How Exposed Are Helpers--Extraction Workers to AI? — The 2026 Risk Report

Helpers--Extraction Workers professional at work with AI overlay

Help extraction craft workers, such as earth drillers, blasters and explosives workers, derrick operators, and mining machine operators, by performing duties requiring less skill. Duties include supplying equipment or cleaning work area.

Data sources: O*NET 29.0, BLS OES. AI capability mapping updated March 2026. Task exposure does not equal full job replacement.

Key Statistics

AI Risk Score
6.5% (low risk)
Median Annual Salary
$64,900
Employment Growth
+5%
Total Employment
108,621
Risk Timeline
Minimal foreseeable impact

Risk Profile

AI Exposure
6.5%
Human Moat
9%
Pivot Ease
0%
AI Augmentation
45%

How exposed are Helpers--Extraction Workers to AI?

How much of this job can AI handle in each area (0% = no AI capability, 100% = fully automatable):

Text & Language Processing
74.6%
Data Analysis & Pattern Recognition
77.8%
Visual & Creative Work
66.5%
Code & Logical Reasoning
58.6%
Physical & Manual Tasks
11.0%
Social & Emotional Intelligence
7.6%

AI exposure dimensions for Helpers--Extraction Workers: Text & Language Processing: 74.6%, Data Analysis & Pattern Recognition: 77.8%, Visual & Creative Work: 66.5%, Code & Logical Reasoning: 58.6%, Physical & Manual Tasks: 11.0%, Social & Emotional Intelligence: 7.6%.

Key Tasks

What AI can automate for Helpers--Extraction Workers

What stays irreplaceable for Helpers--Extraction Workers

Bottom Line

6% AI exposure — low automation risk (Anthropic, March 2026). BLS projects +5% growth 2024–34. Median $64K/yr (BLS 2024). Defend your human strengths: judgment stays irreplaceable.

Verdict: Defend

Not all Helpers--Extraction Workers face the same AI risk

Your title matters less than your task mix. Two people with the same job can have very different exposure. Lower exposure if you do more client-facing, advisory, or coordination work. Higher exposure if most of your day is repetitive digital output.

What the AI-resilient Helpers--Extraction Workers look like

This role already has strong human elements. The best helpers--extraction workers will strengthen their advantage by deepening interpersonal skills, leveraging physical presence, and becoming the person who checks and improves AI output.

What stays human for Helpers--Extraction Workers

The physical labor and problem-solving in unpredictable extraction environments.

Career pivot tip

Focus on specialized equipment operation and maintenance roles that require human oversight.

What not to panic about

AI automates tasks, not your full professional value. Trust, judgment, responsibility, and context still matter deeply. The people most at risk are usually those who stay static. Using AI early often matters more than fearing it.

Helpers--Extraction Workers salary in 2026

Estimated 2026 salary: $67,500. Current median: $64,900. Growth outlook: +5% through 2033. Total employment: 108,621.

Your 3-move defense plan as a Helpers--Extraction Workers

As AI transforms the Helpers--Extraction Workers profession, developing complementary skills is essential. Focus on areas where human judgment, creativity, and interpersonal skills provide an irreplaceable advantage.

Can AI increase Helpers--Extraction Workers salary?

Current median salary: $64,900. Professionals who adopt AI tools early in this field can see significant productivity gains that translate to higher compensation.

AI tools every Helpers--Extraction Workers should know

What AI changes for Helpers--Extraction Workers

AI Exposure: This helper role faces moderate AI exposure due to high data (78%) and text (75%) requirements. AI-powered monitoring systems, automated equipment diagnostics, and digital task assignment platforms could streamline many documentation and observation tasks currently performed by helpers. However, the physical assistance component and learning complex extraction techniques from skilled workers provide significant resilience.Resilience: The minimal physical demands (11%) and very low social requirements (8%) mean workers cannot rely purely on human-centric tasks for protection. Yet the hands-on learning from experienced craft workers and the variable, site-specific nature of extraction work create meaningful barriers to full automation. Helpers acquire tacit knowledge that's difficult to replicate.Tools & Advice: Familiarize yourself with digital reporting systems, equipment sensors, and automated monitoring dashboards. Focus on developing specialized skills in equipment maintenance, safety protocols, and machinery operation that complement AI systems rather than compete with them. Seek mentorship to accelerate skill acquisition beyond routine tasks.

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