L R E A D Y U S I N G A I Recover more than half of stolen cargo 48% 31% Confirmed latest incident within four hours 59% 42% Formal pre-theft surveillance protocols Among organizations with formal protocols for detecting and responding to potential pre- theft surveillance. 49% vs. 27% recover more than half of stolen cargo, with protocols vs. without them. Cyber and cargo security fully integrated Where cyber and cargo security are fully integrated vs. where they are not. 48% vs. 32% recover more than half of stolen cargo, where integrated vs. where not. CARGO THEF T PRE VENTION IN THE AGE OF AI 07
SE CTION 0 6 FI NANCIAL STAK E S & R EG IONAL PROOF F I N A N C I A L S TA K E S Why Recovery Matters For companies facing six- and seven-figure cargo-theft exposure, recovery is a business outcome as much as a security outcome. Nearly one-third of respondents estimate that a single incident costs at least $100,000, while 32% report at least $250,000 in annual cargo-theft impact, and 9% report $1 million or more. When the cargo at risk can be worth hundreds of thousands of dollars, the ability to locate, investigate, and respond while freight is still recoverable carries real financial weight. N E A R LY 1 I N 3 31% COST OF ONE INCIDEN T estimate a single cargo-theft incident costs at least $100,000 N E A R LY 1 I N 3 32% ANNUAL IMPACT report at least $250,000 in annual cargo-theft impact A B O U T 1 I N 1 0 9% ANNUAL IMPACT report $1 million or more in annual impact The Operating Gap Crosses Markets Each region is shown on its own outcome measure. The two panels measure different things and are not comparable to one another. N O R T H A M E R I C A Recover more than half of stolen cargo 46% Organizations using active monitoring 17% Organizations relying on passive monitoring E U R O P E Confirm latest theft within four hours 60% Organizations using active monitoring 28% Organizations relying on passive monitoring The active versus passive monitoring divide also appears within the survey’s two largest regions. In North America, 46% of organizations using active monitoring report recovering more than half of stolen cargo, compared with 17% of organizations relying on passive monitoring. In Europe, 60% of organizations using active monitoring confirm their latest theft within a four-hour timeframe, compared with 28% of organizations relying on passive monitoring. CARGO THEF T PRE VENTION IN THE AGE OF AI 08
SE CTION 0 7 I DEN TI T Y-B A SED TH EF T & TH E P OST-PICKU P WI N DOW M E T H O D B E H I N D T H E L AT E S T T H E F T When Pickup Looks Legitimate, the Next Signal May Come From the Road More than half of respondents who could identify the primary method behind their latest theft cited identity- based fraud. Fifty-five percent cited an identity-based method, combining traditional identity or fictitious-pickup fraud with synthetic or AI-generated identity fraud. Thirty percent specifically cited the synthetic or AI-generated category. Twenty-four percent cited a physical trailer breach, break-in, or hijacking. Fraudulent credentials or documentation can make an illegitimate pickup appear legitimate. When that happens, the next opportunity to identify a problem may come once the freight is moving. Real-time monitoring and route deviation detection can surface when a shipment stops behaving as expected, even when the initial pickup cleared other security checks. P R I M A R Y M E T H O D B E H I N D T H E L AT E S T T H E F T Identity-based method 55% Synthetic or AI-generated identity 30% Included within the 55% above. Physical trailer breach, break-in, or hijacking 24% Respondents who could identify the primary method behind their latest theft incident. CARGO THEF T PRE VENTION IN THE AGE OF AI 09
SE CTION 0 8 RO U TE DE V IATION R O U T E D E V I AT I O N Route Deviation Has the Strongest Recovery Rate of Any Individual Application Tested The recovery data around route deviation delivered the strongest application-level result in the survey. Fifty-three percent of organizations using real-time route deviation detection report recovering more than half of stolen cargo, compared with 29% of organizations that do not use it. That is nearly 1.8 times the recovery rate. Route deviation detection is also the most commonly cited application in the survey, and is the function respondents are most willing to entrust to AI. R E C O V E R M O R E T H A N H A L F O F S T O L E N C A R G O 53% Using real-time route deviation detection 29% Not using it 1.8× Organizations using real-time route deviation detection report recovering more than half of stolen cargo at nearly 1.8 times the rate of those that don’t. Among organizations already using active monitoring, 60% of those also using route deviation report recovering more than half of stolen cargo, compared with 34% without route deviation. W I T H I N O R G A N I Z AT I O N S A L R E A DY U S I N G A C T I V E M O N I TO R I N G Also using route deviation Without route deviation Share recovering more than half of stolen cargo. CARGO THEF T PRE VENTION IN THE AGE OF AI 10 60% 34%
