55
/100

SOC 53-7031

Dredge Operators

ElevatedFrey/Osborne: 92.0%

Risk Score

โš ๏ธ

55/100

Elevated

US Employment

๐Ÿ‘ฅ

1,030

Total workers

Median Wage

๐Ÿ’ฐ

$48K

$42K โ€“ $75K

Projected Growth

๐Ÿ“ˆ

+1.2%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

10/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Dredge Operators face a risk score of 55/100 โ€” 11 points above the national average of 44. With only 10/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $48K ($2K 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 55/100, Dredge Operators faces moderate automation pressure. While tasks like drone delivery displacing last-mile logistics workers are increasingly handled by AI, the role retains significant human elements. The 1,030 workers in this occupation should focus on strengthening skills in navigating unpredictable road and weather conditions and emergency situation response and quick decision-making to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Dredge Operators?

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

โš ๏ธ Top Risk Factors

1

Drone delivery displacing last-mile logistics workers

2

Autonomous vehicle and self-driving truck technology

3

Automated warehouse sorting and loading systems

4

Predictive maintenance reducing manual inspection needs

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Navigating unpredictable road and weather conditions

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

Move levers to position dredges for excavation, to engage hydraulic pumps, to raise and lower suction booms, and to control rotation of cutterheads.

โ€ข

Start and stop engines to operate equipment.

โ€ข

Start power winches that draw in or let out cables to change positions of dredges, or pull in and let out cables manually.

โ€ข

Pump water to clear machinery pipelines.

โ€ข

Lower anchor poles to verify depths of excavations, using winches, or scan depth gauges to determine depths of excavations.

๐Ÿ’ป Technology Skills

โ€ข

Mobile location based services software

โ€ข

Industrial control software

โ€ข

Data base user interface and query software

โ€ข

Map creation software

โ€ข

Internet browser software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

English Language

โ€ข

Public Safety and Security

โ€ข

Administration and Management

โ€ข

Production and Processing

๐Ÿ“Š vs National Average

Median Wage$48K
+$2K

National avg: $46K

Risk Score55/100
+11

National avg: 44/100

GenAI Exposure10/100
-28

National avg: 38/100

Projected Growth1.2%
-2.5%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
First-Line Supervisors of Transportation and Material Moving Workers, Except Aircraft Cargo Handling Supervisors25$62K75%
Aircraft Cargo Handling Supervisors29$64K82%
Air Transportation Workers31$107K78%