Evolving

Last Update: 3/13/2026

Your role’s AI Resilience Score is

45.9%

Median Score

Changing Fast

Evolving

Stable

Our confidence in this score:
Medium

What does this resilience result mean?

These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.

AI Resilience Report for

Loading and Moving Machine Operators, Underground Mining

They operate machines to load and move materials like coal or ore in underground mines, ensuring everything is safely transported to the surface.

This role is evolving

The career of Loading and Moving Machine Operators in Underground Mining is labeled as "Evolving" because AI technology is gradually being integrated to assist workers rather than replace them. While some tasks like operating heavy equipment can be done remotely or with autonomous vehicles, many hands-on activities still require human skill.

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Learn more about how you can thrive in this position

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Chat with Coach
Latest news
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This role is evolving

The career of Loading and Moving Machine Operators in Underground Mining is labeled as "Evolving" because AI technology is gradually being integrated to assist workers rather than replace them. While some tasks like operating heavy equipment can be done remotely or with autonomous vehicles, many hands-on activities still require human skill.

Read full analysis

Contributing Sources

We aggregate scores from multiple models and supplement with employment projections for a more accurate picture of this occupation’s resilience. Expand to view all sources.

AI Resilience

AI Resilience Model v1.0

AI Task Resilience

Learn about this score
Evolving iconEvolving

48.0%

48.0%

Microsoft's Working with AI

AI Applicability

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Stable iconStable

90.9%

90.9%

Will Robots Take My Job

Automation Resilience

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Changing fast iconChanging fast

1.4%

1.4%

Althoff & Reichardt

Economic Growth

Learn about this score
Evolving iconEvolving

47.7%

47.7%

Low Demand

Labor Market Outlook

We use BLS employment projections to complement the AI-focused assessments from other sources.

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Growth Rate (2024-34):

-22.3%

Growth Percentile:

0.7%

Annual Openings:

500

Annual Openings Pct:

5.3%

Analysis of Current AI Resilience

Underground Mining Ops

Updated Quarterly • Last Update: 2/17/2026

Analysis
Suggested Actions
State of Automation

What's changing and what's not

In some modern mines, operators already run heavy equipment from afar. For example, one system lets loaders be controlled from a surface room using cameras and joysticks [1]. This setup keeps people out of danger and cuts downtime [1].

Even autonomous vehicles are being tested underground – researchers have shown a truck guided by colored LED strips on the roof to follow a set path [2]. Conveyors are getting “smart” too: new systems use AI cameras and sensors to spot belt problems (like hot rollers or misaligned belts) and alert crews immediately [3]. In fact, labs have built small robots that automatically inspect long conveyor lines so people don’t have to walk them [4].

Despite these advances, many tasks remain hands-on. Miners still clear fallen rock, reroute heavy power cables, and refuel or fix machines by hand – there’s no robot grabbing a crowbar to pry loose material yet. Today’s AI mostly works in the background: it “watches” machine data, flags issues (overheating, jams, etc.), and tells crews what to fix [3] [5].

Overall, smart technology is slowly joining underground work, but it mainly assists miners rather than replacing them [6] [5].

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AI Adoption

AI in the real world

New systems are growing steadily but selectively. Underground mines are very harsh on electronics (no GPS, heavy dust), so fully driverless gear is hard to implement [2]. Automation equipment is also expensive, so it’s mostly used in larger mines.

However, mines will invest when there’s pressure: for example, moving operators out of harm’s way is a big safety win [1]. One mining panelist noted U.S. mines had roughly 50% annual turnover among haul-truck drivers; after introducing autonomous trucks, none of those workers quit – they were retrained for other roles [7] [7]. This shows that labor shortages and safety concerns can speed up adoption.

Cost and job issues also play a role. Workers in this field earn a good wage (about $30.81/hour on average [8]), so any robot must clearly save more than that to pay off. Many core duties (like shoring up roofs, clearing cable tangles, servicing equipment) still need human skill.

In practice, experts emphasize that automation tends to change jobs rather than wipe them out [7] [7]. In fact, miners usually move into new positions running and maintaining the smart machines. With proper training, a miner might oversee data from sensors or guide automated loaders – so people and AI work together, not one replacing the other [7] [7].

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More Career Info

Career: Loading and Moving Machine Operators, Underground Mining

Employment & Wage Data

Median Wage

$68,860

Jobs (2024)

6,400

Growth (2024-34)

-22.3%

Annual Openings

500

Education

No formal educational credential

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2024-2034

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

70% ResilienceCore Task

Pry off loose material from roofs and move it into the paths of machines, using crowbars.

2

65% ResilienceSupplemental

Push or ride cars down slopes, or hook cars to cables and control cable drum brakes, to ease cars down inclines.

3

65% ResilienceSupplemental

Estimate and record amounts of material in bins.

4

60% ResilienceCore Task

Clean, fuel, and service equipment, and repair and replace parts as necessary.

5

60% ResilienceSupplemental

Guide and stop cars by switching, applying brakes, or placing scotches, or wooden wedges, between wheels and rails.

6

60% ResilienceSupplemental

Maintain records of materials moved.

7

60% ResilienceSupplemental

Inspect boarding and locking of open-top box cars and wedging of side-drop and hopper cars to prevent loss of material in transit.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

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