As of July 2026, Continuous Mining Machine Operators has an AI-exposure score of 34/100 (Low exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Felten, Raj and Seamans AIOE index. BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Continuous Mining Machine Operators

34/100
Low exposure
LowModerateElevatedHighVery High

More exposed than 3% of the roles we track. Median pay ~US$61,810. About 1,600 projected openings a year (BLS 2024–34 - growth plus replacement).

Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.

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Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 exact occupation

Operate self-propelled mining machines that rip coal, metal and nonmetal ores, rock, stone, or sand from the mine face and load it onto conveyors, shuttle cars, or trucks in a continuous operation.

Common titles
Continuous Miner Operator (CMO)Continuous Mining Machine OperatorContinuous Mining Operator (CMO)Miner OperatorBore Miner OperatorContinuous Miner
O*NET job-zone preparation
Job Zone 2 · Some Preparation Needed These occupations usually require a high school diploma. Some previous work-related skill, knowledge, or experience is usually needed.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
Operation and ControlCritical ThinkingJudgment and Decision MakingComplex Problem SolvingMonitoringSpeaking
Tools and technology
Microsoft ExcelMicrosoft Office softwareMicrosoft PowerPointMicrosoft WordFleet monitoring system softwareHitachi ZXLink
Work context
Face-to-face discussionsFrequent contact with othersConsequence of errorDecision latitudeRepeating tasks

Source: O*NET 29.1 exact occupation - Continuous Mining Machine Operators, SOC 47-5041.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Continuous Mining Machine Operators tasks, by AI exposure

Automatable

No automatable tasks identified for this role - its real, individually-assessed tasks consistently read as durable (87%).

Augmentable
  • Apply new technologies developed to minimize the environmental impact of coal mining.
  • Observe and listen to equipment operation to detect binding or stoppage of tools or other equipment malfunctions.
Durable
  • Repair, oil, and adjust machines, and change cutting teeth, using wrenches.
  • Move levers to raise and lower hydraulic safety bars supporting roofs above machines until other workers complete framing.
11 more durable tasks locked in the report.

We analyzed all 15 Continuous Mining Machine Operators tasks - 2 augmentable and 13 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

This role is already among lower-exposure work. The adjacent paths below are shown for opportunity and skill transfer, not as lower-exposure alternatives.

Excavating and Loading Machine and Dragline Operators, Surface Mining
80% skills overlap; 7 points higher - higher exposure; Moderate band; ~US$57,430
View path
41
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Apply new technologies developed to minimize the environmental impact of coal mining.

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
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Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.