SE CTION 0 9 V EN T U R E M E TAL S+ C A S E S T U D Y Venture Metals+: Active Monitoring Helps Prevent More Than $1 Million in Cargo-Theft Losses In the first half of 2026, Venture Metals+ says Tive helped the company prevent more than $1 million in cargo-theft losses across its high-value metals shipments. Tive gives the company continuous visibility into shipment location, movement, and potential security events, allowing its security team to investigate unexpected activity while freight is still in transit. One incident in March shows how that works. Two members of the Venture Metals+ team received both a light alert and Smart Route Deviation Alert from a Tive tracker attached to a $250,000 shipment of recycled copper. Using the Tive platform, Director of Transportation Fernando Boom confirmed that the truck was heading in the wrong direction. Venture Metals+ worked with local police to detain the driver and recover the entire load. “Tive has become an important extension of our security prevention team. Having real-time visibility into our shipments enables us to stay ahead of potential threats, instead of reacting after a loss has already happened. The ability to monitor shipments, receive alerts, and quickly understand what is happening in transit gives our team the confidence to protect our cargo and keep our operations moving.” Fernando Boom , Director of Transportation, Venture Metals+ C A R G O -T H E F T L O S S E S P R E V E N T E D, H 1 2 0 2 6 $1M+ One customer’s result across its high-value metals shipments. T H E M A R C H R E C O V E R Y $250K Recycled copper shipment recovered in full. O N E R E C O V E R Y I N A C T I O N S T E P 0 1 Light alert + Smart Route Deviation Alert From a Tive tracker on a $250,000 recycled copper load S T E P 0 2 Shipment checked in Tive Two team members reviewed the alerts on the platform S T E P 0 3 Truck confirmed heading in the wrong direction Confirmed by the Director of Transportation S T E P 0 4 Local police engaged Police detained the driver S T E P 0 5 Full $250K copper load recovered The entire shipment was returned CARGO THEF T PRE VENTION IN THE AGE OF AI 11
SE CTION 10 WI LLI NG N E S S TO DELEG ATE W I L L I N G N E S S T O D E L E G AT E Companies Are Ready to Give AI Real Authority 84% Would Trust AI to Act Autonomously in Cargo Security. Three in 10 would let it stop a shipment or escalate an alert to law enforcement without prior human approval. 84% would trust AI with at least one autonomous function in cargo security The next stage of AI adoption is already visible in what companies are willing to let the technology do. Forty-two percent would trust AI to autonomously detect or flag a route deviation. Forty percent would allow AI to conduct real-time shipment monitoring or generate alerts. Current users of real-time route deviation detection are also more willing to delegate that function. Among organizations already using it, 53% would trust AI to flag a route deviation autonomously, compared with 36% of organizations that do not currently use it. Respondents are also willing to delegate actions with a more direct effect on the security response. Thirty percent would allow AI to place a shipment on hold, escalate an alert to law enforcement, or do both, without prior human approval. Only 16% say every AI alert or recommendation should require human review before anyone acts on it. Cargo security creates a different test for autonomous AI than many enterprise applications. A decision can affect a physical shipment, trigger an investigation, or escalate an issue to law enforcement. These figures measure willingness to delegate authority, not current deployment of autonomous AI. M O N I T O R / F L A G Detect or flag route deviations 42% Real-time monitoring / alerts 40% I N T E R V E N E / E S C A L AT E Shipment hold and/or law- enforcement escalation 30% R E Q U I R E R E V I E W E V E R Y T I M E Every AI alert requires human review 16% Would trust autonomous route flagging Current route deviation detection users 53% Non-users 36% CARGO THEF T PRE VENTION IN THE AGE OF AI 12
