Somewhat Resilient

Last Update: 8/30/2026

AI Resilience Score for Underground Mining Ops:

47.5%

Median Score

Meaningful human contribution

High

Long-term employer demand

Low

Sustained economic opportunity

Med

Our confidence in this score:
Low

Contributing sources

Methodology and Scoring Rationale

To score how resilient underground mining machine operation is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For underground mining machine operators, only three of the eight sources had data, which is why confidence is low. The AI Resilience Model rated AI exposure as High resilience, meaning the physical underground work stays human, but the BLS Opportunity Score flagged weak hiring demand. That gap between strong human contribution and soft demand lands this role at "Somewhat Resilient."

AI Resilience Report forUnderground Mining Machine Operators, All Other

$70,130 median salary300 annual openingsSOC Code: 47-5049.00

Underground Mining Machine Operators, All Other are somewhat less resilient to AI impacts than most occupations, according to our analysis of 3 sources.

This career sits in the "Somewhat Resilient" category because AI is genuinely changing how underground mining machine operators work, even if it is not replacing them outright. Tools like tele-remote controls and AI vision systems are taking over some of the routine monitoring and hazard detection tasks that operators used to handle entirely on their own, which means the job is shifting rather than disappearing.

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This role is somewhat resilient

This career sits in the "Somewhat Resilient" category because AI is genuinely changing how underground mining machine operators work, even if it is not replacing them outright. Tools like tele-remote controls and AI vision systems are taking over some of the routine monitoring and hazard detection tasks that operators used to handle entirely on their own, which means the job is shifting rather than disappearing.

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Analysis of Current AI Resilience

Underground Mining Ops

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Underground Mining Ops jobs?

If you're thinking about a career underground, here's the honest picture: AI is showing up in mines, but mostly as a helper — not a replacement. The Society for Mining, Metallurgy & Exploration [1] reports that the development and integration of automation, robotic systems, artificial intelligence (AI), machine learning (ML), internet of things (IoT), digital twins, drones, remote monitoring and other intelligent systems are now a regular part of industry conversations. In practice, that looks like tele-remote and AI-assisted controls: Coal Age describes Liebherr's LiReCon teleoperations system [2], a dedicated operator workspace with all necessary controls, and onboard installations including cameras providing multiple angles and views, microphones for recording machine sounds and a radio link receiver and transmitter, which frees the operator from the machine and enables access to extraction areas in hazardous zones.

AI vision systems are also being layered on for collision avoidance and operational readiness in demanding underground mining environments [3]. Your "listening for problems" and "watching gauges" tasks are exactly what AI is now augmenting.

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AI Adoption

How fast is AI adoption growing for Underground Mining Ops?

Adoption is real but slower than in other industries. PwC's Mine 2026 report [4] found that mining had the lowest score of any sector on our AI fitness index, held back by weak data foundations. Still, a McKinsey partner cited at a 2026 mining symposium [5] noted that 59% of the hours currently worked in mining could be automated [6], using already available technologies, and that several mining companies are investing in automation and AI, not necessarily to reduce staff, but to grow and reallocate time towards higher-value tasks.

Global Mining Review echoes this [7], noting automation is transforming the nature of work, but people remain at the core of mining's digital evolution, and forward-thinking firms are investing in workforce development by teaching digital literacy, automation skills, and adaptable problem-solving. The U.S. Bureau of Labor Statistics [8] projects about 83,200 openings for material moving machine operators each year, on average, over the decade — so hands-on skills like installing roof supports and repairing equipment stay in demand, especially as operators upskill into remote-control and diagnostic roles.

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Will AI replace Underground Mining Ops?

Will AI replace Underground Mining Ops?

Not entirely. We think AI will take over some tasks, but not the whole job.

Underground mining is genuinely changing. Teleoperations systems now let operators run machines from dedicated control rooms rather than sitting inside the equipment itself [2], and AI vision tools are being added for collision avoidance in demanding underground environments [3]. A McKinsey analysis cited at a 2026 mining symposium estimated that 59% of hours worked in mining could be automated using already available technologies [6]. That is a real number worth taking seriously.

But "could be automated" is not the same as "will be replaced." Mining had the lowest AI fitness score of any sector in PwC's Mine 2026 report, held back by weak data foundations [4]. Adoption is slower here than almost anywhere else. And the tasks that stay hardest to automate, reading a machine's sounds, responding to unexpected underground conditions, making judgment calls in hazardous spaces, are exactly where human operators still matter most.

Our 47.5% AI Resilience Score reflects that tension honestly. The job market outlook through 2034 is soft, so we would not call this a career with easy long-term security. But operators who build skills in remote control systems and digital diagnostics are positioning themselves for the version of this work that actually survives, and that path is real.

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Latest AI news for Underground Mining Ops

These articles highlight how AI and automation are reshaping careers for underground mining machine operators. For instance, the piece on predictive maintenance shows how AI can anticipate equipment issues, enhancing safety and efficiency. Meanwhile, the discussion on automation emphasizes that while some tasks may evolve, the human touch remains essential in operating complex machinery. Embracing these changes can lead to a resilient career path, where operators adapt and thrive amidst technological advancements in the mining industry.

More Career Info

Career: Underground Mining Machine Operators, All Other

They operate machines underground to safely extract minerals and resources from the earth, ensuring efficient and smooth mining operations.

Employment & Wage Data

Median Wage

$70,130

Jobs (2025)

3,200

Growth (2025-35)

-1.0%

Annual Openings

300

Education

No formal educational credential

Experience

None

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

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

1

90% ResilienceSupplemental

Guide and assist crews in laying track for machines and resetting planer rails, supports, and blocking, using jacks, shovels, sledges, picks, and pinch bars.

2

88% ResilienceCore Task

Position jacks, timbers, or roof supports, and install casings, to prevent cave-ins.

3

86% ResilienceSupplemental

Free jams in planer hoppers, using metal pinch bars.

4

85% ResilienceSupplemental

Remove debris such as loose shale from channels and planer travel areas.

5

82% ResilienceCore Task

Replace worn or broken tools and machine bits and parts, using wrenches, pry bars, and other hand tools, and lubricate machines, using grease guns.

6

65% ResilienceSupplemental

Drive mobile, truck-mounted, or track-mounted drilling or cutting machine in mines and quarries or on construction sites.

7

62% ResilienceCore Task

Reposition machines and move controls to make additional holes or cuts.

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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