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.
- Produce environmental documents, such as environmental assessments or environmental impact statements.75
- Represent jurisdictions in the legislative or administrative approval of land development projects.75
- Define or update information such as urban boundaries or classification of roadways.75
- 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.74
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.
- Collaborate with other professionals to develop sustainable transportation strategies at the local, regional, or national level.01
- Design new or improved transport infrastructure, such as junction improvements, pedestrian projects, bus facilities, or car parking areas.02
- Define regional or local transportation planning problems or priorities.03
- Develop or test new methods or models of transportation analysis.04
- Design transportation surveys to identify areas of public concern.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Transportation Engineers
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Related work
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.
