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Loading and Moving Machine Operators, Underground Mining

Loading and Moving Machine Operators, Underground Mining — AI exposure, safer roles, and a pivot plan.

Also known as: Buggy Man · Car Dumper · Car Dropper · Car Pincher · Cart Driver · Coke Loader

AI Task Exposure Score

Low exposure

More exposed than 20% of 968 occupations · Rank #750 (1 = most exposed)

This score estimates how exposed the tasks in a role are to current and near-term AI capabilities. It does not predict whether a specific person will lose a job.

Most exposed tasks

Highest structured exposure values in this role’s task mix — the work AI systems can already do most of.

No strongly automatable task in the current data release.

Augmentable tasks

Work where AI assists rather than replaces — the productivity frontier of this role.

  • Drive loaded shuttle cars to ramps and move controls to discharge loads into mine cars or onto conveyors.47
  • Monitor loading processes to ensure that materials are loaded according to specifications.43
  • Clean hoppers, and clean spillage from tracks, walks, driveways, and conveyor decking.41

Most durable tasks

Lowest exposure — typically judgment, relationships, physical presence, or accountability. This is the human moat.

  • Examine roadway and clear obstructions from the path of travel.21
  • Drive machines into piles of material blasted from working faces.27
  • Stop gathering arms when cars are full.27

Task exposure values and classifications come from the versioned data release — they are structured data, not model output. Bars show exposure contribution relative to this role’s task mix.

What this means

A score of 36 puts Loading and Moving Machine Operators, Underground Mining in the least-exposed quarter of analyzed occupations. In practice, exposure this level is about the mix: 0 of 20 analyzed tasks lean automatable, 14 augmentable, and 6 durable. The useful question isn’t “will AI take this job” — it’s which tasks go first, which get faster, and where to reposition time. That’s what the personalized report maps against your actual week.

One next move: lean into the durable core above and adopt AI on the routine remainder before it becomes a mandate.

Lower-exposure adjacent roles

No adjacent role in the current data release is at least 10 points lower with ≥50% skill overlap — we don’t label anything “safer” unless the data supports it.

Labor-market context

  • $74,500median wage
  • 5,930employed
  • 500annual openings
  • -21.9%projected growth

Context only — labor statistics are not inputs to the exposure score. See methodology.

Your week probably doesn’t match the average

This page scores the occupation. The $9 Personalized Risk & Action Report scores your task mix — paste what you actually do and get your own score, confidence level, task matrix, human moat, and a 7/30/90-day plan.

Personalize my result — $9

Related roles

Adjacent by skills or family — no exposure claim implied.

FAQ — Loading and Moving Machine Operators, Underground Mining

What does a score of 36 mean for a Loading and Moving Machine Operators, Underground Mining?
It means that, weighted across the 20 tasks we analyzed for this role, the task mix sits at 36 on a 0–100 exposure scale — in the least-exposed quarter of analyzed occupations. It measures task exposure to current and near-term AI capabilities, not the probability of losing a job.
Which tasks in this role are most exposed to AI?
This role has no strongly automatable task in the current data release.
Which parts of this job are most durable?
The most durable responsibilities are: Examine roadway and clear obstructions from the path of travel; Drive machines into piles of material blasted from working faces; Stop gathering arms when cars are full. Durable tasks typically depend on judgment, relationships, physical presence, or accountability.
Is this score personalized to me?
No — this page shows the occupation-level baseline. Two people with the same title often do different work. The $9 personalized report recalculates the score from the tasks you actually do and builds a concrete 7/30/90-day plan around them.

Score version jr-v1 · data release 2026.07.11-r1 · updated 2026-07-11 · baseline mapping: 20 of 20 tasks carry source-level provenance · methodology