π‘ Traffic Technicians have a composite risk score of 62/100 (Frey-Osborne probability: 90%, GenAI exposure: 65/100). With 7,580 workers in the US, this is one of the most AI-vulnerable occupations. Full occupation profile β
π― The Verdict
Likely for many tasks. The role will look very different in 5β10 years.
With 7,580 workers and a median wage of $58K,traffic technicians represent a significant portion of the US workforce. Their GenAI exposure index is 65%, meaning a majority of their core tasks overlap with current generative AI capabilities.
Risk Score
62/100
Employment
7,580
Median Wage
$58K
GenAI Exposure
65%
β οΈ Top Risk Factors
Automated data interpretation and insight generation
AI coding assistants reducing developer demand
Predictive maintenance reducing manual inspection needs
AI summarization replacing manual report compilation
π‘οΈ Tasks AI Can't Easily Replace
Manual loading of irregular and fragile cargo
Emergency situation response and quick decision-making
Navigating complex urban environments with obstacles
π Career Transition Paths
Related occupations with lower AI risk and high skills overlap:
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors
74% skills overlap Β· $62K median wage
Aircraft Cargo Handling Supervisors
81% skills overlap Β· $64K median wage
Air Transportation Workers
77% skills overlap Β· $107K median wage
β Frequently Asked Questions
Will AI completely replace traffic technicians?
Likely for many tasks. The role will look very different in 5β10 years.
What is the AI risk score for traffic technicians?
Traffic Technicians have a composite AI automation risk score of 62 out of 100, classified as "High Risk".
How many traffic technicians are there in the US?
There are approximately 7,580 traffic technicians employed in the United States.
What do traffic technicians earn?
The median annual wage for traffic technicians is $58K.
What skills should traffic technicians develop?
Focus on tasks AI can't easily replicate: manual loading of irregular and fragile cargo, emergency situation response and quick decision-making, navigating complex urban environments with obstacles. These human-centric skills will become more valuable as routine tasks are automated.