Often handed to AI
Task areas most often handled directively in observed AI conversations — candidates to delegate with light review.
- Prepare or review engineering studies or specifications. · 0.6%
Transportation Planners
Occupation · SOC 19-3099.01
Prepare studies for proposed transportation projects. Gather, compile, and analyze data. Study the use and operation of transportation systems. Develop transportation models or simulations.
Also called: Planner · Program Officer · Transportation Data Programs Manager · Transportation Planner · Transportation Analyst · Airway Transportation Systems Specialist (ATSS) · Fleet Coordinator · Traffic Analyst · Transit Planner · Transportation Consultant · Transportation Designer · Transportation Logistics Analyst
Job family: Life, Physical, and Social Science Occupations
Take this to your AI
A source-stamped Markdown brief of this occupation — paste it into an agent, or fetch
/roles/role-19-3099-01/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.
Use as a copilot
Task areas where people work with AI — iterating, learning, or checking — staying in the loop rather than handing the task off.
- Prepare reports or recommendations on transportation planning. · 0.3%
Keep a human in the loop
Task areas where a human was still judged necessary in a large share of observed conversations — not a safety ruling, an observed-need signal.
- Prepare reports or recommendations on transportation planning. · 94.1% need a human
- Prepare or review engineering studies or specifications. · 90.9% need a human
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 →Market signal
Independent published positions, read together — not a forecast.
- Declining employment outlook (-1.7% by 2034)
- 3,200 openings/yr
- High AI exposure
- Observed AI use leans automation
- Median pay $100,340/yr
- Can largely be done remotely (teleworkable)
- A reversal from 2013 — rated low automation risk then (22nd), high AI task-overlap now (95th)
95th-percentile task overlap — yet about 3,200 openings a year (-1.7% projected, BLS), and observed AI use leans 3708% copilot, not hand-off (AEI) . 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.) High | 89th | 1.3 | |
| LLM task exposure, γ (OpenAI / Eloundou) High | 86th | 1.0 | |
| AI assistant applicability (Microsoft) High | 94th | 0.3 |
OpenAI's exposure study scores tasks three ways: with a language model alone (α 0.1), with simple added tooling (β 0.5), and including AI-powered software (γ 1.0). Higher means more of the job's tasks could be done at least twice as fast — not that they will be automated away.
Most of this job's tasks can be done remotely (Dingel–Neiman), which tends to track with higher digital and AI exposure.
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 0.0 · 22nd percentile among occupations · Low
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.
| Prepare or review engineering studies or specifications. | 2.8% | |
| Analyze information from traffic counting programs. | 0.8% | |
| Prepare reports or recommendations on transportation planning. | 0.6% | |
| Design transportation surveys to identify areas of public concern. | 0.6% | |
| Develop computer models to address transportation planning issues. | 0.3% | |
| Review development plans for transportation system effects, infrastructure requirements, or compliance with applicable transportation regulations. | 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 | Declining · -1.7% by 2034 |
| Projected annual openings | 3,200 |
| Employment 2024 → 2034 | 40,800 → 40,100 |
“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 2 occupations below. Exposure here means how much of the work's tasks today's AI can attempt — task overlap, not automation, adoption, or jobs lost.
Transportation Planners sits at the 90th percentile of 427
occupations on the global GenAI task-exposure gradient
— exposure rose from 2023 to 2025. Each dot is one occupation; the
ringed one is this work. Exposure is task overlap, not automation or jobs lost.
52% mean task exposure (2025)
90th percentile of 427 placed occupations
+3 pts shift 2023 → 2025
| International occupation (ISCO-08) | Task exposure (2025) | Most tasks fall in |
|---|---|---|
| Translators, Interpreters and Other Linguists · 2643 | 59% | Gradient 3 |
| Philosophers, Historians and Political Scientists · 2633 | 47% | Gradient 2 |
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.
