AI vs. Cargo Theft: What CORCA Means for Shippers

Cargo theft isn’t “somebody cut a seal and grabbed a pallet” anymore. According to industry testimony shared with lawmakers this week, strategic cargo theft is up 1,500% since Q1 2021, and it’s increasingly digitally driven—criminal groups using laptops to impersonate carriers, manipulate paperwork, and redirect freight while it’s already moving.

That shift matters for anyone running transportation, logistics, supply chain, or procurement. When theft becomes a data problem, security becomes a data problem too. Federal legislation like the Combating Organized Retail Crime Act (CORCA) can raise the floor—more coordination, clearer authority, better enforcement. But it won’t raise the ceiling. The ceiling comes from how quickly companies can detect anomalies and act in real time.

This post is part of our “AI in Supply Chain & Procurement” series, where we look at practical ways AI reduces risk, controls cost, and keeps goods flowing. Cargo theft is exactly that kind of problem: cross-functional, high-impact, and measurable.

Why cargo theft is escalating (and why it’s not just a trucking issue)

Cargo theft is escalating because the attack surface is bigger than the trailer. The modern shipment touches broker systems, carrier portals, email, EDI, digital bills of lading, load boards, marketplace listings, and payment rails. Criminal networks don’t need to be near a warehouse to win.

Industry estimates presented to lawmakers put the annual cargo theft burden between $1.83B and $6.56B (direct and indirect costs), with average loss per incident around $29,108 for motor carriers and $95,351 for logistics companies. Strategic theft incidents can average over $200,000 per event—the kind of number that turns a good quarter into a bad one.

Here’s the part procurement leaders often underestimate: theft doesn’t just hit the transportation budget.

• Inventory accuracy breaks (and your planners start chasing ghosts).
• OTIF and service levels fall (and retail chargebacks rise).
• Expedites spike (air, team drivers, premium LTL—pick your poison).
• Supplier scorecards get noisy (because “late” looks like “noncompliant”).

The reality? Cargo theft is now a supply chain risk management problem, not a loss-prevention problem.

The new playbook: “strategic theft” and transnational coordination

Strategic theft is a polite phrase for a very modern kind of fraud: criminals redirecting or stealing loads using digital access and deception. The testimony highlighted that many groups operate outside the U.S., making state and local enforcement insufficient when the scheme spans jurisdictions, platforms, and borders.

If you’ve ever investigated a suspicious “carrier update” email or a last-minute request to change a delivery address, you’ve seen the same pattern:

When criminals can alter information faster than you can verify it, they don’t need force. They just need timing.

What CORCA changes: a federal response to organized retail crime and cargo theft

CORCA’s core value is coordination. It aims to give law enforcement the structure and authority to treat cargo theft and organized retail crime like the networked, multi-state problem it is.

Based on what’s been described publicly, CORCA includes four provisions worth paying attention to—because each one maps directly to how theft happens in 2025.

1) A coordination center that matches how crime networks operate

CORCA proposes an Organized Retail and Supply Chain Crime Coordination Center within federal enforcement (as described, within U.S. Immigration and Customs Enforcement). The point isn’t bureaucracy—it’s a single place to:

• share intelligence across jurisdictions
• track patterns and emerging tactics
• support multi-agency investigations
• provide technical assistance and training

Why this matters to operators: today, a theft ring can hit a shipper in Texas, fence goods through an online marketplace, and launder funds through gift cards. If the response is fragmented, the criminals keep their advantage.

2) Gift card fraud and money laundering alignment

CORCA also expands money laundering statutes to include gift card misuse, which retail security leaders say has surged. One large retailer testified that fraud losses tied to gift cards have been estimated at over $1B across the last two years.

Gift cards might sound like a retail-only headache, but they’re a critical “exit ramp” for criminal enterprises. If you can’t slow the monetization path, theft remains profitable.

3) Lower threshold for federal intervention on stolen property

CORCA would lower the threshold for federal action on interstate transportation of stolen goods to an aggregate $5,000+ over a 12-month period.

That’s a practical move. Theft rings don’t always steal one giant load; they often run repeatable plays across many smaller events, betting that each incident won’t meet a higher threshold.

4) Digital marketplace oversight: following the resale channels

The bill also targets the illegal acquisition and resale of goods through physical and online marketplaces.

If you’re trying to reduce cargo theft, you have to care about resale liquidity. Criminals steal what they can sell quickly. If marketplaces and resale channels face more scrutiny, it changes what’s “worth stealing.”

Where legislation ends and AI begins: prevention beats prosecution

Legislation helps after the fact; AI helps before the truck turns off the highway. I’m firmly in the “both” camp—but companies waiting for policy fixes are choosing to bleed longer than necessary.

In practice, the most effective cargo theft prevention programs behave like an early-warning system:

• detect anomalies in identity, routing, timing, and documentation
• score risk in real time
• trigger verification steps before tender acceptance or appointment changes

That’s a natural fit for AI in supply chain security, especially for organizations already building AI-driven procurement and transportation control towers.

