Somewhat Resilient
Last Update: 6/19/2026
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
$67,220 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.
Learn more about how you can thrive in this position
Learn more about how you can thrive in this position
This role is somewhat resilient
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.
Read full analysisAnalysis 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 tougher environments on earth for automation to crack. GPS doesn't reach a mile underground, tight tunnels complicate navigation, and converting existing facilities to autonomous systems is significantly harder than doing so above ground [5]. Equipment makers are making progress, with roadmaps pointing toward operators managing multiple machines from surface control rooms rather than sitting inside them [2], but real-world deployment is still limited and concentrated in specific equipment like drilling rigs and haul trucks [1].
What stays human is meaningful. Positioning roof supports, replacing worn parts, and responding to the unpredictable conditions of a live mine are genuinely hard to automate. Experts also note that automation tends to change the nature of mining jobs rather than eliminate them, creating demand for control room operators and people comfortable with sensors and remote systems.
The honest part of the picture is that long-term employer demand for this specific role is low, and our 46.6% AI Resilience Score reflects real pressure ahead. The workers most likely to thrive are those who pair traditional underground know-how with comfort using the digital tools now layering onto familiar machines [4]. The job is evolving. It is not disappearing.
Sources

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Latest AI news for Underground Mining Ops
These articles highlight the transformative impact of AI on underground mining machine operators. For instance, the AI safety systems discussed in "From camera clarity to collision avoidance" enhance visibility and prevent accidents, crucial for operator safety. Additionally, "Simulating autonomous mining operations" shows how AI can optimize truck operations, which could lead to more efficient workflows for operators. Embracing AI technologies not only improves safety but also creates opportunities for operators to engage with advanced tools, ensuring resilience and adaptability in their careers.

From camera clarity to collision avoidance: What ‘AI in mining’ actually looks like in 2026
www.mining-technology.com • 6/16/2026
Learn how AI mining safety systems support visibility, detection, collision avoidance and operational readiness in demanding underground...

Autonomous Drilling Technology: AI-Driven Revolution in Mining and Oil Operations
discoveryalert.com.au • 4/24/2026
Discover how autonomous drilling technology revolutionizes mining and energy operations with AI-powered precision systems.

AI-Based Forecasting Tools Revolutionising Mining Operations 2026
discoveryalert.com.au • 3/13/2026
AI-based forecasting tools in mining optimize operations through predictive analytics, equipment monitoring, and risk assessment.

AI-led enhancements could boost mining safety
im-mining.com • 9/18/2025
The advent of advanced safety technologies marks a turning point in how risks on mine sites are managed, viAct says.

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.
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
$67,220
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.
