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.
- Provide technical supervision regarding traffic control devices to other traffic technicians or laborers.74
- Compute time settings for traffic signals or speed restrictions, using standard formulas.74
- Provide traffic information, such as road conditions, to the public.74
- Study traffic delays by noting times of delays, the numbers of vehicles affected, and vehicle speed through the delay area.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.
- Prepare work orders for repair, maintenance, or changes in traffic systems.01
- Maintain or make minor adjustments or field repairs to equipment used in surveys, including the replacement of parts on traffic data gathering devices.02
- Operate counters and record data to assess the volume, type, and movement of vehicular or pedestrian traffic at specified times.03
- Prepare drawings of proposed signal installations or other control devices, using drafting instruments or computer-automated drafting equipment.04
- Plan, design, and improve components of traffic control systems to accommodate current or projected traffic and to increase usability and efficiency.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Civil Engineering Technologists and Technicians
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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.