Working with AI in this job
How people actually apply AI to this occupation's tasks, from Claude.ai (Free and Pro) conversations in the Anthropic Economic Index, 2026-01-15. This is one AI assistant's consumer sample — not all AI, not the whole workforce. Autonomy and the collaboration mix are model-rated estimates; figures below the sample floor are hidden.
| Augmentation vs. automation | 37.1% working with AI · 47.2% handed to AI |
| Most common way people use AI here | Directive · AI does it; you give the instruction |
| Typical AI autonomy | 3.8 / 5 · higher = AI acts more independently |
| Used for work (vs. personal / coursework) | 70.8% |
What people delegate to AI
The role's most common tasks in AI conversations, each tagged with how people work with the AI on it. “Usage” is the share of observed conversations, not of the job.
| Task | How | Usage |
|---|---|---|
| Prepare or review engineering studies or specifications. | Directive | 0.6% |
| Prepare reports or recommendations on transportation planning. | Iteration | 0.3% |
Where a human is still needed
Tasks where the model most often judged that a person remained necessary — a useful read on the current boundary, not a guarantee.
| Prepare reports or recommendations on transportation planning. | 94.1% | |
| Prepare or review engineering studies or specifications. | 90.9% |
What people most often hand AI here
Example prompts phrased from the tasks people most often delegate to AI in this occupation (Anthropic Economic Index). Each shows the underlying measured task and its share of observed AI use. They are suggested phrasings of real tasks — starting points, not endorsed instructions.
-
Help me prepare or review engineering studies or specifications.From: Prepare or review engineering studies or specifications. · 0.6% of measured AI use · directive
-
Help me prepare reports or recommendations on transportation planning.From: Prepare reports or recommendations on transportation planning. · 0.3% of measured AI use · task iteration
Tasks
All 22 tasks O*NET lists for this occupation, ordered by importance. Each links to its own page with AI-exposure and observed-use detail.
- Define regional or local transportation planning problems or priorities. Core · importance 4.3
- Participate in public meetings or hearings to explain planning proposals, to gather feedback from those affected by projects, or to achieve consensus on project designs. Core · importance 4.3
- Prepare reports or recommendations on transportation planning. Core · importance 4.2
- Collaborate with engineers to research, analyze, or resolve complex transportation design issues. Core · importance 4.2
- Recommend transportation system improvements or projects, based on economic, population, land-use, or traffic projections. Core · importance 4.2
- Develop computer models to address transportation planning issues. Core · importance 4.1
- Analyze information related to transportation, such as land use policies, environmental impact of projects, or long-range planning needs. Core · importance 4.1
- Design transportation surveys to identify areas of public concern. Core · importance 4.0
- Interpret data from traffic modeling software, geographic information systems, or associated databases. Core · importance 4.0
- Collaborate with other professionals to develop sustainable transportation strategies at the local, regional, or national level. Core · importance 4.0
- Evaluate transportation project needs or costs. Core · importance 4.0
- Analyze information from traffic counting programs. Core · importance 3.9
- Review development plans for transportation system effects, infrastructure requirements, or compliance with applicable transportation regulations. Core · importance 3.8
- Prepare necessary documents to obtain planned project approvals or permits. Core · importance 3.8
- Produce environmental documents, such as environmental assessments or environmental impact statements. Core · importance 3.7
- Prepare or review engineering studies or specifications. Core · importance 3.6
- Develop or test new methods or models of transportation analysis. Core · importance 3.6
- Evaluate transportation-related consequences of federal or state legislative proposals. Core · importance 3.5
- Design new or improved transport infrastructure, such as junction improvements, pedestrian projects, bus facilities, or car parking areas. Core · importance 3.4
- Define or update information such as urban boundaries or classification of roadways. Supplemental · importance 3.3
- Represent jurisdictions in the legislative or administrative approval of land development projects. Core · importance 3.2
- Direct urban traffic counting programs. Core · importance 3.1
Work activities
- Prepare scientific or technical reports or presentations.
- Represent the interests of clients in legal proceedings.
- Represent the organization in external relations.
- Direct scientific activities.
- Develop theories or models of physical phenomena.
- Prepare information or documentation related to legal or regulatory matters.
- Analyze data to identify trends or relationships among variables.
- Analyze traffic data.
- Evaluate civic projects or public policies.
- Prepare research or technical reports on environmental issues.
- Communicate with the public on environmental issues.
- Develop methods of social or economic research.
