How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Create, prepare, or requisition graphic or narrative reports on land use data, including land area maps overlaid with geographic variables, such as population density.74
- Keep informed about economic or legal issues involved in zoning codes, building codes, or environmental regulations.74
- Advise planning officials on project feasibility, cost-effectiveness, regulatory conformance, or possible alternatives.73
- Assess the feasibility of land use proposals and identify necessary changes.73
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Discuss with planning officials the purpose of land use projects, such as transportation, conservation, residential, commercial, industrial, or community use.01
- Design, promote, or administer government plans or policies affecting land use, zoning, public utilities, community facilities, housing, or transportation.02
- Advise planning officials on project feasibility, cost-effectiveness, regulatory conformance, or possible alternatives.03
- Supervise or coordinate the work of urban planning technicians or technologists.04
- Assess the feasibility of land use proposals and identify necessary changes.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Transportation Planners
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Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