SE CTION 11 2 026 BENCH MAR K B E N C H M A R K A 2026 Benchmark for Cargo-Security Leaders The survey gives leaders a way to examine their own operation against the market. W H E R E T H E M A R K E T S TA N D S S H A R E O F O R G A N I Z AT I O N S 2 0 2 6 Would trust AI with at least one autonomous function 84% Use AI 83% Use active monitoring 47% Have formal pre-theft protocols 46% Fully integrate cyber and cargo security 37% Use AI for real-time route deviation detection 34% Ranked by prevalence. Practical Areas to Examine For cargo-security leaders, the benchmark creates several practical areas to examine, each tied to a specific finding in this report. 01 Know what's in the stack. Verification, visibility, monitoring, and response measures need to be understood as one operating environment; the research found that counting layers alone says little about outcomes. 02 Keep the shipment visible after pickup. Identity fraud can let an illegitimate pickup clear initial checks; movement and route behavior are the next source of information once freight is in transit. 03 Define what happens after an alert. The strongest operating differences in the survey appear among organizations using active monitoring. Pair real-time visibility with a clear response process, whether that’s proactive check-ins, monitoring-center oversight, or escalation protocol, so the alert leads to action the moment it’s raised. 04 Decide where AI gets authority. Most respondents are already comfortable with some autonomous functions, and a meaningful share would let AI affect the response itself. That’s a governance decision as much as a technology one. CARGO THEF T PRE VENTION IN THE AGE OF AI 13
Tive operates in the area of cargo security where these findings converge: the period after freight leaves pickup and before an incident becomes a loss. Real-time shipment visibility gives security teams a current view of where a load is, and shows what's happening to it in transit. Smart route deviation alerts flag when a shipment moves off its expected path, while prolonged stop alerts surface unexpected dwell or stops that warrant investigation. Light alerts and Tive Seals provide additional visibility into potential tampering or unauthorized access to the load. Together, these signals give security teams the context needed to assess unusual activity while there is still time to respond. That matters in a threat environment where a pickup can look legitimate … even when it isn’t. It also matters as AI takes on more responsibility. A system asked to monitor a shipment, flag a deviation, or support a higher-consequence decision needs timely information about the physical load. Tive provides that real-time shipment intelligence, and gives security teams a clearer basis for deciding what happens next. Venture Metals+ shows the operational value: in the first half of 2026, Tive helped prevent more than $1 million in cargo-theft losses by giving its team continuous visibility into high-value shipments and the ability to act on unexpected activity while freight was still in transit. See how Tive helps security teams protect high-value freight in transit. tive.com/solutions/cargo-theft-prevention → CARGO THEF T PRE VENTION IN THE AGE OF AI 14 T I V E From Shipment Data to Security Action
SE CTION 12 M E THODOLOGY R E F E R E N C E Methodology & Sources Tive surveyed 442 supply chain, transportation, operations, security, and executive leadership respondents across North America, Europe, and Latin America. Findings tied to respondents’ most recent theft incident, including the primary method and time from suspected theft to confirmed discovery, are based on the incident subset where applicable (n=300). Recovery findings use Q29, which asks respondents about the share of stolen cargo recovered over the past 12 months; crosstab bases vary accordingly. The survey is cross-sectional and self-reported. Comparisons between security practices and outcomes describe associations, and do not establish causation. Incident-frequency comparisons are not normalized by shipment volume. Reader-facing percentages are rounded to whole numbers; source figures with full decimal precision are preserved separately for design and internal reference. Percentages may not total 100 due to rounding. T I V E 2 0 2 6 M A R K E T S U R V E Y CARGO THEF T PRE VENTION IN THE AGE OF AI 15