Trust but Verify: Freight Brokers Rank Last as Logistics Trust Hits New Low

Only 16% of logistics professionals express high or very high trust in freight brokers — the lowest rating of any partner type in the industry — according to the 35th Annual Study of Logistics and Transportation Trends. Asset-based carriers and shippers/customers topped the trust table at roughly 53% each. Freight forwarders (33%) and technology vendors (31%) sat in the middle, while third-party logistics providers managed just 23%.

The study drew on 230 industry professionals. Nearly three-quarters have 15 or more years of experience, and 76% hold manager-level titles or higher. Participants spanned manufacturing, asset-based transportation, transportation services, wholesale and distribution, technology, warehousing and 3PL operations, retail, and government.

Is trust in the industry rising or falling?

Respondents split three ways on how overall trust among trading partners compares with five years ago. Thirty-nine percent said trust had deteriorated, another 39% said it stayed about the same, and 22% said it improved. Those seeing deterioration outnumbered optimists nearly two to one.

The survey landed shortly after the May 2026 U.S. Supreme Court ruling in Montgomery v. Caribe Transport II, which held that certain state negligent-selection claims against freight brokers are not preempted by federal law. The study did not ask whether the ruling affected trust ratings. But the timing matters.

The decision unsettled longstanding assumptions about risk and liability among trading partners. Brokers now face greater pressure to demonstrate effective carrier selection and monitoring procedures, while shippers may demand verification that those processes actually work.

Are verification methods keeping pace?

Barely. Contractual requirements — insurance certificates and letters of authority — remain the most frequently reported verification method. Manual processes such as callbacks and document reviews follow, along with checks of FMCSA or other regulatory databases. AI-assisted fraud detection tools ranked last, despite the changing risk dynamics.

How fast is AI adoption moving?

Fast, by every measure the study tracks. The share of passive AI adopters — traditionalists, gatekeepers, and observers — fell from 64% in 2025 to 30% in 2026. Active adopters, the optimizers and pioneers, jumped from 16% to 43%.

Employee use climbed in parallel. Sanctioned use, with a manager's or organization's knowledge and approval, rose from 16% to 47%. Overall use, approved or not, increased from 45% to 65%. Formal or informal training and guidance grew from 16% to 47%. The share of organizations actively encouraging or allowing employee use rose from 39% to 59%, while those with no formal position fell from 55% to 32%.

But adoption is not confidence. Fifty-five percent of respondents reported moderate trust in AI-generated outputs and recommendations. Thirty-eight percent reported low or no trust. Only 7% reported high or very high trust. AI also ranked last among the seven data and information sources the study evaluated.

Last year's study identified a gap between knowing and doing: leaders understood the disruptive forces reshaping the industry but had not moved to execution. That gap is narrowing, particularly in AI adoption, employee usage, organizational support, and training. Execution, though, has exposed a new one: organizations are adopting AI faster than they are building the confidence, accountability, and verification needed to support it.

What threats are driving the trust deficit?

Phishing and cyberattacks targeting logistics operations generate the greatest concern, with 62% of respondents very or extremely concerned. AI-generated or fabricated documents ranked next at 53%.

• Double brokering: 47% very or extremely concerned
• Carrier identity fraud: 45%
• Fictitious pickups or phantom loads: 43%
• Invoice or billing fraud: 42%

AI makes information easier to produce — and trust harder to earn. The same technology that helps organizations analyze information and decide faster can also create increasingly convincing fraudulent documents, identities, and communications.

Organizations are responding. Employee training in fraud awareness and data verification is the most frequently reported mitigation strategy. Others have implemented or upgraded fraud-detection and carrier-vetting tools, added human review requirements for AI-assisted decisions, and established formal policies for verifying AI-generated content.

Is AI already disrupting hiring?

Yes. Thirty-four percent of respondents said AI-generated resumes, cover letters, and applications had reduced their confidence in evaluating candidates. Only 7% said their organization had effectively adapted hiring processes to the new AI environment.

That hits an industry still struggling for talent. The industry's image problem remained the leading attraction challenge in 2026, at 35.6% of reported selections, nearly unchanged from 2025. Demanding work ranked second, followed by difficulty finding qualified candidates and limited career paths. Structured interviews, work samples, internships, and verified credentials may grow more important as employers try to distinguish presentation from performance.

How strong is the operating backdrop?

Improving. Average self-ratings against competitors rose across all five performance measures compared with 2025. Customer satisfaction climbed from 3.93 to 4.03, competitive position from 3.56 to 3.65, revenue growth from 3.54 to 3.62, return on assets from 3.50 to 3.56, and profitability from 3.53 to 3.54.

AI remained the top-ranked force expected to shape the industry over the next three to five years, ahead of economic uncertainty, workforce shortages, and government policies. Transportation capacity and infrastructure constraints moved from seventh to fifth, signaling concern that recent capacity constraints may continue unabated.

Confidence is rising too. The share of respondents describing their organization as very or somewhat prepared increased from 63% to 77%. Still, only 15% said they were very well-prepared with clear strategies and resources, while 62% admitted to gaps.

What should managers do now?

The study prescribes turning "trust, but verify" into an operating practice. Key actions:

• Align verification with consequences. A routine planning recommendation does not carry the risk of changing a carrier's payment information or releasing a high-value shipment. Verify what matters most.
• Treat partner trust as a managed process. Onboarding should define what gets verified, who owns it, how often it is reviewed, and what triggers extra scrutiny.
• Match AI oversight to decision risk. Low-risk uses need little review; recommendations touching inventory, routing, capacity, pricing, hiring, safety, or legal exposure deserve detailed analysis.
• Measure whether controls work. Track AI override frequency, error types, verification time, and prevented losses, not documents reviewed.
• Hire people who question answers. Scenario-based interviews, verified credentials, and internship experience matter more than polished resumes.
• Use the current window. Improving performance gives firms room to strengthen controls before the next major fraud event, cyberattack, or AI-related failure.

The bottom line from the researchers: no supply chain can operate if every transaction begins from suspicion, but trust can no longer rest on history, reputation, or confidence in a system's output. The best-prepared organizations will be those that know what they trust, why they trust it, and when the evidence requires verification — and with moderate trust in AI at 55% and broker trust at 16%, verification requirements look set to tighten before they loosen.