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AI Job Checker

Helpers Extraction Workers

Construction

AI Impact Likelihood

AI impact likelihood: 72% - High Risk
72/100
High Risk

Helpers--Extraction Workers (SOC 47-5081.00) occupy one of the most physically exposed roles in the automation landscape. Approximately 75–80% of their job time involves manual physical tasks — transporting materials, loading and unloading equipment, setting up and adjusting machinery, and clearing sites — all of which are primary targets of already-operational robotic systems. The Frey-Osborne Oxford methodology assigns this occupation a 63% automation probability, and real-world deployment data from Caterpillar, Komatsu, Rio Tinto, and ABB confirms that the theoretical risk has become an operational reality. Autonomous haul trucks, remote-operated drilling platforms, and robotic blasting charge installations are not future concepts — they are live deployments that directly replace tasks listed in this occupation's O*NET profile. The most important framing error to avoid is conflating 'low GenAI/LLM exposure' with 'low automation risk.' Standard AI exposure indices (Anthropic Economic Index, ILO GenAI Index) focus on cognitive and information-processing tasks and correctly identify this role as low-exposure to language models.

This occupation faces high physical-robotics automation risk — not from AI language models — driven by a fully deployed and rapidly scaling autonomous equipment ecosystem (Caterpillar, Komatsu, Rio Tinto, ABB) that directly targets every core task; BLS employment has already declined from ~10,000 to ~7,000 and is projected to continue falling at 1–1.7% annually.

The Verdict

Changes First

Material transport and autonomous haulage tasks are being displaced right now — Caterpillar has 690+ autonomous mining trucks operational and is targeting 2,000+ by 2030, directly eliminating the transport and loading duties that constitute the largest share of this role.

Stays Human

Real-time mechanical troubleshooting in cramped, unstructured, and hazardous underground environments offers the most durable human niche, but even this is being eroded as remote operations centers increasingly supervise autonomous equipment from surface facilities.

Next Move

Exit this occupation within 3–5 years; the skills most transferable are equipment familiarity and safety protocol knowledge, which can bridge into autonomous systems monitoring technician or mine operations control room operator roles — but retraining investment must start immediately.

Most Exposed Tasks

TaskWeightAI LikelihoodContribution
Drive moving equipment to transport materials and parts to excavation sites20%87%17.4
Observe and monitor equipment operation during extraction to detect problems15%82%12.3
Load and unload materials, devices, and machine parts using hand tools15%72%10.8

Contribution = weight × automation likelihood. Full task breakdown in the Essential report.

Key Risk Factors

Autonomous Haulage Fleet Scaling (Caterpillar / Komatsu)

#1

Caterpillar's autonomous haulage fleet surpassed 690 trucks in 2023 and the company has publicly committed to scaling beyond 2,000 units by 2030, with Komatsu's FrontRunner system adding hundreds more across BHP, Fortescue, and Anglo American operations. The technology is no longer in pilot phase — it is the default procurement choice for new greenfield open-pit operations above a certain scale, and is being retrofitted into existing fleets via telematics upgrades. Critically, both Caterpillar and Komatsu are now actively developing lighter-duty autonomous variants for quarry and smaller mine environments, extending the addressable market well beyond the Pilbara mega-mines where the technology was proven.

Autonomous and Remote-Operated Drilling Systems

#2

Rio Tinto's autonomous drilling operation at its Pilbara iron ore mines uses a single remote operator to supervise an entire drill shift from a surface operations center 1,500 km away in Perth, Australia — what previously required a driller plus one or two helpers at each machine. The autonomous drilling CAGR of 74% since 2008 (per Wood Mackenzie) reflects both technology maturation and rapid commercial deployment across iron ore, copper, coal, and gold operations. Epiroc's 6th Sense automation platform and Sandvik's AutoMine Surface Drilling are now the competitive baseline for new drill purchases, with autonomy features bundled rather than optional.

Full analysis with experiments and mitigations available in the Essential report.

Recommended Course

IoT Fundamentals: Connecting Things

Coursera

Builds foundational understanding of IoT sensor networks and data systems being deployed to replace human monitoring roles in mines, enabling transition into oversight and technician roles.

+7 more recommendations in the full report.

Frequently Asked Questions

Will AI replace Helpers Extraction Workers?

At 72/100 High Risk, AI threatens most tasks. Autonomous haulage (87%) and IoT monitoring (82%) are imminent, but hands-on craft assistance at 52% offers more job security near-term.

Which tasks face the highest automation risk for Helpers Extraction Workers?

Driving equipment to transport materials carries 87% automation likelihood within 1-3 years. Monitoring follows at 82% in 2-4 years, driven by IoT sensor and AI anomaly detection deployments.

What is the timeline for AI automation affecting Helpers Extraction Workers?

Transport tasks automate in 1-3 years as Caterpillar targets 2,000+ autonomous trucks by 2030. The occupation already contracted 30-35% from pre-2019 levels, signaling accelerating displacement.

What can Helpers Extraction Workers do to reduce their automation risk?

Equipment repair carries only 44% automation risk with a 6-9 year timeline. Retraining in robotics maintenance or IoT systems aligns with where extraction sites are heading.

Go deeper

Essential Report

Diagnosis

Understand exactly where your risk is and what to do about it in 30 days.

  • +Full task exposure table with AI Can Do / Still Human analysis
  • +All risk factors with experiments and mitigations
  • +Current job mitigations — skill gaps, leverage moves, portfolio projects
  • +1 adjacent role comparison
  • +Full course recommendations with quick-start picks
  • +30-day action plan (week-by-week)
  • +Watchlist signals with severity and timeline

Complete Report

Strategy

Design your next 90 days and your option set. Not more pages — more clarity.

  • +2x2 Automation Map — every task plotted by automation risk vs. differentiation
  • +Strategic cards — best leverage move and biggest trap
  • +3 adjacent roles with task deltas and bridge skills
  • +Learning roadmap — 6-month course sequence tied to risk factors
  • +90-day action plan with monthly milestones
  • +Personalise Your Assessment — 4 dimensions, 72 combinations
  • +If-this-then-that playbooks for career-critical moments

Unlock your full analysis

Choose the depth that's right for you for Helpers Extraction Workers.

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Essential Report

$9.99$6.99

Full task breakdown + 1 adjacent role

  • Task-by-task score breakdown
  • Risk factors with timelines
  • Skill gaps + leverage moves
  • Courses + 30-day action plan
  • Watch signals
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Complete Report

$14.99$10.49

Deep analysis + 3 adjacent roles + strategy

  • Everything in Essential
  • Automation map (likelihood vs. differentiation)
  • Deep evidence per task & risk factor
  • 3 adjacent roles with bridge skills
  • If-this-then-that playbooks
  • 3-month learning roadmap
  • Interactive personalisation matrix

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