Supply Chain Analytics Pulse
The New Cost of Picking the Wrong Carrier
August 2026 | Supply Chain Analytics Pulse
In June 2026, the average U.S. dry van spot rate did something it hadn’t done since February 2022: it rose above the contract rate. Tender rejections hit 17.55%, the highest level in four years.
Three weeks earlier, the U.S. Supreme Court had ruled that freight brokers can be sued under state law for carelessly choosing an unsafe carrier. And across the industry, fraud investigators were closing out 2025 with cargo-crime losses near $725 million, up 60% year over year.
None of these three developments made headlines together. But put next to each other, they describe the same moment from three different angles: the decision of which carrier to use just got harder to make well, and more expensive to make badly.
01 Three Forces, One Decision
Capacity is turning for the first time in years
From 2022 through most of 2025, trucking capacity ran well ahead of freight demand. Carrier counts had ballooned during the pandemic-era boom, and the resulting oversupply pushed rates down for nearly four straight years, the longest freight recession most shippers had ever managed through. That gave buyers enormous leverage: if one carrier’s price or terms weren’t ideal, ten more were waiting.
That leverage is disappearing. According to DAT Freight & Analytics, the national average dry van spot rate crossed above the contract rate in June 2026 for the first time since February 2022, with spot rates briefly touching $3.83 per mile. Ryder and FreightWaves’ June State of Transportation report put tender rejection rates above 15%. Reefer and flatbed segments show the same pattern.
The mechanics matter here: when carriers can earn more chasing spot loads than honoring contracted rates, they reject contracted tenders. Shippers scramble to fill the gap, often with whichever carrier is available on short notice.
The legal shield brokers relied on just narrowed
On May 14, 2026, the U.S. Supreme Court issued a unanimous decision in Montgomery v. Caribe Transport II, LLC, holding that a federal transportation law does not automatically shield brokers from state negligent-selection lawsuits when a carrier they chose turns out to be unsafe. To be precise about what that does and doesn’t mean: the Court didn’t rule on anyone’s guilt, it removed a procedural defense that used to get these claims dismissed early, before discovery. The practical effect is that negligent-selection claims against brokers are now harder to dismiss nationwide, and legal commentary suggests the same reasoning could plausibly extend to other intermediaries that select carriers, including 3PLs and digital freight-matching platforms, though that hasn’t yet been tested in court.
Fraud is rising exactly when vetting is hardest to do carefully
The third force is less visible in boardrooms but well documented in industry data. According to Verisk CargoNet, U.S. supply chain crime losses reached roughly $725 million in 2025, up 60% from 2024, with the average loss per incident climbing to $273,990. CargoNet separately reports that “strategic theft”, fraud and identity-based schemes, as opposed to physical break-ins has risen roughly 1,500% since 2021.
Licensed freight broker based in San Antonio, had its identity stolen by overseas criminals who spoofed its email domain and logo, then brokered real loads to unsuspecting carriers under their name. One six-figure shipment of energy drinks was rerouted more than a thousand miles before anyone realized the company that had booked it wasn’t real. The fraudulent entity was even added to the FMCSA’s public SAFER safety-rating database alongside the legitimate one, and owner Adam Blanchard testified that getting it removed proved difficult.
Buyers hold contracts, and audit rights, with their Tier 1 suppliers. Almost none of that formal standing extends to Tier 2 or Tier 3. A visibility platform has nothing to connect to below the purchase order boundary, because the purchase order boundary is exactly where the enrolled, contracted relationship ends.
02 What the Research Shows
On detection performance
May 2026 study by Hayes and colleagues, published via a machine learning and behavioral analytics framework for supply chain fraud, combined graph neural networks with behavioral pattern analysis and reported 0.94 precision and 0.91 recall in identifying fraudulent transactions, a 34% reduction in false positives compared to standalone models. Notably, the behavioral component surfaced collusive fraud rings involving shell vendors and inflated invoicing that traditional rule-based checks had missed entirely. Pattern-based models that update continuously can catch coordinated fraud that this kind of one-time check will never see, simply because they keep watching after the initial check is done.
94%
91%
recall in indetifying fraud
34%
reduction in false positive flags
On legal treatment of automated decisions
The law is moving faster than many logistics organizations may have registered. California’s AB 316, effective January 1, 2026, prohibits a company from defending itself by arguing that an AI system “autonomously” caused the harm: a company that deploys, modifies, or uses an AI tool cannot point to the tool as the responsible party. A June 2026 analysis in the Berkeley Technology Law Journal goes further, arguing that liability frameworks built around a single AI system don’t hold up well once multiple AI agents interact, for instance, a shipper’s procurement agent negotiating with a carrier’s booking agent, because those handoffs are typically unlogged and difficult to reconstruct after something goes wrong. NIST’s AI Agent Standards Initiative, launched in February 2026, has identified agent identity and traceability as a priority precisely because of this gap. A useful, non-freight precedent is Mobley v. Workday, in which a plaintiff argued that an employer couldn’t avoid discrimination liability simply because an algorithm made the screening decision; courts have shown little appetite for treating “the algorithm decided” as a standalone defense.
