41
/100

SOC 47-5081

Helpers--Extraction Workers

ElevatedFrey/Osborne: 37.0%

Risk Score

โš ๏ธ

41/100

Elevated

US Employment

๐Ÿ‘ฅ

6,720

Total workers

Median Wage

๐Ÿ’ฐ

$48K

$36K โ€“ $68K

Projected Growth

๐Ÿ“ˆ

-1.7%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

10/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Helpers--Extraction Workers face a risk score of 41/100 โ€” 3 points below 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 41/100, Helpers--Extraction Workers faces moderate automation pressure. While tasks like autonomous heavy equipment operation are increasingly handled by AI, the role retains significant human elements. The 6,720 workers in this occupation should focus on strengthening skills in real-time safety judgment in hazardous conditions and fine motor craftsmanship in custom installations to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Helpers--Extraction Workers?

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

โš ๏ธ Top Risk Factors

1

Autonomous heavy equipment operation

2

3D printing of building components

3

AI project scheduling and resource optimization

4

BIM-integrated automated progress tracking

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Real-time safety judgment in hazardous conditions

โœ“

Fine motor craftsmanship in custom installations

โœ“

Adapting to unique building configurations on-site

โœ“

Physical work in confined or elevated spaces

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

Observe and monitor equipment operation during the extraction process to detect any problems.

โ€ข

Drive moving equipment to transport materials and parts to excavation sites.

โ€ข

Unload materials, devices, and machine parts, using hand tools.

โ€ข

Set up and adjust equipment used to excavate geological materials.

โ€ข

Organize materials to prepare for use.

๐Ÿ’ป Technology Skills

โ€ข

Enterprise resource planning ERP software

โ€ข

Word processing software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Electronic mail software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

English Language

โ€ข

Transportation

โ€ข

Mathematics

โ€ข

Administration and Management

๐Ÿ“Š vs National Average

Median Wage$48K
+$2K

National avg: $46K

Risk Score41/100
-3

National avg: 44/100

GenAI Exposure10/100
-28

National avg: 38/100

Projected Growth-1.7%
-5.4%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K67%
Extraction Workers29$56K84%
Electricians32$62K78%