55
/100

SOC 47-4061

Rail-Track Laying and Maintenance Equipment Operators

ElevatedFrey/Osborne: 89.0%

Risk Score

โš ๏ธ

55/100

Elevated

US Employment

๐Ÿ‘ฅ

16,480

Total workers

Median Wage

๐Ÿ’ฐ

$67K

$46K โ€“ $85K

Projected Growth

๐Ÿ“ˆ

+1.6%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

21/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Rail-Track Laying and Maintenance Equipment Operators face a risk score of 55/100 โ€” 11 points above the national average of 44. With only 21/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $67K ($21K 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, Rail-Track Laying and Maintenance Equipment Operators faces moderate automation pressure. While tasks like bim-integrated automated progress tracking are increasingly handled by AI, the role retains significant human elements. The 16,480 workers in this occupation should focus on strengthening skills in adapting to unique building configurations on-site and real-time safety judgment in hazardous conditions to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Rail-Track Laying and Maintenance Equipment Operators?

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

โš ๏ธ Top Risk Factors

1

BIM-integrated automated progress tracking

2

3D printing of building components

3

Autonomous heavy equipment operation

4

AI project scheduling and resource optimization

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Adapting to unique building configurations on-site

โœ“

Real-time safety judgment in hazardous conditions

โœ“

Physical work in confined or elevated spaces

โœ“

Navigating unpredictable and unstructured job sites

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

Patrol assigned track sections so that damaged or broken track can be located and reported.

โ€ข

Repair or adjust track switches, using wrenches and replacement parts.

โ€ข

Weld sections of track together, such as switch points and frogs.

โ€ข

Observe leveling indicator arms to verify levelness and alignment of tracks.

โ€ข

Operate single- or multiple-head spike driving machines to drive spikes into ties and secure rails.

๐Ÿ’ป Technology Skills

โ€ข

Enterprise resource planning ERP software

โ€ข

Spreadsheet software

โ€ข

Office suite software

โ€ข

Time accounting software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Transportation

โ€ข

Mechanical

โ€ข

Building and Construction

โ€ข

Public Safety and Security

โ€ข

Administration and Management

๐Ÿ“Š vs National Average

Median Wage$67K
+$21K

National avg: $46K

Risk Score55/100
+11

National avg: 44/100

GenAI Exposure21/100
-17

National avg: 38/100

Projected Growth1.6%
-2.1%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K55%
Supervisors of Construction and Extraction Workers33$79K74%
Extraction Workers29$56K72%