Will AI replace traffic technicians?

Not replace, but it is changing the job. About 46m of an 8-hour shift goes to tasks touched by robots. The other 7h 14m (91%) stays with people. Separately, BLS expects about 4% more of these jobs by 2035 (all jobs: +3.5%).

None of this job's tasks show regular AI use yet. That can mean the work is hands-on or in person, or simply that it rarely comes up in AI usage data.

For some tasks, yes. Robots have done 3 of this job's tasks in workplaces like this one, about 46m of a typical shift. 3 more tasks have only been done in factory setups built around the machine, so they stay with people here. For 2 physical tasks, no robot has shown it can do the work yet.

• Measure and record the speed of vehicular traffic, using electrical timing devices or radar equipment. (19m a shift; e.g. ReADI autonomous dock-drone network (AI View Group, on FlytBase, DJI M300/M30T + VTOL), in use)
• Study traffic delays by noting times of delays, the numbers of vehicles affected, and vehicle speed through the delay area. (13m a shift; e.g. ReADI (AI View Group docked drones on FlytBase, DJI M300/M30T + VTOL), in use)
• Lay out pavement markings for striping crews. (13m a shift; e.g. TinyMobileRobots TinySurveyor Terra, in use)

7h 14m of a typical shift, or 91%, goes to tasks with no AI or robot evidence yet. No AI usage or robot deployment has shown up for these so far. The biggest:

• Interact with the public to answer traffic-related questions, respond to complaints or requests, or discuss traffic control ordinances, plans, policies, or procedures. (32m a shift)
• Analyze data related to traffic flow, accident rates, or proposed development to determine the most efficient methods to expedite traffic flow. (32m a shift)
• Gather and compile data from hand count sheets, machine count tapes, or radar speed checks and code data for computer input. (32m a shift)
• Operate counters and record data to assess the volume, type, and movement of vehicular or pedestrian traffic at specified times. (32m a shift)
• Prepare work orders for repair, maintenance, or changes in traffic systems. (26m a shift)

The median pay is about $59,090 a year ($28.41 an hour), 16% above the median for all U.S. jobs ($50,980). Most people in this job earn between $39,090 and $85,130 a year; that range covers the middle 80%. Pay figures are from BLS, May 2025, and vary a lot by state and employer.

BLS projects growth of 4% from 2025 to 2035, compared with 3.5% growth for all jobs. That's about 8,400 jobs in 2035. It expects about 900 openings a year, mostly from people retiring or changing careers. These projections don't single out AI as a cause.

About 7,860 people in the U.S., roughly 0.01% of all workers (BLS, May 2025). That makes it the 697th largest of the 796 jobs on this site. BLS expects about 8,400 in 2035.

The most common requirement is a high school diploma: about 43% of people in the job said so in the official O*NET survey. O*NET rates the job at level 3 of 5 for preparation, which usually means: vocational school or associate's degree. Requirements vary by state and employer, especially for licensed work.

These come from the job's official skill ratings and from the tasks that AI and robots touch least today. Building them keeps you strong in the parts of the work that still need a person:

• Skills that matter more here than in most jobs: Management of Personnel Resources, Systems Evaluation, Systems Analysis, Complex Problem Solving
• Get strong at the parts of the job that stay with people (listed above), which take 7h 14m of a typical shift
• Tools employers list: Microsoft Office software, Microsoft Excel, Autodesk AutoCAD, Bentley MicroStation, C++

These use similar skills. Matches come from 109 official ratings of skills, knowledge and work activities, and each needs the same or less preparation unless the official list relates the jobs directly:

• Civil Engineering Technologists and Technicians (1h 23m touched, $65k median pay)

Each task carries its own evidence label. For this job: 3 with robots in real deployments, 20 with no AI or robot evidence found. The minutes per task are estimates, not measured hours, and "no evidence" doesn't prove a task is safe.