38
/100

SOC 53-5021

Captains, Mates, and Pilots of Water Vessels

ModerateFrey/Osborne: 27.0%

Risk Score

โš ๏ธ

38/100

Moderate

US Employment

๐Ÿ‘ฅ

35,390

Total workers

Median Wage

๐Ÿ’ฐ

$86K

$46K โ€“ $164K

Projected Growth

๐Ÿ“ˆ

+0.5%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

38/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Captains, Mates, and Pilots of Water Vessels face a risk score of 38/100 โ€” 6 points below 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 $86K ($39K above the national median). The 3 recommended career transitions offer lower AI risk while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 38/100, Captains, Mates, and Pilots of Water Vessels faces moderate automation pressure. While tasks like ai route optimization reducing dispatcher roles are increasingly handled by AI, the role retains significant human elements. The 35,390 workers in this occupation should focus on strengthening skills in emergency situation response and quick decision-making and manual loading of irregular and fragile cargo to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Captains, Mates, and Pilots of Water Vessels?

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

โš ๏ธ Top Risk Factors

1

AI route optimization reducing dispatcher roles

2

Automated warehouse sorting and loading systems

3

Autonomous vehicle and self-driving truck technology

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Emergency situation response and quick decision-making

โœ“

Manual loading of irregular and fragile cargo

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

Direct courses and speeds of ships, based on specialized knowledge of local winds, weather, water depths, tides, currents, and hazards.

โ€ข

Prevent ships under navigational control from engaging in unsafe operations.

โ€ข

Serve as a vessel's docking master upon arrival at a port or at a berth.

โ€ข

Consult maps, charts, weather reports, or navigation equipment to determine and direct ship movements.

โ€ข

Steer and operate vessels, using radios, depth finders, radars, lights, buoys, or lighthouses.

๐Ÿ’ป Technology Skills

โ€ข

Operating system software

โ€ข

Computer aided design CAD software

โ€ข

Facilities management software

โ€ข

Route navigation software

โ€ข

Analytical or scientific software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Transportation

โ€ข

Public Safety and Security

โ€ข

Mechanical

โ€ข

Law and Government

โ€ข

English Language

๐Ÿ“Š vs National Average

Median Wage$86K
+$39K

National avg: $46K

Risk Score38/100
-6

National avg: 44/100

GenAI Exposure38/100
0

National avg: 38/100

Projected Growth0.5%
-3.2%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Air Transportation Workers31$107K74%
Ship Engineers33$101K70%
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K81%