Skills it runs on
The capabilities O*NET rates most important for this occupation — the human ground the work is built on.
See all skills →Crossing Guards and Flaggers
Occupation · SOC 33-9091.00
Guide or control vehicular or pedestrian traffic at such places as streets, schools, railroad crossings, or construction sites.
Also called: Adult Crossing Guard · Community Service Officer · Crossing Guard · School Crossing Guard · Road Crossing Guard · Substitute Crossing Guard · Campus Supervisor · Construction Site Crossing Guard · Crossing Flagman · Crossing Gateman · Crossing Tender · Crossing Watchman
Job family: Protective Service Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-33-9091-00/context.md directly.
AI work map
A fast read on where AI already shows up in this occupation, where it stays a copilot, where humans remain in the loop, and what the labor market is doing. Built from observed Claude.ai conversations mapped to O*NET tasks and from published research — measures of usage and exposure, not advice or predictions that the job is going away.
Market signal
Independent published positions, read together — not a forecast.
- About average employment outlook (+3.6% by 2034)
- 18,000 openings/yr
- Moderate AI exposure
- Median pay $37,700/yr
- Work is mostly on-site (not teleworkable)
37th-percentile task overlap — yet about 18,000 openings a year (+3.6% projected, BLS) . What exposure means →
AI & job outlook
What today's research says about this occupation's exposure to AI, how AI is actually being used in it, and where employment is headed. These are positions within published studies — measures of exposure and usage, not predictions that this job will disappear.
Exposure to current AI
Each study uses its own scale, so the raw scores are not comparable across rows — the percentile (this job's rank among all U.S. occupations with data) is the comparable figure, and sizes the bars.
| Measure | Rank vs all occupations | Percentile | Score |
|---|---|---|---|
| Overall AI exposure (Felten et al.) Low | 33rd | -0.6 | |
| LLM task exposure, γ (OpenAI / Eloundou) Low | 20th | 0.2 | |
| AI assistant applicability (Microsoft) Moderate | 64th | 0.2 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.1), and including AI-powered software (γ 0.2). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
This job mostly cannot be done remotely (Dingel–Neiman) — its hands-on tasks sit outside what software-based AI reaches.
Historical automation estimate (2013)
A pre-LLM (2013) estimate of how automatable this job is by computerization and robotics. Shown for historical context only — it is not part of any current AI ranking.
Frey–Osborne probability 0.5 · 47th percentile among occupations · Moderate
How AI is actually used in this job
Among measured AI assistant conversations mapped to this occupation (Anthropic Economic Index, 2026-01-15), these task types came up most. These are shares of observed AI conversations — not shares of the job, of worker time, or of what could be automated.
| Communicate traffic and crossing rules and other information to students and adults. | 0.3% |
Job outlook
Independent U.S. Bureau of Labor Statistics employment projection for 2024–2034 — a labor-market forecast, not an AI-impact forecast.
| Outlook | About average · +3.6% by 2034 |
| Projected annual openings | 18,000 |
| Employment 2024 → 2034 | 91,400 → 94,700 |
“Annual openings” counts new jobs plus replacements for workers who leave the occupation, so it can be large even when growth is modest.
Where this work sits on the global GenAI gradient
The ILO's 2025 global study scores generative-AI exposure on the international ISCO-08 occupation system, not US SOC. Bridged through the published (and approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 crosswalk, this US occupation corresponds to the international occupation below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Crossing Guards and Flaggers sits at the 33rd percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure eased from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
20% mean task exposure (2025)
33rd percentile of 427 placed occupations
−1 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Protective Services Workers Not Elsewhere Classified · 5419 | 20% | Not exposed |
Read the whole six-band gradient on the GenAI exposure gradient page. The crosswalk is approximate: a US occupation can map to several international ones, and the ILO scores describe the international occupation, not this exact US role.