- Collaborate with technical specialists to resolve design or development problems.
- Advise others on matters of public policy.
- Analyze data to identify or resolve operational problems.
- Determine causes of operational problems or failures.
- Appraise environmental impact of regulations or policies.
- Interpret research or operational data.
- Design civil structures or systems.
- Analyze costs and benefits of proposed designs or projects.
- Prepare documentation for permits or licenses.
Knowledge, skills & abilities
O*NET importance rating, from 1 (not important) to 5 (extremely important).
Knowledge
| Transportation | 4.8 | |
| English Language | 3.9 | |
| Mathematics | 3.9 | |
| Geography | 3.7 | |
| Law and Government | 3.7 | |
| Computers and Electronics | 3.5 | |
| Administration and Management | 3.4 | |
| Engineering and Technology | 3.3 |
Essential skills
| Reading Comprehension | 4.0 | |
| Active Listening | 4.0 | |
| Writing | 4.0 | |
| Speaking | 4.0 | |
| Critical Thinking | 4.0 | |
| Active Learning | 3.8 | |
| Mathematics | 3.4 | |
| Monitoring | 3.1 |
Transferable skills
| Complex Problem Solving | 4.0 | |
| Judgment and Decision Making | 3.9 | |
| Systems Evaluation | 3.8 | |
| Coordination | 3.6 | |
| Systems Analysis | 3.5 | |
| Operations Analysis | 3.3 | |
| Time Management | 3.3 |
Abilities
| Oral Comprehension | 4.0 | |
| Written Comprehension | 4.0 | |
| Oral Expression | 4.0 | |
| Written Expression | 4.0 | |
| Fluency of Ideas | 4.0 | |
| Deductive Reasoning | 4.0 | |
| Inductive Reasoning | 4.0 | |
| Problem Sensitivity | 3.9 | |
| Visualization | 3.9 | |
| Near Vision | 3.8 | |
| Speech Clarity | 3.8 | |
| Originality | 3.6 | |
| Information Ordering | 3.6 | |
| Speech Recognition | 3.5 | |
| Category Flexibility | 3.3 | |
| Mathematical Reasoning | 3.1 | |
| Flexibility of Closure | 3.1 |
Skills in demand
Skills employers ask for in job postings for this occupation (Lightcast), with whether each is a common or specialized skill.
Showing the top 40 of 44.
Tools & technology
Showing the top 40 of 45.
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 4 — Job Zone Four: Considerable Preparation Needed
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Typical entry-level education
- Bachelor's degree · BLS, the typical path — not a requirement
- Related experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
- Preparation level
- SVP (7.0 to < 8.0) — total schooling plus on-the-job experience.
What to study: Education , Family and Consumer Sciences/Human Sciences , Foreign Languages, Literatures, and Linguistics , Health Professions and Related Programs , Multi/Interdisciplinary Studies , Natural Resources and Conservation , Public Administration and Social Service Professions , Social Sciences . Fields of study crosswalked to this occupation (NCES CIP–SOC), not a requirement.
Education of current workers
Share of people in this occupation at each level of education.
| Bachelor's Degree | 55.0% | |
| Master's Degree | 45.0% |
Interests & work styles
The interests and personal qualities O*NET associates with people who do this work.
Career interests (Holland / RIASEC)
| Investigative | 5.6 | |
| Conventional | 4.9 | |
| Realistic | 3.6 | |
| Enterprising | 3.1 |
Interest areas
| Mathematics/Statistics | 4.9 | |
| Engineering | 3.5 | |
| Public Speaking | 3.3 | |
| Information Technology | 3.0 | |
| Politics | 3.0 | |
| Management/Administration | 3.0 | |
| Law | 2.5 | |
| Social Science | 2.5 | |
| Office Work | 2.5 | |
| Business Initiatives | 2.1 |
Work styles
| Dependability | 3.0 | |
| Attention to Detail | 2.6 |
Wages & employment
U.S. · annual wages (BLS OEWS)
| 10th percentile | $62,570 |
| 25th percentile | $79,210 |
| Median (50th) | $100,340 |
| 75th percentile | $127,880 |
| 90th percentile | $160,810 |
| People employed | 36,970 |
Wages and employment are reported by BLS for the broader occupation group this specialty belongs to (SOC 19-3099), not for the specialty alone.
