Medium AI Risk Average

Shuttle drivers and chauffeurs

SOC Code: 53-3053

Shuttle drivers and chauffeurs carries a 36% AI exposure score (Medium automation risk), with a median annual wage of $36,670 and +6.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 243,900 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
36% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
+6.7%
2024–2034 (BLS)
+16,400 jobs
Median Annual Wage
$36,670
BLS May 2024
How wage figures are sourced →
The verdict

At 36% AI exposure, Shuttle drivers and chauffeurs sits 1 points below the 37.2% average across 832 U.S. occupations - more exposed than 58% of them. Most of its core tasks still require human judgment.

36%
AI exposure
Top 42%
most exposed
+6.7%
Job growth 2024–34
$36,670
Median wage

Where Shuttle drivers and chauffeurs sits among all occupations

AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.

AI exposure distribution - Shuttle drivers and chauffeurs marked 1 occupations at 0–10% 1 0 43 occupations at 10–20% 43 10 184 occupations at 20–30% 184 20 332 occupations at 30–40% 332 30 158 occupations at 40–50% 158 40 64 occupations at 50–60% 64 50 29 occupations at 60–70% 29 60 15 occupations at 70–80% 15 70 5 occupations at 80–90% 5 80 1 occupations at 90–100% 1 90 AI exposure (%) →
Top 42% by AI exposure Higher AI exposure than 58% of all 832 occupations.

Shuttle drivers and chauffeurs has ai exposure of 36%. Distribution: 1 occupations at 0-10%; 43 occupations at 10-20%; 184 occupations at 20-30%; 332 occupations at 30-40%; 158 occupations at 40-50%; 64 occupations at 50-60%; 29 occupations at 60-70%; 15 occupations at 70-80%; 5 occupations at 80-90%; 1 occupations at 90-100%.

Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.

Shuttle drivers and chauffeurs vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Shuttle drivers and chauffeurs is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk18.9%25.2%31.5%37.8%44.1%-6.1%-2.2%1.7%5.6%9.5%AI exposure (%) →Projected growth (%) →LaborersStockersHeavyLight truck driversIndustrial truckFirst-line supervisoPackersDriver/sales workersCleaners of vehiclesBus driversShuttle drivers

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

243,900
Employment 2024
260,300
Projected 2034
+6.7%
Change (%)
+16,400
Change (jobs)

Occupation Insight

Shuttle drivers and chauffeurs (SOC 53-3053) carries an AI exposure score of 36%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.

The economic context matters alongside the risk score. BLS counted approximately 243,900 workers in this occupation in 2024, and projects a +6.7% change through 2034 - modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $36,670, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires No formal educational credential, plus None of related experience.

For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Shuttle drivers and chauffeurs. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
No formal educational credential
Work Experience
None
On-the-Job Training
Short-term on-the-job training

Top Tasks (O*NET)

  1. 1. Test vehicle equipment, such as lights, brakes, horns, or windshield wipers, to ensure proper operation.
  2. 2. 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.
  3. 3. Comply with traffic regulations to operate vehicles in a safe and courteous manner.
  4. 4. Follow relevant safety regulations and state laws governing vehicle operation, and ensure that passengers follow safety regulations.
  5. 5. Operate vehicles with specialized equipment, such as wheelchair lifts, to transport and secure passengers with special needs.
  6. 6. Report any vehicle malfunctions or needed repairs.
  7. 7. Perform routine vehicle maintenance, such as regulating tire pressure and adding gasoline, oil, and water.
  8. 8. Pick up and drop off passengers at regularly scheduled neighborhood locations, following strict time schedules.
  9. 9. Drive shuttle busses, limousines, company cars, or privately owned vehicles to transport passengers.
  10. 10. Prepare and submit reports that may include the number of passengers or trips, hours worked, mileage driven fuel consumed, or fares received.

Key Skills Required

  • Active Listening
  • Critical Thinking
  • Monitoring
  • Operation and Control
  • Speaking
  • Social Perceptiveness
  • Service Orientation
  • Operations Monitoring
  • Reading Comprehension
  • Coordination

Knowledge Areas

  • Customer and Personal Service
  • Transportation
  • Public Safety and Security
  • English Language
  • Personnel and Human Resources
  • Administrative
  • Administration and Management
  • Education and Training
  • Production and Processing
  • Law and Government

Frequently Asked Questions

Will AI replace Shuttle drivers and chauffeurs?

Shuttle drivers and chauffeurs has an AI exposure score of 36%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.

What is the job outlook for Shuttle drivers and chauffeurs?

According to BLS Employment Projections 2024-2034, Shuttle drivers and chauffeurs is projected to grow by 6.7% over the decade. Current employment stands at approximately 243,900 workers.

What skills are needed for Shuttle drivers and chauffeurs?

Key skills for Shuttle drivers and chauffeurs include Active Listening, Critical Thinking, Monitoring, and others. Typical entry-level education is No formal educational credential.

How much do Shuttle drivers and chauffeurs earn?

The median annual wage for Shuttle drivers and chauffeurs is $36,670, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.

What education is required for Shuttle drivers and chauffeurs?

The typical entry-level education for Shuttle drivers and chauffeurs is No formal educational credential. Employers generally expect None of related work experience. On-the-job training typically involves Short-term on-the-job training. Requirements can vary by employer and specialization.

Which companies employ Shuttle drivers and chauffeurs?

Shuttle drivers and chauffeurs roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.

AI Exposure Rating

1.8
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.