Tasks
All 12 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Direct or escort pedestrians across streets, stopping traffic, as necessary. Core · importance 4.8
- Guide or control vehicular or pedestrian traffic at such places as street and railroad crossings and construction sites. Core · importance 4.7
- Monitor traffic flow to locate safe gaps through which pedestrians can cross streets. Core · importance 4.7
- Communicate traffic and crossing rules and other information to students and adults. Core · importance 4.5
- Direct traffic movement or warn of hazards, using signs, flags, lanterns, and hand signals. Core · importance 4.5
- Distribute traffic control signs and markers at designated points. Supplemental · importance 4.3
- Report unsafe behavior of children to school officials. Core · importance 4.3
- Stop speeding vehicles to warn drivers of traffic laws. Supplemental · importance 4.2
- Learn the location and purpose of street traffic signs within assigned patrol areas. Supplemental · importance 4.1
- Record license numbers of vehicles disregarding traffic signals, and report infractions to appropriate authorities. Core · importance 4.0
- Discuss traffic routing plans and control-point locations with superiors. Supplemental · importance 3.8
- Inform drivers of detour routes through construction sites. Supplemental · importance 3.5
Work activities
- Monitor access or flow of people to prevent problems.
- Direct vehicle traffic.
- Assist motorists or pedestrians.
- Inform the public about policies, services or procedures.
- Discuss performance, complaints, or violations with supervisors.
- Record information about suspicious objects.
- Communicate situation details to appropriate personnel.
- Warn individuals about rule violations or safety concerns.
- Maintain professional knowledge or certifications.
- Position safety or support equipment.
- Confer with others to conduct or arrange operational activities.
- Provide information to the general public.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Public Safety and Security | 3.9 | |
| Customer and Personal Service | 3.2 | |
| English Language | 3.1 | |
| Law and Government | 2.4 | |
| Psychology | 2.4 |
Abilities
| Oral Comprehension | 3.5 | |
| Oral Expression | 3.5 | |
| Problem Sensitivity | 3.5 | |
| Selective Attention | 3.1 | |
| Far Vision | 3.1 | |
| Speech Clarity | 3.1 | |
| Deductive Reasoning | 3.0 | |
| Speech Recognition | 3.0 | |
| Inductive Reasoning | 2.9 | |
| Information Ordering | 2.9 | |
| Trunk Strength | 2.9 | |
| Near Vision | 2.9 | |
| Time Sharing | 2.8 | |
| Arm-Hand Steadiness | 2.8 | |
| Reaction Time | 2.8 | |
| Written Comprehension | 2.4 | |
| Written Expression | 2.4 | |
| Category Flexibility | 2.4 | |
| Manual Dexterity | 2.4 | |
| Stamina | 2.4 | |
| Auditory Attention | 2.4 | |
| Perceptual Speed | 2.3 | |
| Multilimb Coordination | 2.3 | |
| Depth Perception | 2.3 |
Essential skills
| Speaking | 3.1 | |
| Active Listening | 2.9 | |
| Monitoring | 2.9 | |
| Critical Thinking | 2.8 | |
| Reading Comprehension | 2.3 | |
| Active Learning | 2.3 |
Transferable skills
| Social Perceptiveness | 3.0 | |
| Coordination | 2.8 | |
| Service Orientation | 2.8 | |
| Judgment and Decision Making | 2.8 | |
| Complex Problem Solving | 2.4 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Tools & technology
| Example | Category | |
|---|---|---|
| Microsoft Word | Word processing software | Hot technology |
| Payroll software | Human resources software | |
| Visual Computer Solutions Crossing Guard Scheduling | Calendar and scheduling software |
Work context
How characteristic each condition is of the job, on O*NET's 1–5 context scale (higher = more present in day-to-day work). Each condition links to how it varies across all occupations.
How to get in
- Job zone
- Zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed
- Education
- Usually requires a high school diploma or GED, though some occupations may not.
- Typical entry-level education
- No formal educational credential · BLS, the typical path — not a requirement
- Related experience
- Some occupations may need little or no previous experience; others require several months to a year of experience. For example, landscaping and groundskeeping workers might require very little training or previous experience, while agricultural equipment operators can benefit from on-the job training.
