57
/100

SOC 45-4022

Logging Equipment Operators

ElevatedFrey/Osborne: 79.0%

Risk Score

โš ๏ธ

57/100

Elevated

US Employment

๐Ÿ‘ฅ

22,520

Total workers

Median Wage

๐Ÿ’ฐ

$49K

$35K โ€“ $72K

Projected Growth

๐Ÿ“ˆ

-1.4%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

31/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Logging Equipment Operators face a risk score of 57/100 โ€” 13 points above the national average of 44. With only 31/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $49K ($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 57/100, Logging Equipment Operators faces moderate automation pressure. While tasks like ai-driven irrigation and soil analysis systems are increasingly handled by AI, the role retains significant human elements. The 22,520 workers in this occupation should focus on strengthening skills in assessing crop health through hands-on field inspection and adapting to variable weather and terrain conditions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Logging Equipment Operators?

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

โš ๏ธ Top Risk Factors

1

AI-driven irrigation and soil analysis systems

2

Drone crop monitoring and precision spraying

3

Satellite and sensor-based yield prediction models

4

Autonomous harvesting and planting machinery

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Assessing crop health through hands-on field inspection

โœ“

Adapting to variable weather and terrain conditions

โœ“

Managing livestock behavior and welfare

โœ“

Operating in unstructured and remote environments

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

Inspect equipment for safety prior to use, and perform necessary basic maintenance tasks.

โ€ข

Control hydraulic tractors equipped with tree clamps and booms to lift, swing, and bunch sheared trees.

โ€ข

Grade logs according to characteristics such as knot size and straightness, and according to established industry or company standards.

โ€ข

Drive straight or articulated tractors equipped with accessories such as bulldozer blades, grapples, logging arches, cable winches, and crane booms to skid, load, unload, or stack logs, pull stumps, or clear brush.

โ€ข

Drive crawler or wheeled tractors to drag or transport logs from felling sites to log landing areas for processing and loading.

๐Ÿ’ป Technology Skills

โ€ข

Data base user interface and query software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Electronic mail software

โ€ข

Word processing software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Public Safety and Security

โ€ข

Production and Processing

โ€ข

Transportation

โ€ข

Administration and Management

๐Ÿ“Š vs National Average

Median Wage$49K
+$3K

National avg: $46K

Risk Score57/100
+13

National avg: 44/100

GenAI Exposure31/100
-7

National avg: 38/100

Projected Growth-1.4%
-5.1%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Social Scientists and Related Workers21$93K57%
Political Scientists25$139K69%
Occupational Health and Safety Specialists and Technicians26$79K67%