Paste the code into any HTML page or a WordPress Custom HTML block. The frame resizes to its content automatically.
Free to embed under CC BY 4.0 with attribution to Axis Intelligence Research.
Axis Intelligence Research · co-author Mia Scarlett · updated October 26, 2026
AI in Logistics Statistics 2026
Freight handled per employee, AI disclosure in results filings, adoption and trust surveys, and the U.S. logistics labor mix — every figure traced to the organization that produced it.
10 charts · 3 tables · 264 sourced rows · CC BY 4.0
LPDR · C.H. Robinson NAST
114.8Q2 2026
Logistics Productivity Decoupling Ratio: +1.5% truckload and LTL volume with 11.6% fewer average employees. 100 = freight and staff move in step.
Headcount
−34.5%
C.H. Robinson, Dec 2022 → Jun 2026 · 17,399 to 11,388
LATS
1.3/ 4
Mean Logistics AI Transparency Score, 10 listed logistics companies
High trust in AI
7%
Logistics professionals, 2026 · while 65% use AI at work
Planners per 100 clerks
31.3
U.S. logistics office mix, May 2025 · 24.2 in May 2022
SECC.H. Robinson, J.B. Hunt, UPS filings to Oct 15, 2026IRExpeditors, RXO, GXO, FedEx, DSV, Kuehne+Nagel, DHL results Jun–Aug 2026BLSOEWS May 2022 & May 2025SURVEY35th Annual Study of Logistics and Transportation Trends Sep 2026SURVEYMHI & Deloitte 2026 reportSURVEYGartner Sep 24, 2026
LPDR = (1 + volume Δ) ÷ (1 + headcount Δ) × 100. C.H. Robinson NAST: 1.015 ÷ 0.884 × 100 = 114.8. Volume and headcount come from the same company, segment and period.
Reading
The top two readings belong to DSV, and the driver is the Schenker merger, not AI. Excluding it, C.H. Robinson holds the three highest scores, and J.B. Hunt’s brokerage is the one line staffing ahead of loads.
Points above the diagonal handle more freight per employee
8 business lines
Axis Intelligence Research from company filings. Diagonal = parity (volume and headcount change by the same percentage). Headcount basis: average (C.H. Robinson), period-end (Expeditors, J.B. Hunt, DSV).
LPDR ranking
Index, 100 = parity
Orange bars flag the DSV readings, whose Q2 2025 base includes Schenker for only part of the quarter.
J.B. Hunt: 1.215 ÷ 1.282 × 100 = 94.8. Loads per employee 164,462 ÷ 722 = 227.8, down from 135,309 ÷ 563 = 240.3.
Reading
J.B. Hunt’s brokerage is not failing: revenue per load rose 29.2% to $2,638. It is staffing ahead of volume. Expeditors’ ocean line should move after its Global Technology restructuring lands in Q3.
Source
Company filings as listed. Expeditors and DSV headcount are period-end FTE; Expeditors reports one company-wide count for both lines.
Integrity notes · disclosed, not smoothed
DSV readings are acquisition-affectedDSV completed its purchase of Schenker at the end of April 2025, so Q2 2025 volume includes Schenker for part of the quarter. DSV reports more than 8,000 white-collar FTE removed since integration began. Published and flagged, not ranked as an AI effect.
C.H. Robinson’s 2022 base includes a divested unitThe 17,399 employees at December 31, 2022 include Europe Surface Transportation, divested February 1, 2025. The −34.5% headcount change is stated with that caveat everywhere it appears.
“Over 60%” productivity is company-reportedC.H. Robinson credits its Lean AI strategy with productivity gains of more than 60% since end-2022 in NAST and Global Forwarding; the calculation is not disclosed. LPDR is the independent check from filed figures.
02
The C.H. Robinson case
The one broker publishing headcount, volume and task-level AI metrics together
Employees · Dec 2022 to Jun 2026
Period-end headcount
−6,011 people
C.H. Robinson Form 10-K fiscal 2022, Q4 2025 and Q2 2026 earnings releases. December 2022 includes the Europe Surface Transportation business divested in February 2025.
Q2 2025 → Q2 2026 ledger
Company-reported inputs; derived lines by Axis
Average employeesConsolidated
12,858
→
11,471
−10.8%
Adj. gross profit / employeeAnnualized, $K
215.7
→
257.3
+19.3%
NAST AGP / employeeQuarterly change
+22.8%
Adjusted operating marginConsolidated
31.1%
→
34.7%
+3.6 pts
NAST volume vs marketCass Freight Shipment Index
−3.3%
vs
+1.5%
share gain
Adjusted gross profit (AGP) = revenue after purchased transportation, plus amortization of internally developed software. 737,966 ÷ 11,471 × 4 = $257.3K.
What the AI agents do · company-reported task metrics
C.H. Robinson newsroom, March 12, 2026 · on-time and speed figures from truckload shipments Jan 2024–Jan 2026
“Hundreds” of agents
32sec
Truckload price quote delivered
90sec
Order processed end to end
42,000
Locations with automated appointment scheduling
−42%
Unnecessary return trips from missed pickups
4×
Faster booking of AI-recommended loads
Range
On-time pickups improved 7% on average and up to 35%; speed to market up to 11% faster on average and as much as 23%.
Reading
The missing number across the industry is the touchless rate: the share of quotes, orders and appointments completed with no human step. Until a broker publishes it, task speed describes capability, not the cost line.
Source
C.H. Robinson newsroom post, March 12, 2026. All figures company-reported. No other large broker publishes comparable task timings.
