Gini Loh System Tools

AI Automation Index

Will AI Replace Light Truck Drivers?

Task-level automation exposure for Light Truck Drivers: 13 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

43% weighted task index

13 of 13 tasks scored

Median Salary

$44,860 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Very High

983,300 people hold this job — size, not growth

Projected 2025–35

+6.3% employment change

107,200 openings a year · BLS line item

Pay by state

BLS OEWS publishes 54 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$24,430 – $57,190

Highest medians

Alaska $57,190
District of Columbia $49,330
Washington $49,070
Minnesota $48,880
Colorado $48,410

Lowest medians

Puerto Rico $24,430
Guam $25,100
Virgin Islands $31,180
Arkansas $37,080
South Carolina $37,680

State figures come from the 53-3033 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 43%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 44%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 9%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 15%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 21/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

13 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 42%

5 tasks

Medium exposure (≥ 35%) 15%

2 tasks

Low exposure (below 35%) 43%

6 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#8615 · Core · 55% automatable

Obey traffic laws and follow established traffic and transportation procedures.

decision support — AI can guide safety procedures but human executes driving

Follow safety procedures for vehicle operation.
#8617 · Core · 65% automatable

Report any mechanical problems encountered with vehicles.

text generation — Reporting malfunctions is structured information relay

Report vehicle or equipment malfunctions.
#8620 · Core · 80% automatable

Verify the contents of inventory loads against shipping papers.

information retrieval — Spec verification against references, human confirms edge cases

Verify information or specifications.
#8616 · Core · 14% automatable

Inspect and maintain vehicle supplies and equipment, such as gas, oil, water, tires, lights, or brakes, to ensure that vehicles are in proper working condition.

visual inspection — Vehicle inspection is physical on-site work

Inspect motor vehicles. Maintain vehicles in good working condition.
#8623 · Core · 67% automatable

Read maps and follow written or verbal geographic directions.

information retrieval — Map route reading strong, real-world routing human

Read maps to determine routes. Receive information or instructions for performing work assignments.
#8619 · Core · 4% automatable

Load and unload trucks, vans, or automobiles.

physical manipulation — Physical lifting and loading of shipments

Load shipments, belongings, or materials.
#8618 · Core · 20% automatable

Present bills and receipts and collect payments for goods delivered or loaded.

physical manipulation — Collecting fares physically from customers

Collect fares or payment from customers.
#8622 · Core · 82% automatable

Maintain records, such as vehicle logs, records of cargo, or billing statements, in accordance with regulations.

text generation — Log delivery details into structured records

Record details of deliveries or shipments.
#8626 · Core · 5% automatable

Drive vehicles with capacities under three tons to transport materials to and from specified destinations, such as railroad stations, plants, residences, offices, or within industrial yards.

physical manipulation — Hands-on vehicle and equipment operation

Operate vehicles or material-moving equipment.
#8621 · Supplemental · 70% automatable

Turn in receipts and money received from deliveries.

data analysis — Billing and payment processing largely automated

Process customer bills or payments.
#8628 · Supplemental · 10% automatable

Use and maintain the tools or equipment found on commercial vehicles, such as weighing or measuring devices.

physical manipulation — Physical maintenance of machinery

Maintain work equipment or machinery.
#8624 · Supplemental · 55% automatable

Report delays, accidents, or other traffic and transportation situations to bases or other vehicles, using telephones or mobile two-way radios.

interpersonal — Emergency notification needs live accountable delivery

Notify others of emergencies, problems, or hazards.
#8629 · Supplemental · 8% automatable

Perform emergency repairs, such as changing tires or installing light bulbs, fuses, tire chains, or spark plugs.

physical manipulation — Physical vehicle maintenance work

Maintain vehicles in good working condition.
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Community Sentiment

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Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
  3. 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
  4. 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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