- Preparation level
- SVP (Below 6.0) — total schooling plus on-the-job experience.
Education of current workers
Share of people in this occupation at each level of education.
| High School Diploma | 72.8% | |
| Less than a High School Diploma | 17.9% | |
| Some College Courses | 6.0% | |
| Post-Secondary Certificate | 3.2% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Realistic | 5.9 | |
| Conventional | 3.6 | |
| Social | 3.1 | |
| Enterprising | 3.0 | |
| Investigative | 1.6 |
Interest areas
| Protective Service | 3.5 | |
| Transportation/Machine Operation | 2.0 | |
| Physical/Manual Labor | 2.0 | |
| Personal Service | 1.7 | |
| Teaching/Education | 1.7 |
Work styles
| Dependability | 3.0 | |
| Cautiousness | 2.6 | |
| Cooperation | 2.0 | |
| Integrity | 1.9 | |
| Attention to Detail | 1.8 | |
| Self-Control | 1.7 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $29,940 |
| 25th percentile | $34,280 |
| Median (50th) | $37,700 |
| 75th percentile | $46,920 |
| 90th percentile | $61,440 |
| People employed | 90,180 |
Industries that employ this occupation
Where these workers are employed, by number of jobs (national, BLS OEWS). Pay shown is the occupation's national median, not industry-specific.
| Industry | Workers | National median pay |
|---|---|---|
| Administrative and Support and Waste Management and Remediation Services · Sector | 38,570 | $37,740 |
| Educational Services · Sector | 7,540 | $34,950 |
| Construction · Sector | 6,090 | $46,840 |
| Temporary Help Services · National industry | 4,750 | $36,700 |
| Real Estate and Rental and Leasing · Sector | 910 | $35,330 |
| Transportation and Warehousing · Sector | 690 | $33,190 |
| Other Services (except Public Administration) · Sector | 510 | $35,890 |
| Power and Communication Line and Related Structures Construction · National industry | 360 | $45,840 |
| Electrical Contractors and Other Wiring Installation Contractors · National industry | 350 | $47,320 |
| Arts, Entertainment, and Recreation · Sector | 200 | $29,590 |
| Manufacturing · Sector | 170 | $42,680 |
| Landscaping Services · National industry | 160 | $45,400 |
Where this work is most concentrated
Industries where this occupation is far more common than in the economy as a whole. The location quotient is how many times more concentrated it is here (a value of 5 means five times its economy-wide share).
| Industry | Concentration | Workers |
|---|---|---|
| Administrative and Support and Waste Management and Remediation Services · Sector | 7.3× | 38,570 |
| Temporary Help Services · National industry | 3.06× | 4,750 |
| Power and Communication Line and Related Structures Construction · National industry | 2.63× | 360 |
| Construction · Sector | 1.28× | 6,090 |
| Educational Services · Sector | 0.95× | 7,540 |
| Real Estate and Rental and Leasing · Sector | 0.66× | 910 |
| Electrical Contractors and Other Wiring Installation Contractors · National industry | 0.56× | 350 |
| Landscaping Services · National industry | 0.3× | 160 |
Related occupations
Part of the Public Service & Safety career cluster.
- Transit and Railroad Police · 33-3052.00 Compare →
- Subway and Streetcar Operators · 53-4041.00 Compare →
- Railroad Conductors and Yardmasters · 53-4031.00 Compare →
- Security Guards · 33-9032.00 Compare →
- Parking Enforcement Workers · 33-3041.00 Compare →
- Bridge and Lock Tenders · 53-6011.00 Compare →
- Locomotive Engineers · 53-4011.00 Compare →
- Transportation Security Screeners · 33-9093.00 Compare →
- Bus Drivers, Transit and Intercity · 53-3052.00 Compare →
- Railroad Brake, Signal, and Switch Operators and Locomotive Firers · 53-4022.00 Compare →
- Police and Sheriff's Patrol Officers · 33-3051.00 Compare →
- Highway Maintenance Workers · 47-4051.00 Compare →
Side-by-side comparisons place two occupations’ pay, preparation, skills, and AI exposure on the same page — same data, same scale, no forecast.