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 |
|---|---|---|
| Professional, Scientific, and Technical Services · Sector | 4,870 | $104,310 |
| Educational Services · Sector | 4,520 | $83,100 |
| Research and Development in the Social Sciences and Humanities · National industry | 2,450 | $104,680 |
| Management of Companies and Enterprises · Sector | 1,610 | $171,320 |
| Health Care and Social Assistance · Sector | 490 | $66,260 |
| Other Services (except Public Administration) · Sector | 450 | $80,760 |
| Wholesale Trade · Sector | 80 | $85,070 |
| Offices of Mental Health Practitioners (except Physicians) · National industry | 70 | $39,690 |
| Temporary Help Services · National industry | 60 | $68,080 |
| Manufacturing · Sector | 50 | $66,570 |
| Information · Sector | 40 | $134,250 |
| Engineering Services · National industry | — | $96,360 |
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 |
|---|---|---|
| Research and Development in the Social Sciences and Humanities · National industry | 168.09× | 2,450 |
| Management of Companies and Enterprises · Sector | 2.39× | 1,610 |
| Professional, Scientific, and Technical Services · Sector | 1.89× | 4,870 |
| Educational Services · Sector | 1.38× | 4,520 |
| Other Services (except Public Administration) · Sector | 0.42× | 450 |
| Health Care and Social Assistance · Sector | 0.09× | 490 |
Related occupations
Part of the Education , Energy & Natural Resources , Healthcare & Human Services and Public Service & Safety career clusters.
- Transportation Engineers · 17-2051.01 Compare →
- Urban and Regional Planners · 19-3051.00 Compare →
- Transportation, Storage, and Distribution Managers · 11-3071.00 Compare →
- Logistics Engineers · 13-1081.01 Compare →
- Logisticians · 13-1081.00 Compare →
- Traffic Technicians · 53-6041.00 Compare →
- Logistics Analysts · 13-1081.02 Compare →
- Civil Engineers · 17-2051.00 Compare →
- Project Management Specialists · 13-1082.00 Compare →
- Civil Engineering Technologists and Technicians · 17-3022.00 Compare →
- Freight Forwarders · 43-5011.01 Compare →
- Management Analysts · 13-1111.00 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 Transportation Planners — 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.
- Bachelor's degree · typical entry level
- Job zone 4 — Job Zone Four: Considerable Preparation Needed · preparation tier
- Education · field of study
- Family and Consumer Sciences/Human Sciences · field of study
Zoom out
On the global GenAI exposure gradient this work sits around the 90th percentile of 427 international occupations.
Write a report on thisheadline · factoids · citation
Transportation Planners show 95th-percentile AI task overlap — and about 3,200 annual U.S. openings
- Transportation Planners rank in the 95th percentile (High 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 3,200 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 declining (-1.7%) from 2024 to 2034.BLS Employment Projections 2024–34
- Median annual pay is $100,340, across about 36,970 U.S. workers.BLS OEWS (May 2024)
- Of the AI use actually observed for this work, 37% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census.2026-01-15-v4-plus-2025-03-27-v2
Copy the whole kit
Transportation Planners show 95th-percentile AI task overlap — and about 3,200 annual U.S. openings • Transportation Planners rank in the 95th percentile (High 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 3,200 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 declining (-1.7%) from 2024 to 2034. (BLS Employment Projections 2024–34) • Median annual pay is $100,340, across about 36,970 U.S. workers. (BLS OEWS (May 2024)) • Of the AI use actually observed for this work, 37% looks like augmentation (drafting, iterating, checking) rather than hands-off automation — from a Claude.ai usage sample, not a census. (2026-01-15-v4-plus-2025-03-27-v2) Source: Singulariki — "Transportation Planners". https://singulariki.com/roles/role-19-3099-01 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. "Transportation Planners." 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-19-3099-01
APA
Singulariki. (2026). Transportation Planners. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/roles/role-19-3099-01
BibTeX
@misc{singulariki-role-19-3099-01,
title = {Transportation Planners},
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-19-3099-01}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.