Inspect loads to ensure that cargo is secure.[2]
Where your edge is
Time Machine
Heavy and Tractor-Trailer Truck Drivers
Scrub through 140 years of this role's history — from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.
19001925195019752000now
Drag the dot, click anywhere on the track, or use ← → arrow keys (Shift for 10-year jumps, PgUp/PgDn for 25).
2026
Known today as Heavy and Tractor-Trailer Truck Driver (SOC 53-3032)
US Employment
2.24M
BLS OEWS May 2024 estimate for SOC 53-3032, sourced from O*NET which reflects the same BLS establishment-survey figure. Note: this is a notably higher figure than the May 2023 count; the jump may reflect methodology changes or survey year timing. Both values are from official BLS sources.
Median Annual Wage
$57,440
Source: BLS-OEWS
Tool of the era · Aurora + Kodiak — real commercial driverless freight on US highways
May 1, 2025: Aurora Innovation launched paid commercial driverless trucking between Dallas and Houston (120-mile I-45 corridor) with Hirschbach Motor Lines and Uber Freight — the first revenue-generating, no-driver-in-cab long-haul service on a US interstate highway. Aurora reported 1,200+ autonomous miles in a single run by May 2025 and over 10,000 customer loads in supervised mode across 3 million autonomous miles pre-launch. Kodiak AI separately delivered the first customer-owned driverless trucks (to Atlas Energy Solutions, Permian Basin off-road routes) in December 2024. Both represent the end of the proof-of-concept phase and the start of actual commercial deployment — measured in loads and revenue, not press releases.
Aurora's 2025 commercial fleet is ~30 trucks; Kodiak's is 4+ in the Permian. At this scale, employment displacement is negligible. The displacement risk is in the scaling trajectory: if unit economics prove out, the fleet size and route count double annually.
Beat · 2025
Aurora Innovation begins paid commercial driverless trucking on the Dallas-Houston I-45 corridor in May 2025 — the first revenue-generating, driver-absent long-haul autonomous service on a US interstate. Aurora reports completing over 10,000 customer loads in supervised mode across 3 million autonomous miles before going driverless. Fleet size: ~30 trucks. The commercial era of autonomous highway freight has begun, though at a scale that affects zero drivers' employment today.
Projection cone · present → 2034
What credible sources project
Scrub the slider past now to anchor each scenario on the scrubber. The spread you see below is the range of futures credible sources project for this role.
ATA counter-scenario: driver shortage (2024)
→ 2028
+7%
The American Trucking Associations' workforce projections estimate the industry will be short more than 80,000 drivers in 2024, growing to 160,000+ by 2028, driven by retirements, freight demand growth, and difficulty attracting younger workers. This is the structural counter-narrative to the displacement story: if autonomous trucks scale slowly, the demand/supply gap grows *faster* than displacement, meaning net employment is positive. ATA is not a neutral research organization (it lobbies against autonomous vehicle liability rules) but its shortage model uses BLS demand forecasts as inputs.
BLS Occupational Outlook 2024-34
→ 2034
+4%
BLS Employment Projections — industry-occupation matrix + labor productivity assumptions. The current published outlook for 53-3032 (2024-34 cycle): +4% employment growth ("About as fast as average"), 2,324,400 projected jobs by 2034 (up from 2,235,100), ~237,600 openings per year. BLS projections do not model the speculative scenario of full autonomy; they model productivity-adjusted demand given current technology trajectories.
Anthropic Economic Index (live observational)
→ 2026
-1%
Direct measurement of Claude API usage by occupation category, January 2026 report. Transportation and Material Moving occupations represent a near-zero share of 1P API traffic — the report explicitly identifies this category as underrepresented in Claude usage relative to workforce share. This is the structural complement to the high LLM exposure of computer programmers: truck driving is nearly zero LLM-affected today in production. The -1% is a marker that this is the "not yet a software story" end of the displacement spectrum; the real disruption vector for 53-3032 is sensor fusion + autonomy stacks, not language models.
Eloundou et al. — "GPTs are GPTs" (2023)
→ 2028
-5%
GPT-4 task-by-task LLM exposure labeling on O*NET tasks for 53-3032. Truck drivers score very low on LLM exposure (β near 0.04-0.07) because the core tasks — physically driving a vehicle, loading/unloading, inspecting equipment — are not text-based tasks an LLM can perform. The important contrast to F&O: Eloundou measures *LLM* exposure specifically, not general automation potential. A self-driving system is not an LLM. The -5% estimate here represents a conservative lower-bound on near-term displacement from AI-augmented software tools (logistics optimization, dispatch, route planning) rather than from autonomous driving itself.
Goldman Sachs autonomous vehicle impact (2017)
→ 2030
-25%
Goldman Sachs' 2017 analysis estimated autonomous vehicles could displace up to 25,000 professional drivers per month once fully deployed at scale — implying ~300,000/year at peak. The -25% figure here represents an intermediate 2030 scenario assuming partial highway autonomy scaled to ~20-30% of long-haul routes by 2030. Goldman's 2023 generative-AI paper (Briggs/Kodnani) separately found Transportation occupations have low LLM task exposure, consistent with Eloundou's finding — the threat is robotics/autonomy, not LLM-based tools.
Frey & Osborne (2013)
→ 2033
-79%
Gaussian-process classifier on O*NET task features — the single most cited long-run displacement estimate for trucking. F&O estimated Heavy and Tractor-Trailer Truck Drivers at 0.79 probability of computerisation (out of 702 occupations studied) — among the highest blue-collar scores in the dataset. The 10-20 year horizon cited in F&O maps to roughly 2023-2033. Note: this is *probability of computerisation*, not *projected employment change* — the -79% figure here represents the implied displacement at the stated probability if realized fully, which F&O did not claim would happen. Treat as a ceiling on the pessimistic tail.
Today, in this role
What's shifting in the work right now
The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.
What's changing in your day
Three parts of your work where AI is already doing real lifting — and what stays yours.
Check vehicles to ensure that mechanical, safety, and emergency equipment is in good working order.[2]
Where your edge is
Crank trailer landing gear up or down to safely secure vehicles.[2]
Where your edge is
Present-day sources
Sources
Every claim on this page traces back to one of the following. Updated 2026-05-30.
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