48
/100

SOC 53-3053

Shuttle Drivers and Chauffeurs

ElevatedFrey/Osborne: 40.0%

Risk Score

โš ๏ธ

48/100

Elevated

US Employment

๐Ÿ‘ฅ

229,630

Total workers

Median Wage

๐Ÿ’ฐ

$37K

$27K โ€“ $53K

Projected Growth

๐Ÿ“ˆ

+6.7%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

48/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Shuttle Drivers and Chauffeurs face a risk score of 48/100 โ€” 4 points above the national average of 44. With only 48/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $37K. 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 48/100, Shuttle Drivers and Chauffeurs 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 229,630 workers in this occupation should focus on strengthening skills in manual loading of irregular and fragile cargo and navigating unpredictable road and weather conditions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Shuttle Drivers and Chauffeurs?

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

Automated warehouse sorting and loading systems

4

Drone delivery displacing last-mile logistics workers

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Manual loading of irregular and fragile cargo

โœ“

Navigating unpredictable road and weather conditions

โœ“

Customer interaction and conflict resolution during delivery

โœ“

Navigating complex urban environments with obstacles

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

Arrange to pick up particular customers or groups on a regular schedule.

โ€ข

Check the condition of a vehicle's tires, brakes, windshield wipers, lights, oil, fuel, water, and safety equipment to ensure that everything is in working order.

โ€ข

Collect fares or vouchers from passengers, and make change or issue receipts as necessary.

โ€ข

Communicate with dispatchers by radio, telephone, or computer to exchange information and receive requests for passenger service.

โ€ข

Complete accident reports when necessary.

๐Ÿ’ป Technology Skills

โ€ข

Data base user interface and query software

โ€ข

Map creation software

โ€ข

Mobile location based services software

โ€ข

Web page creation and editing software

โ€ข

Spreadsheet software

๐Ÿ“Š vs National Average

Median Wage$37K
$-10K

National avg: $46K

Risk Score48/100
+4

National avg: 44/100

GenAI Exposure48/100
+10

National avg: 38/100

Projected Growth6.7%
+3.0%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K76%
Aircraft Cargo Handling Supervisors29$64K83%
Air Transportation Workers31$107K79%