Somewhat Resilient
Last Update: 7/31/2026
AI Resilience Score for Underground Mining Ops:
46.6%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
High
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Very few data sources cover this career, or the available sources disagree significantly. Treat this score as a rough estimate.
Contributing sources
AI Resilience Report forUnderground Mining Machine Operators, All Other
$70,130 median salary•400 annual openings•SOC 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.
Underground mining machine operators are seeing their work meaningfully shift as AI and automation take over some repetitive tasks like hauling and drilling, but the career is holding up because many of the hands-on skills involved are genuinely hard for machines to replicate in tight, unpredictable underground environments. Navigation technology for deep underground spaces is still catching up, and converting existing mines to fully autonomous systems remains a real technical challenge, which keeps human operators in the picture for now.
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Underground mining machine operators are seeing their work meaningfully shift as AI and automation take over some repetitive tasks like hauling and drilling, but the career is holding up because many of the hands-on skills involved are genuinely hard for machines to replicate in tight, unpredictable underground environments. Navigation technology for deep underground spaces is still catching up, and converting existing mines to fully autonomous systems remains a real technical challenge, which keeps human operators in the picture for now.
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View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreAnalysis of Current AI Resilience
Underground Mining Ops
Updated Quarterly
How is AI changing Underground Mining Ops jobs?
The underground mining industry is moving steadily toward automation, but most of what's happening today augments operators rather than fully replacing them. A 2025 review in the Society for Mining, Metallurgy & Exploration's journal found that robotic autonomous systems offer transformative potential for mining by enhancing safety and productivity, but the absence of comprehensive real-world implementation data hinders adoption, with deployments concentrated in drilling rigs, haul trucks, and earthmoving equipment (Mining Engineering Online [1]). Equipment makers are now layering AI on top of familiar machines: Komatsu's roadmap for the Joy continuous miner points toward full-section automation where an operator oversees multiple machines via advanced interfaces such as VR or digital control hubs, with the long-term vision of operators managing equipment from the surface, creating safer and more attractive working conditions (Coal Age [2]).
Navigation is a key breakthrough — Advanced Navigation's Chimera Land sensor is designed to solve the primary challenge for underground mining: maintaining precise vehicle positioning in deep, dark, and unmapped environments where GPS cannot reach (International Mining [3]).
Sources
How fast is AI adoption growing for Underground Mining Ops?
Adoption is being pulled forward by economics and safety, but slowed by the realities of working a mile underground. McKinsey notes that robotics is expanding the frontier of automation and, although still early, advances in robotic systems could dramatically improve safety, utilization, and consistency by enabling machines to perform complex physical work with minimal human intervention (McKinsey [4]). Autonomous haul trucks are scaling above ground — operators say autonomous trucks are safer because "mistakes happen" and the system "very safely watches all its surroundings" — but a Colorado School of Mines professor cautioned that it's more difficult to convert existing facilities, especially underground mines, to autonomous systems, because navigation systems don't work well underground in tight spaces (Marketplace [5]).
Regulation is also a brake: a 2025 review of MSHA's rulemaking found the agency is proposing to modernize outdated rules and permit modern equipment, like electronic surveying tools, while removing obsolete requirements tied to outdated technology (Jackson Lewis [6]). The encouraging news for young workers: experts report that the practice in the world shows that automation doesn't reduce jobs — it changes the nature of the job, so mines will need more control room operators and data analysts. Hands-on skills like positioning roof supports and replacing worn machine parts remain hard to automate, so people who pair traditional mining know-how with comfort using sensors, cameras, and remote-control hubs will be in strong demand.
Sources
Will AI replace Underground Mining Ops?
Not entirely. We think AI will take over some tasks, but not the whole job.
Underground mining is one of the toughest environments on earth for automation. GPS doesn't reach a mile underground, tight tunnels complicate navigation, and converting existing facilities to autonomous systems is genuinely harder than doing it above ground [5]. Equipment makers are making progress, but a 2025 review found that the absence of comprehensive real-world implementation data still hinders adoption of robotic systems in mining [1].
What's actually happening is augmentation. Komatsu's roadmap for continuous miners points toward operators supervising multiple machines from advanced control hubs, not operators disappearing entirely [2]. Hands-on tasks like positioning roof supports and replacing worn parts remain difficult to automate. People who pair traditional mining know-how with comfort using sensors, cameras, and remote-control systems will be well positioned as the job evolves.
The honest part: our 46.6% AI Resilience Score puts this role below average, and the long-term job market outlook is weak. Expect real workflow changes and fewer openings over time. But the core human contribution here is rated high, and experts note that automation tends to change the nature of mining jobs rather than eliminate them outright. Staying current with the technology is the most practical thing you can do.
Sources
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Latest AI news for Underground Mining Ops
As underground mining machine operators, understanding AI's role in the industry is crucial. Newmont's strategy highlights how autonomous systems and digital twins can enhance safety and efficiency, suggesting operators may work alongside advanced technology. Similarly, the simulation of autonomous trucks by Boliden demonstrates how AI can optimize logistics and workflow, directly impacting operations. Embracing these innovations fosters AI resilience, ensuring operators are equipped to adapt to evolving technologies that improve mine safety and productivity.
Advanced AI-Driven Automation Transforming Mine Site Management Operations
discoveryalert.com.au • 3/5/2026
Modern mining operations face unprecedented challenges requiring intelligent solutions that transform traditional management approaches. The...
Brazil Potash Trials AI Ore-Sorting Technology to Cut Costs and Boost Sustainability
www.azomining.com • 12/12/2025
The AI optical sorting trial at Autazes Project showcases advancements in potash extraction, highlighting economic and environmental...
Newmont’s AI Strategy: Analysis of Dominance in Mining AI
www.klover.ai • 8/4/2025
Newmont's AI strategy integrates autonomous systems, digital twins, and 5G to dominate the future of mining.
Simulating autonomous mining operations using Robotec.ai on AWS
aws.amazon.com • 7/1/2024
In this post, you'll learn how Boliden simulates multiple autonomous trucks in a mine, and scales those simulations to run dozens of scenarios simultaneously.
Application of artificial intelligence in mine ventilation: a brief review
www.frontiersin.org • 5/1/2024
In recent years, there has been a notable integration of artificial intelligence (AI) technologies into mine ventilation systems.
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.
Parent Careers
Similar Careers
Employment & Wage Data
Median Wage
$70,130
Jobs (2024)
3,600
Growth (2024-34)
-6.1%
Annual Openings
400
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
Free jams in planer hoppers, using metal pinch bars.
2
Position jacks, timbers, or roof supports, and install casings, to prevent cave-ins.
3
Replace worn or broken tools and machine bits and parts, using wrenches, pry bars, and other hand tools, and lubricate machines, using grease guns.
4
Signal truck drivers to position their vehicles for receiving shale from planer hoppers.
5
Move controls to start and position drill cutters or torches and advance tools into mines or quarry faces to complete horizontal or vertical cuts.
6
Reposition machines and move controls to make additional holes or cuts.
7
Move planer levers to control and adjust the movement of equipment, the speed, height, and depth of cuts, and to rotate swivel cutting booms.
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.
