AI Automation Index

Will AI Replace Crossing Guards and Flaggers?

Task-level automation exposure for Crossing Guards and Flaggers: 12 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified

Developed & audited by Gini Loh

Automation Exposure

35% weighted task index

12 of 12 tasks scored

Median Salary

$38,100 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

94,360 people hold this job — size, not growth

Projected 2025–35

+3.5% employment change

17,300 openings a year · BLS line item

Pay by state

BLS OEWS publishes 50 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$25,450 – $60,230

Highest medians

North Dakota $60,230

California $50,610

Washington $48,940

Minnesota $48,100

Oregon $47,110

Lowest medians

Louisiana $25,450

Oklahoma $28,610

Alabama $29,190

Arkansas $30,830

Rhode Island $31,200

State figures come from the 33-9091 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 35%

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

Physical work 41%

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

Judgment & influence 18%

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

Routine administration 8%

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 52/100 High

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

12 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) 14%

2 tasks

Medium exposure (≥ 35%) 46%

6 tasks

Low exposure (below 35%) 41%

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

#11117 · Core · 8% automatable

Direct or escort pedestrians across streets, stopping traffic, as necessary.

situated mobility — Roadside physical assistance in unpredictable settings

Direct vehicle traffic. Assist motorists or pedestrians.

#11118 · Core · 5% automatable

Guide or control vehicular or pedestrian traffic at such places as street and railroad crossings and construction sites.

situated mobility — Directing live traffic requires physical presence

Direct vehicle traffic.

#11116 · Core · 35% automatable

Monitor traffic flow to locate safe gaps through which pedestrians can cross streets.

situated mobility — Managing physical flow of people needs on-site presence

Monitor access or flow of people to prevent problems.

#11119 · Core · 55% automatable

Communicate traffic and crossing rules and other information to students and adults.

interpersonal — Public communication needs accountability and audience trust

Inform the public about policies, services or procedures.

#11122 · Core · 28% automatable

Direct traffic movement or warn of hazards, using signs, flags, lanterns, and hand signals.

interpersonal — Warning individuals is live, relational, accountable

Direct vehicle traffic. Warn individuals about rule violations or safety concerns.

#11120 · Core · 40% automatable

Report unsafe behavior of children to school officials.

interpersonal — Performance and complaint discussions carry accountability

Discuss performance, complaints, or violations with supervisors.

#11121 · Core · 60% automatable

Record license numbers of vehicles disregarding traffic signals, and report infractions to appropriate authorities.

text generation — Recording suspicious objects; human observes and verifies

Record information about suspicious objects. Communicate situation details to appropriate personnel.

#11125 · Supplemental · 10% automatable

Distribute traffic control signs and markers at designated points.

physical manipulation — Hands-on positioning of safety equipment in field

Position safety or support equipment.

#11124 · Supplemental · 50% automatable

Stop speeding vehicles to warn drivers of traffic laws.

interpersonal — Warning individuals is live, relational, accountable

Warn individuals about rule violations or safety concerns.

#11123 · Supplemental · 70% automatable

Learn the location and purpose of street traffic signs within assigned patrol areas.

information retrieval — AI supports study; certification requires human

Maintain professional knowledge or certifications.

#11126 · Supplemental · 42% automatable

Discuss traffic routing plans and control-point locations with superiors.

interpersonal — Arranging operations requires live human negotiation

Confer with others to conduct or arrange operational activities.

#11127 · Supplemental · 55% automatable

Inform drivers of detour routes through construction sites.

information retrieval — Public info provision partly automatable; accountability human

Provide information to the general public.

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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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