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03 How the Industry is Responding
Two proof points and one cautionary tale — chosen because they span three different sub-tier verification methods and three different outcomes.
BrokageAI Automations
C. H. Robinson: Automating the Decision the Courts are Scrutinizing
C.H. Robinson occupies an unusual position in this story: it’s the named broker in Montgomery, and simultaneously one of the industry’s most visible adopters of AI in the exact decision the case is about. The company has deployed more than 30 AI agents handling over 3 million shipment-related tasks through what it calls its Always-On Logistics Planner, and its AI truckload optimization product explicitly folds carrier selection into a continuous decision engine, evaluating carrier performance, lane conditions, and market dynamics on an ongoing basis rather than relying on a static routing guide.
Whatever the outcome of the underlying litigation, the pairing is instructive: the same organization facing the industry’s clearest signal that carrier selection now carries real legal exposure is also betting that continuous, data-driven selection is the better way to make that decision.
30+
3M
shipment related tasks handled
3PLHuman-AI Balance
DHL Supply Chain: Free People for the Judgement Calls
At the Manifest 2026 conference, DHL Supply Chain’s VP of integrated transportation described a more incremental path: AI agents now handle appointment scheduling and much of exception management, which frees experienced staff to focus on the calls that genuinely require judgment. It’s a useful counterpoint to the “full automation” narrative: DHL’s public framing treats AI as a way to protect human attention for higher-stakes decisions, not replace the decision-maker.
ComplianceRisk Tooling
A Vetting-Technology Sector has Emerged Specifically for this Problem
A cluster of companies now exists to solve exactly the gap this edition describes: continuous, defensible carrier verification rather than one-time onboarding checks. Highway’s carrier-identity platform reportedly blocked around 2 million fraudulent emails in 2025, up 117% year over year, along with 8.5 million spoofed phone numbers. Other platforms, including Carrier Assure, Descartes’ MyCarrierPortal, and various RMIS providers, continuously monitor FMCSA safety data, insurance status, and identity signals rather than checking them once at onboarding and assuming they hold.
2M
117%
8.5M
spoofed phone numbers
04 Organizational Readiness Check
If most of your answers sit in Levels 1–2, the current market conditions (tight capacity, active fraud, sharpened legal exposure) describe real risk sitting inside a normal-looking process, not a hypothetical one.
| Dimension | Level 1 — Ad Hoc | Level 2 — Developing | Level 3 — Managed | Level 4 — Defensible |
|---|---|---|---|---|
| Safety data checks | Checked informally, if at all, at onboarding | Checked once at onboarding via FMCSA lookup | Re-checked periodically (e.g., quarterly) | Continuously monitored with automated alerts on rating changes |
| Identity verification | Assumed legitimate based on paperwork received | Manual verification of MC/DOT number only | Cross-checked against multiple identity signals | Continuous identity monitoring integrated into tender workflow |
| Documentation trail | No record of why a carrier was chosen | Rate and availability recorded, rationale not | Selection rationale recorded inconsistently | Every selection decision timestamped and auditable |
| Ownership | No one owns carrier-selection risk explicitly | Sits informally with procurement or dispatch | Named owner exists but no formal escalation path | Clear governance with defined executive accountability |
| AI/automation oversight | No automation in carrier selection | Automation exists but undocumented decision logic | Automated recommendations, human sign-off required | Full audit trail of automated decisions, human-in-the-loop on exceptions |
05 What to do Next: Choose Your Perspective
Click on the perspective you want to analyze – executives or analysts.
Analyst View
Build a carrier risk score that sits next to your rate comparison, not separate from it.
✔ If your team already runs cost comparisons across LSPs during tenders, the safety and fraud-risk profile of each carrier belongs in the same view, updated on the same cadence.
Move from point-in-time to continuous monitoring.
✔ A carrier’s FMCSA safety rating, insurance status, and identity signals can all change between onboarding and the tenth load you give them. is.
Start logging selection rationale, not just selection outcomes.
✔ A simple timestamped note (why this carrier, based on what data, at what point) creates a documentation trail that a purely automated system needs just as much as a human decision-maker does.
Map what AI can decide alone versus what needs human sign-off.
✔ If AI or automation already influences carrier selection, document that boundary explicitly rather than leaving it assumed.
Executive View
Assign explicit ownership of carrier-selection risk.
✔ In many organizations, this decision is made thousands of times a week with no formal risk-governance layer above it.
Revisit insurance coverage assumptions.
✔ The FAAAA sets minimum insurance requirements for carriers but not for brokers or 3PLs; confirm your coverage reflects the post-Montgomery landscape.
Treat AI-assisted procurement as a governance question, not just an efficiency one.
✔ Confirm there’s a human checkpoint before a new or unfamiliar carrier is used for the first time.
Budget for the capacity shift, not just the liability shift.
✔ Tender rejection rates at four-year highs mean carrier options are narrowing at the exact moment rigor is most needed.
06 Conclusion
None of these three forces created the others. But they’re now converging on a single, frequently repeated decision that most organizations have treated as low-stakes for a long time: which carrier gets the load. The tools to make that decision more rigorously already exist.
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