03
Who discloses the AI dividend
Logistics AI Transparency Score (LATS) · Axis proprietary metric · as of October 26, 2026
One point per disclosure; risk-factor boilerplate scores zero
Company
Document scored
A · AI named
B · AI gain quantified
C · Currency value
D · Headcount y/y
LATS
Sample of 10
Points earned 13 of 40
7
2
1
4
Mean 1.3
Formula
LATS = A + B + C + D, each 0 or 1. A: AI program named in body text. B: AI-linked productivity figure. C: currency value of AI benefit. D: headcount with prior-year comparison.
Reading
Seven of ten mention AI; two quantify a gain; one prices it. A company that never names a number can never miss one, so investors pricing an AI margin story should weight disclosure accordingly.
Source
Axis Intelligence Research scoring of each company’s latest results release or presentation. Newsroom posts and conference remarks are not scored.
Kuehne+Nagel AI target · CHF millions
Stated 5% on the white-collar base vs the stated value
Gap 15–65
Kuehne+Nagel H1 2026 analyst presentation: 5% productivity across 25,000+ white-collar FTE, cost base CHF 1.7bn, CHF 100–150m annualized uplift in 2027. 0.05 × 1,700 = 85; target = 5.9–8.8% of the base.
Where the disclosure stops
Companies meeting each LATS criterion, of 10
Axis Intelligence Research, LATS as of October 26, 2026. Disclosure narrows at each step from naming AI to pricing it.
04
Adoption and governance
Two 2026 surveys, read in full
2025 → 2026 · logistics organizations and professionals
35th Annual Study of Logistics and Transportation Trends, September 2026
Sanctioned use +31 pts
0%25%50%75%
20252026, rising2026, falling
Formula
Active adopters 43 − 16 = +27 pts. Approved use 47 − 16 = +31 pts. No formal AI position 32 − 55 = −23 pts.
Reading
Approval moved more than usage. Sanctioned use is what changes cost lines, because a process owner signed off; the 65% headline includes people using AI without permission.
Source
Logistics Management with Mississippi State University, Georgia College and State University and the University of Central Arkansas.
41% or 72%? One survey, two questions
2026 MHI Annual Industry Report (MHI and Deloitte), 500+ supply chain professionals, late 2025
Resolved from the full report
Technology adoption · AI in use today
41%
A further 47% expect to adopt AI within five years. Together they form the 88% figure quoted in press coverage.
≠
Use cases · current or planned within 2 years
72%
28% are not leveraging AI now or in a planned use case. The other 72% named at least one, current or planned.
Formula
41 + 47 = 88% within five years. 100 − 28 = 72% using or planning an AI use case within two years.
Reading
41% is the installed base; 72% is the installed base plus the two-year plan. Neither measures depth: no single use case reaches more than a third of organizations.
Source
2026 MHI Annual Industry Report, key findings and Figure 6. Prior-year 30% as stated by MHI’s CEO at MODEX 2026.
Supply chain technology · in use today vs expected within 5 years
Share of organizations
2026 MHI Annual Industry Report, Figure 6. “Within 5 years” counts organizations not yet using the technology. Humanoid robotics moves from 4% to a planned 28%.
05
Trust, fraud and readiness
What logistics teams believe about AI outputs
Very or extremely concerned · 2026
Share of logistics professionals
AI-forged documents 53%
35th Annual Study of Logistics and Transportation Trends. Double brokering: illegal re-brokering of a load without the shipper’s knowledge. Phantom load: a fake load posting used to extract payment or information.
Trust in AI outputs
Logistics professionals, 2026
55%
38%
High / very high 7%Moderate 55%Low / none 38%
AI rank
7 / 7
Last of seven data and information sources evaluated
Very well prepared
15%
Clear strategies and resources in place
Use vs trust
65%use AI at work · only7%trust it highly
Professionals act on AI output after human review: the verification step is part of the workflow, not a delay in it.
06
Spending versus delegation
Budgets are large; autonomous decisions are rare
Supply chain planning automation · spent vs delegated
Gartner, n = 243 senior leaders at companies with $500M+ revenue, fieldwork Nov 11–Dec 18, 2025
Spent ≥ $3 million
83%
of surveyed organizations on planning automation, including AI
Spent $3–10 million
51%
the modal spending band
Autonomous by 2030
5%
will make at least 10% of planning decisions autonomously, Gartner forecasts
Budgets
MHI: 56% raise supply chain innovation spending, 52% plan over $1M, 17% over $10M.
Reading
Organizations are buying decision support far faster than they hand over decisions. A planning system whose every output a planner still signs is a cost line without its matching saving.
Source
Gartner press release, September 24, 2026; 2026 MHI Annual Industry Report.
AI use cases · current or planned within 2 years
Share of organizations
2026 MHI Annual Industry Report. 28% are not leveraging AI in any of these use cases.
Primary barrier to AI adoption
Share naming it as the top barrier
Talent issues
90%
of organizations affected
Cyber risk
88%
cite it as a challenge
2026 MHI Annual Industry Report. Building a business case leads, ahead of understanding and talent.
07
The U.S. logistics office
Bureau of Labor Statistics, Occupational Employment and Wage Statistics · May 2022 vs May 2025
Employment change by occupation · May 2022 → May 2025
Percent; dashed line = all U.S. occupations (+5.1%)
BLS OEWS national files, cross-industry. Changes calculated by Axis Intelligence Research.
Planners and managers per 100 clerks
Axis Intelligence Research calculation
24.2
→
31.3
May 2022 to May 2025. Clerical desk −2.0%; planning and management +26.6%.
Change = (May 2025 ÷ May 2022) − 1. OEWS estimates pool three years of survey panels, so changes show direction and size of the shift rather than an exact annual count.
Reading
The shrinking roles are the ones broker AI agents target by name: keying orders, booking dock appointments, chasing updates. The growing roles decide which carrier, which lane, which inventory position.
Source
U.S. Bureau of Labor Statistics, OEWS national files for May 2022 and May 2025.