53
/100

SOC 53-5011

Sailors and Marine Oilers

ElevatedFrey/Osborne: 83.0%

Risk Score

โš ๏ธ

53/100

Elevated

US Employment

๐Ÿ‘ฅ

31,360

Total workers

Median Wage

๐Ÿ’ฐ

$50K

$33K โ€“ $82K

Projected Growth

๐Ÿ“ˆ

+2.3%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

38/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Sailors and Marine Oilers face a risk score of 53/100 โ€” 9 points above the national average of 44. With only 38/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $50K ($3K above the national median). 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 53/100, Sailors and Marine Oilers 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 31,360 workers in this occupation should focus on strengthening skills in navigating complex urban environments with obstacles and emergency situation response and quick decision-making to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Sailors and Marine Oilers?

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

Drone delivery displacing last-mile logistics workers

3

AI route optimization reducing dispatcher roles

4

Automated warehouse sorting and loading systems

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Navigating complex urban environments with obstacles

โœ“

Emergency situation response and quick decision-making

โœ“

Manual loading of irregular and fragile cargo

โœ“

Customer interaction and conflict resolution during delivery

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

Tie barges together into tow units for tugboats to handle, inspecting barges periodically during voyages and disconnecting them when destinations are reached.

โ€ข

Attach hoses and operate pumps to transfer substances to and from liquid cargo tanks.

โ€ข

Handle lines to moor vessels to wharfs, to tie up vessels to other vessels, or to rig towing lines.

โ€ข

Read pressure and temperature gauges or displays and record data in engineering logs.

โ€ข

Stand watch in ships' bows or bridge wings to look for obstructions in a ship's path or to locate navigational aids, such as buoys or lighthouses.

๐Ÿ’ป Technology Skills

โ€ข

Facilities management software

โ€ข

Data base user interface and query software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Electronic mail software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Public Safety and Security

โ€ข

Transportation

โ€ข

Mechanical

โ€ข

Education and Training

โ€ข

Administration and Management

๐Ÿ“Š vs National Average

Median Wage$50K
+$3K

National avg: $46K

Risk Score53/100
+9

National avg: 44/100

GenAI Exposure38/100
0

National avg: 38/100

Projected Growth2.3%
-1.4%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K71%
Aircraft Cargo Handling Supervisors29$64K78%
Air Transportation Workers31$107K74%