AI Automation Index

Will AI Replace Driver/Sales Workers?

Task-level automation exposure for Driver/Sales Workers: 11 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

42% weighted task index

11 of 11 tasks scored

Median Salary

$38,770 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Very High

409,180 people hold this job — size, not growth

Projected 2025–35

+7.9% employment change

45,500 openings a year · BLS line item

Pay by state

BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$20,630 – $48,420

Highest medians

Alaska $48,420

Iowa $47,120

Massachusetts $46,870

Vermont $46,300

California $45,600

Lowest medians

Guam $20,630

Puerto Rico $22,220

South Carolina $22,240

Utah $26,590

Wyoming $26,940

State figures come from the 53-3031 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 42%

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

Physical work 29%

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

Judgment & influence 0%

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

Routine administration 28%

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 32/100 Moderate

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

11 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) 18%

2 tasks

Medium exposure (≥ 35%) 46%

5 tasks

Low exposure (below 35%) 37%

4 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

#3158 · Core · 5% automatable

Drive trucks to deliver such items as food, medical supplies, or newspapers.

physical manipulation — Hands-on vehicle and equipment operation

Operate vehicles or material-moving equipment.

#3156 · Core · 55% automatable

Inform regular customers of new products or services and price changes.

information retrieval — Transport info lookup automatable; live assistance human

Provide transportation information to passengers or customers.

#3161 · Core · 85% automatable

Record sales or delivery information on daily sales or delivery record.

data analysis — Structured transaction data entry and recording

Record details of deliveries or shipments. Record sales or transactions data.

#3155 · Core · 42% automatable

Listen to and resolve customers' complaints regarding products or services.

decision support — AI suggests fixes; human resolves in operations

Resolve issues affecting transportation operations.

#3154 · Core · 54% automatable

Collect money from customers, make change, and record transactions on customer receipts.

data analysis — Structured transaction data entry and recording

Record sales or transactions data. Collect fares or payment from customers.

#3164 · Core · 9% automatable

Maintain trucks and food-dispensing equipment and clean inside of machines that dispense food or beverages.

physical manipulation — Machinery cleaning requires hands-on work

Clean machinery or equipment. Maintain vehicles in good working condition.

#3163 · Supplemental · 32% automatable

Arrange merchandise and sales promotion displays or issue sales promotion materials to customers.

interpersonal — Closing sales requires persuasion and accountability

Sell products or services.

#3159 · Supplemental · 35% automatable

Collect coins from vending machines, refill machines, and remove aged merchandise.

physical manipulation — In-person payment handling; some digital automation

Collect payments for goods or services.

#3157 · Supplemental · 88% automatable

Write customer orders and sales contracts according to company guidelines.

data analysis — Structured transaction data entry and recording

Record sales or transactions data.

#3162 · Supplemental · 42% automatable

Review lists of dealers, customers, or station drops and load trucks.

information retrieval — Review customer records and summarize

Review customer information. Load shipments, belongings, or materials.

#3165 · Supplemental · 32% automatable

Sell food specialties, such as sandwiches and beverages, to office workers and patrons of sports events.

interpersonal — Closing sales requires persuasion and accountability

Sell products or services.

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Community Sentiment

Do you agree?

Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
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. 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. 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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