64
/100

SOC 53-6031

Automotive and Watercraft Service Attendants

High RiskFrey/Osborne: 83.0%

Risk Score

โš ๏ธ

64/100

High Risk

US Employment

๐Ÿ‘ฅ

98,270

Total workers

Median Wage

๐Ÿ’ฐ

$35K

$28K โ€“ $45K

Projected Growth

๐Ÿ“ˆ

-1%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

53/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Automotive and Watercraft Service Attendants face a risk score of 64/100 โ€” 20 points above the national average of 44. With 53/100 GenAI exposure, this occupation faces significant pressure from AI tools despite weak projected growth. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $35K. The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 64/100, Automotive and Watercraft Service Attendants faces moderate automation pressure. While tasks like ai traffic management and fleet coordination are increasingly handled by AI, the role retains significant human elements. The 98,270 workers in this occupation should focus on strengthening skills in navigating complex urban environments with obstacles and manual loading of irregular and fragile cargo to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Automotive and Watercraft Service Attendants?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

AI traffic management and fleet coordination

2

Predictive maintenance reducing manual inspection needs

3

Autonomous vehicle and self-driving truck technology

4

Drone delivery displacing last-mile logistics workers

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Navigating complex urban environments with obstacles

โœ“

Manual loading of irregular and fragile cargo

โœ“

Emergency situation response and quick decision-making

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

Collect cash payments from customers, and make change or charge purchases to customers' credit cards, providing customers with receipts.

โ€ข

Check tire pressure and levels of fuel, motor oil, transmission, radiator, battery, or other fluids, adding air or fluids as required.

โ€ข

Perform minor repairs, such as adjusting brakes, replacing spark plugs, or changing engine oil or filters.

โ€ข

Clean parking areas, offices, restrooms, or equipment, and remove trash.

โ€ข

Order stock, and price and shelve incoming goods.

๐Ÿ’ป Technology Skills

โ€ข

Inventory management software

โ€ข

Spreadsheet software

โ€ข

Electronic mail software

โ€ข

Operating system software

โ€ข

Point of sale POS software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Customer and Personal Service

โ€ข

Mechanical

โ€ข

Sales and Marketing

โ€ข

Administration and Management

โ€ข

Mathematics

๐Ÿ“Š vs National Average

Median Wage$35K
$-11K

National avg: $46K

Risk Score64/100
+20

National avg: 44/100

GenAI Exposure53/100
+15

National avg: 38/100

Projected Growth-1.0%
-4.7%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K78%
Aircraft Cargo Handling Supervisors29$64K70%
Ambulance Drivers and Attendants, Except Emergency Medical Technicians28$34K77%