Not Very Resilient

Last Update: 6/19/2026

AI Resilience Score for Extraction Workers:

33.5%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Low

Sustained economic opportunity

Med

Our confidence in this score:
Medium

Contributing sources

Methodology and Scoring Rationale

To score how resilient extraction worker helper roles is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from four AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, and Will Robots Take My Job. 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 extraction worker helpers, six of seven sources had data (Anthropic had none), and they disagreed on AI exposure: Microsoft saw low AI involvement while Will Robots Take My Job saw high, pulling confidence to medium. A low hiring outlook from the BLS Opportunity Score weighed heavily on the final score, leaving this role "Not Very Resilient."

AI Resilience Report forHelpers--Extraction Workers

$48,400 median salary700 annual openingsSOC Code: 47-5081.00

Helpers--Extraction Workers are less resilient to AI impacts than most occupations, according to our analysis of 6 sources.

This career is labeled "Not Very Resilient" because several of its most common tasks are being directly automated by AI. Autonomous haul trucks are already replacing drivers at large mines, and AI-powered drilling systems like Hexagon's Drill Assist are outperforming human operators by 20 to 30 percent, which hits two of the biggest parts of this job.

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This role is not very resilient

This career is labeled "Not Very Resilient" because several of its most common tasks are being directly automated by AI. Autonomous haul trucks are already replacing drivers at large mines, and AI-powered drilling systems like Hexagon's Drill Assist are outperforming human operators by 20 to 30 percent, which hits two of the biggest parts of this job.

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Analysis of Current AI Resilience

Extraction Workers

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Extraction Workers jobs?

If you've ever pictured mining as just pickaxes and hard hats, the reality in 2026 looks a lot more high-tech — but the good news is that AI is mostly helping extraction helpers rather than replacing them. The biggest change is on the haul road: autonomous trucks were first tested in remote iron ore mines in Western Australia in 2008, and now there are nearly 4,000 around the world, with more than half in use in mines in China. In Minnesota, Mesabi Metallics is deploying 400-ton driverless haul trucks as part of a $110 million equipment purchase, directly affecting the "drive moving equipment" task.

AI is also entering drilling — Hexagon's Drill Assist uses an AI engine that monitors machine feedback every 10 milliseconds [1] and has produced productivity gains of 20–30% over the best human operators, helping with the "observe and monitor equipment" task. Deloitte's 2026 Mining and Metals Industry Outlook [2] expects miners to scale autonomous hauling, drilling, AI-enabled process control, and predictive maintenance, while keeping humans in charge of safety-critical decisions. Importantly, a mining engineering professor told Marketplace [3] that the practice in the world shows that automation doesn't reduce jobs — it changes the nature of the job, shifting roles toward control room operators and data analysts.

Hands-on assistance with rigging, cleanup, and equipment dismantling still depends on humans, as a Permian Basin floorhand described in a recent BLS Career Outlook interview [4].

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AI Adoption

How fast is AI adoption growing for Extraction Workers?

Adoption is moving quickly in some places and slowly in others. Pushing it forward: a severe skills crunch. The CIM article notes a severe labour shortage in which it can take about a decade to train a driller to expert level, making AI tools attractive.

Global Mining Review predicts smaller, agile miners will lead innovation [5] because they lack legacy systems. Slowing adoption: high equipment costs (those Komatsu trucks aren't cheap), underground navigation limits, union caution, and risk aversion — miners are really risk averse, and the last thing they want is plans designed automatically that aren't good. The encouraging takeaway: human judgment, teamwork, and adaptability still matter, and workers who build digital and safety skills will be well positioned for the future.

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Will AI replace Extraction Workers?

Will AI replace Extraction Workers?

In part. We think AI will eventually automate a real share of this work, but there will still be tasks and transitions that need human hands and judgment.

The numbers here are honest: a 33.5% AI Resilience Score puts this role in a genuinely exposed position. Autonomous haul trucks are already operating at scale around the world, and AI-assisted drilling tools have shown productivity gains of 20 to 30% over experienced human operators [1]. Deloitte expects miners to keep scaling these technologies through the coming years [2]. At the same time, hands-on work like rigging, cleanup, and equipment dismantling still depends on people, and a mining engineering professor noted that automation tends to change the nature of jobs rather than eliminate them outright [3].

The more important question for anyone early in this career is where to go next. Workers who build digital skills, safety expertise, and comfort with monitoring technology will be better positioned to move into control room and data roles as the industry shifts. The extraction sector is facing a real skills crunch [1], which means people who adapt will have options. This job may look different in ten years, but the skills you build here can carry you further than this one role.

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Latest AI news for Extraction Workers

These articles highlight how AI is transforming careers in extraction industries, emphasizing both efficiency and new challenges. For instance, the piece on gold mining reveals how AI enhances safety and resource management, which can lead to more sustainable practices. Meanwhile, the article on AI moderation sheds light on the psychological toll of AI training, reminding future workers to prioritize mental well-being. Embracing AI in these roles offers resilience, enabling workers to adapt and thrive in a rapidly evolving landscape.

More Career Info

Career: Helpers--Extraction Workers

They assist miners by carrying tools and equipment, clearing debris, and ensuring safety to help extract minerals and resources from the ground.

Employment & Wage Data

Median Wage

$48,400

Jobs (2024)

7,000

Growth (2024-34)

-1.7%

Annual Openings

700

Education

High school diploma or equivalent

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

92% ResilienceCore Task

Repair and maintain automotive and drilling equipment, using hand tools.

2

90% ResilienceCore Task

Provide assistance to extraction craft workers, such as earth drillers and derrick operators.

3

90% ResilienceCore Task

Unload materials, devices and machine parts, using hand tools.

4

88% ResilienceCore Task

Dismantle extracting and boring equipment used for excavation, using hand tools.

5

87% ResilienceSupplemental

Signal workers to start geological material extraction or boring.

6

85% ResilienceSupplemental

Load materials into well holes or into equipment, using hand tools.

7

82% ResilienceCore Task

Clean up work areas and remove debris after extraction activities are complete.

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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