What you can do with this
Options the data surfaces for Crossing Guards and Flaggers — not advice or a forecast. Each is a real cross-link you can follow into the evidence.
Skills that travel
Capabilities this work builds that are used across many other occupations.
Adjacent roles
Occupations O*NET rates as related — the nearby moves on the map.
Paths in
How people typically prepare for this work.
- No formal educational credential · typical entry level
- Job zone 2 — Job Zone 1-2: Very Little to Some Preparation Needed · preparation tier
Zoom out
On the global GenAI exposure gradient this work sits around the 33rd percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Crossing Guards and Flaggers show 37th-percentile AI task overlap — and about 18,000 annual U.S. openings
- Crossing Guards and Flaggers rank in the 37th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated.Eloundou et al. (GPTs are GPTs) + Felten AIOE
- The occupation is projected to see about 18,000 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI.BLS Employment Projections 2024–34
- BLS projects employment to be about average (+3.6%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $37,700, across about 90,180 U.S. workers.BLS OEWS (May 2024)
Copy the whole kit
Crossing Guards and Flaggers show 37th-percentile AI task overlap — and about 18,000 annual U.S. openings • Crossing Guards and Flaggers rank in the 37th percentile (Moderate band) for AI task overlap across U.S. occupations — a measure of how much of the work today's AI can attempt, not how much is automated. (Eloundou et al. (GPTs are GPTs) + Felten AIOE) • The occupation is projected to see about 18,000 U.S. job openings per year (2024–34), counting growth and replacement — a labor-demand projection made independently of AI. (BLS Employment Projections 2024–34) • BLS projects employment to be about average (+3.6%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $37,700, across about 90,180 U.S. workers. (BLS OEWS (May 2024)) Source: Singulariki — "Crossing Guards and Flaggers". https://singulariki.com/roles/role-33-9091-00 Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.
AssetsShare imageMethodology & sourcesPress & newsroomThe newsroom
Every line is built only from figures this page already shows and cites. AI task overlap means what today's AI can attempt — not automation, job loss, or a forecast.
Sources for this page
Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.
- O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
- BLS Occupational Employment and Wage Statistics (OEWS) May 2024 U.S. Bureau of Labor Statistics
- BLS Employment Projections 2024–2034 U.S. Bureau of Labor Statistics
- Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
- Microsoft “Working with AI” working-with-ai Microsoft Research
- “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic
- AI Occupational Exposure (AIOE) Felten, Raj & Seamans academic
- ILO / Gmyrek et al. GenAI exposure gradient 2025 International Labour Organization
- IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022 Institute for Structural Research (IBS)
- Frey & Osborne (2013) frey-osborne-automation academic
- Dingel & Neiman (2020) dingel-neiman-workathome academic
Data compiled June 2, 2026. Figures are estimates, not advice.
Cite this page
Plain
Singulariki. "Crossing Guards and Flaggers." Singulariki: a source-backed encyclopedia of work. Built from O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026. https://singulariki.com/roles/role-33-9091-00
APA
Singulariki. (2026). Crossing Guards and Flaggers. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-33-9091-00
BibTeX
@misc{singulariki-role-33-9091-00,
title = {Crossing Guards and Flaggers},
author = {{Singulariki}},
year = {2026},
note = {O*NET 30.3; BLS Occupational Employment and Wage Statistics (OEWS) May 2024; BLS Employment Projections 2024–2034; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); Microsoft “Working with AI” working-with-ai; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130; AI Occupational Exposure (AIOE) Felten, Raj & Seamans; ILO / Gmyrek et al. GenAI exposure gradient 2025; IBS O*NET-SOC ↔ ISCO-08 occupation crosswalk 2022; Frey & Osborne (2013) frey-osborne-automation; Dingel & Neiman (2020) dingel-neiman-workathome. Accessed June 7, 2026},
url = {https://singulariki.com/roles/role-33-9091-00}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.