Medium AI Risk Slow Growth

Ship engineers

SOC Code: 53-5031

Ship engineers carries a 39% AI exposure score (Medium automation risk), with a median annual wage of $101,320 and +1.6% projected employment growth from 2024 to 2034 (BLS), affecting approximately 8,800 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
39% Medium
Typical exposure

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

Projected Growth
+1.6%
Typical growth
2024–2034 (BLS)
+100 jobs
Median Annual Wage
$101,320
Above typical pay
BLS May 2024
How wage figures are sourced →
The verdict

At 39% AI exposure, Ship engineers sits 2 points above the 37.2% average across 832 U.S. occupations - more exposed than 65% of them. Most of its core tasks still require human judgment.

39%
AI exposure
Top 35%
most exposed
+1.6%
Job growth 2024–34
$101,320
Median wage
C

Career outlook score

56/100

Ship engineers, weighted across 3 of 3 tracked dimensions

A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.

  • Median wage A $101,320

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth D +1.6%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) F 39% exposure

    Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure

Employment vs AI exposure

Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).

4.3M
Home health and personal care aides employment (#1)
#392
Home health and personal care aides AI rank
95%
Bookkeeping, accounting, and auditing clerks AI exposure (#1)
#17
Bookkeeping, accounting, and auditing clerks employment rank

Automation-risk inventory

Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Ship engineers in the Medium band.

Credential × growth standing

Associate / award entry with a named growth shelf

Entry credential Associate / award covers 99 of 832 occupations; BLS places this one in Slow growth (245/832). Mid-credential standing - thicker than graduate shelves, thinner than HS-dominated mass.

Where Ship engineers sits among all occupations

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

Where Ship engineers sits by AI exposure

AI-exposure score distribution across U.S. occupations (O*NET task analysis)

39% Around the middle lower than 35% of 832 occupations

Occupations, banded by AI-exposure score

Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.

Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034

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

Ship engineers vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Ship engineers 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 (%) →Ship engineers, AI exposure (%) →: 39% · Projected growth (%) →: 1.6%Ship engineersLaborers, AI exposure (%) →: 23% · Projected growth (%) →: 1.5%LaborersStockers, AI exposure (%) →: 43% · Projected growth (%) →: 8.5%StockersHeavy, AI exposure (%) →: 43% · Projected growth (%) →: 4%HeavyLight truck drivers, AI exposure (%) →: 36% · Projected growth (%) →: 7.3%Light truck driversIndustrial truck, AI exposure (%) →: 24% · Projected growth (%) →: 1.1%Industrial truckFirst-line superviso, AI exposure (%) →: 35% · Projected growth (%) →: 3.7%First-line supervisoPackers, AI exposure (%) →: 41% · Projected growth (%) →: -5.4%PackersDriver/sales workers, AI exposure (%) →: 34% · Projected growth (%) →: 8.8%Driver/sales workersCleaners of vehicles, AI exposure (%) →: 20% · Projected growth (%) →: 3.9%Cleaners of vehiclesBus drivers, AI exposure (%) →: 32% · Projected growth (%) →: 0.2%Bus driversShuttle drivers, AI exposure (%) →: 36% · Projected growth (%) →: 6.7%Shuttle drivers

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

Employment Projections

8,800
Employment 2024
9,000
Projected 2034
+1.6%
Change (%)
+100
Change (jobs)

Where This Score Comes From

Ship engineers's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the 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 employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 53-5031) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Ship engineers be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.

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 Ship engineers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.

Education & Entry Requirements

Typical Education
Postsecondary nondegree award
Work Experience
Less than 5 years
On-the-Job Training
None

Top Tasks (O*NET)

  1. 1. Monitor engine, machinery, or equipment indicators when vessels are underway, and report abnormalities to appropriate shipboard staff.
  2. 2. Monitor the availability, use, or condition of lifesaving equipment or pollution preventatives to ensure that international regulations are followed.
  3. 3. Monitor and test operations of engines or other equipment so that malfunctions and their causes can be identified.
  4. 4. Start engines to propel ships, and regulate engines and power transmissions to control speeds of ships, according to directions from captains or bridge computers.
  5. 5. Perform or participate in emergency drills, as required.
  6. 6. Perform general marine vessel maintenance or repair work, such as repairing leaks, finishing interiors, refueling, or maintaining decks.
  7. 7. Maintain or repair engines, electric motors, pumps, winches, or other mechanical or electrical equipment, or assist other crew members with maintenance or repair duties.
  8. 8. Maintain complete records of engineering department activities, including machine operations.
  9. 9. Operate or maintain off-loading liquid pumps or valves.
  10. 10. Maintain electrical power, heating, ventilation, refrigeration, water, or sewerage systems.

Key Skills Required

  • Critical Thinking
  • Operations Monitoring
  • Operation and Control
  • Equipment Maintenance
  • Troubleshooting
  • Repairing
  • Active Listening
  • Monitoring
  • Speaking
  • Complex Problem Solving

Knowledge Areas

  • Mechanical
  • English Language
  • Engineering and Technology
  • Public Safety and Security
  • Transportation
  • Mathematics
  • Computers and Electronics
  • Building and Construction
  • Administration and Management
  • Chemistry

Frequently Asked Questions

Will AI replace Ship engineers?

Ship engineers has an AI exposure score of 39%, 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 Ship engineers?

According to BLS Employment Projections 2024-2034, Ship engineers is projected to grow by 1.6% over the decade. Current employment stands at approximately 8,800 workers.

What skills are needed for Ship engineers?

Key skills for Ship engineers include Critical Thinking, Operations Monitoring, Operation and Control, and others. Typical entry-level education is Postsecondary nondegree award.

How much do Ship engineers earn?

The median annual wage for Ship engineers is $101,320, 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 Ship engineers?

The typical entry-level education for Ship engineers is Postsecondary nondegree award. Employers generally expect Less than 5 years of related work experience. On-the-job training typically involves None. Requirements can vary by employer and specialization.

Which companies employ Ship engineers?

Ship engineers 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

1.9
out of 5.0

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

Nationwide occupations with similar workforce profiles

Two data-derived peer sets for Ship engineers: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (39% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (+1.6% here).

Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.

What to do with this

Use Ship engineers' numbers above to compare, not just read in isolation.

AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.

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).

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.

Sources: BLS Employment Projections 2024-2034, O*NET Database 30.0.