The practical AI use cases that stop strategic theft

1) Identity and entity resolution (carrier, broker, driver, bank account)

Strategic theft often starts with impersonation: a “carrier” that looks legitimate enough to accept a tender. AI can support:

• matching DOT/MC + phone + email + domain age + banking details
• flagging lookalike domains and synthetic identities
• detecting sudden changes in contact info, remit-to, or factoring instructions

Strong stance: if you’re still approving carriers with a spreadsheet and a gut check, you’re operating like it’s 2015.

2) Anomaly detection on shipment events

AI is very good at learning “normal” and flagging “weird”:

• unexpected trailer dwell patterns
• repeated last-minute appointment changes
• route deviations inconsistent with traffic/weather constraints
• suspicious “address corrections” near high-theft regions

This is where real-time tracking + predictive analytics becomes more than visibility. Visibility says what happened. Predictive models say what’s likely happening.

3) Document intelligence for bills of lading, PODs, and tenders

The hearing highlighted how criminals can manipulate shipment documentation. AI can:

• compare BOL fields against TMS/ERP “system of record” values
• flag mismatches in ship-to, consignee, weight, or commodity
• detect reused or templated PDFs that match known fraud patterns

4) Marketplace and returns intelligence (retail + supply chain together)

If you’re a retailer, or supply a retailer, your risk doesn’t end at delivery. AI can connect the dots between:

• theft patterns and SKU-level resale velocity
• abnormal return spikes for high-risk items
• online listing patterns that correlate to recent theft incidents

This is one reason CORCA’s marketplace focus is directionally right: resale is part of the crime scene.

A 90-day anti-theft plan for transportation, logistics, and procurement leaders

You don’t need a massive program to get meaningful risk reduction quickly. The teams that make progress treat cargo theft like a measurable funnel: attempted fraud → prevented events → losses.

Days 1–30: tighten the “front door” (tender + identity)

Start by reducing how often bad actors can get onto your loads.

• Require multi-factor verification for any ship-to change or appointment change
• Implement a “two-channel” confirmation rule (example: email change must be confirmed by phone to a known number)
• Score carriers/brokers using a simple risk model (new entity, domain age, mismatch in addresses, bank changes)
• Create a do-not-use and watchlist process that’s actually enforced in the TMS

Days 31–60: instrument high-value freight with real-time controls

Pick a lane first: high-theft lanes, high-value SKUs, or repeat locations.

• Add real-time location monitoring for high-risk shipments
• Define 5–7 “red flag” triggers (route deviation, unexpected dwell, geofence breach)
• Build a playbook: who gets called, what gets verified, and what gets stopped

The goal isn’t perfect detection. It’s faster intervention.

Days 61–90: operationalize AI signals into workflow

AI only creates value when it changes decisions.

• Route alerts into the tools teams already live in (TMS queue, ticketing, SOC inbox)
• Assign owners and SLAs for each alert type
• Track three metrics weekly:
  1. attempted fraud volume
  2. prevented incidents
  3. time-to-verify (from alert to decision)

If you can cut time-to-verify from hours to minutes, you’ll stop more theft than any single device or checklist.

Common questions leaders ask about AI cargo theft prevention

“Will AI create too many false positives?”

It will if you treat it like a siren instead of a scoring system. The workable approach is:

• risk scoring (0–100) instead of binary alerts
• higher sensitivity for high-value shipments
• continuous tuning based on outcomes (prevented vs. cleared)

False positives become manageable when you connect them to workflow and SLAs.

“Do we need new hardware to use AI?”

Not necessarily. Many high-impact signals are already digital:

• tender history
• carrier identity data
• email/domain patterns n- appointment changes
• POD/BOL documents

Hardware (locks, sensors) helps. But if your documentation and identity controls are weak, hardware becomes a speed bump.

“How does this fit into AI in supply chain and procurement?”

Cargo theft prevention is procurement’s problem because it’s supplier risk + service continuity + total landed cost. AI that improves fraud detection also improves vendor governance, inventory planning, and claims management.

Where this is headed in 2026: security becomes a shared data layer

The most interesting part of the CORCA debate isn’t partisan. It’s structural: policymakers are acknowledging that organized theft is a network problem, and networks get fought with coordinated intelligence.

Companies should take the hint. The organizations that reduce cargo theft in 2026 won’t treat security as a bolt-on. They’ll treat it as a shared data layer across procurement, transportation, warehouse ops, and retail channels.

If you’re building an AI roadmap for supply chain and procurement, cargo theft is one of the highest-ROI places to start because the math is blunt: fewer incidents, fewer expedites, fewer claims, fewer customer failures.

If you want a practical next step, audit one thing this week: How many shipment-critical changes (carrier identity, ship-to address, appointment time, banking/remit-to) can be made with only an email? If the answer is “too many,” you’ve found your first fix.