Not Very Resilient

Last Update: 8/30/2026

AI Resilience Score for Extraction Workers, Other:

33.9%

Median Score

Meaningful human contribution

Low

Long-term employer demand

Low

Sustained economic opportunity

Med

Our confidence in this score:

Low-medium

Contributing sources

AI Resilience Report forExtraction Workers, All Other

$57,010 median salary•600 annual openings•SOC Code: 47-5099.00

Extraction Workers, All Other are less resilient to AI impacts than most occupations, according to our analysis of 4 sources.

Extraction work is labeled "Not Very Resilient" because AI and automation are replacing some of the most common tasks in the field, like driving haul trucks, monitoring equipment, and scheduling maintenance, which used to require lots of workers on the ground. Companies like Rio Tinto are already running fleets of 130 or more autonomous trucks controlled by a central system, meaning fewer people are needed for those roles.

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How is AI changing Extraction Workers, Other jobs?

Extraction work — pulling oil, gas, and minerals out of the ground — is one of the industries where AI and automation have moved fastest, but mostly to augment workers rather than replace them entirely. In mining, Rio Tinto's AutoHaul long-distance trains have travelled more than 7 million km since their introduction in 2019, and part of its iron-ore operations is a fleet of 130+ autonomous trucks operated by a supervisory system and a central controller, rather than drivers. The company notes that these systems also take truck operators out of harm's way, reducing the risks associated with working around heavy machinery.

In oil and gas, professional groups are pushing similar ideas — more than 900 drilling and well professionals gathered at APDT 2026 in Bali ^[1] to explore how AI and automation are driving safer, smarter drilling. According to a recruiter tracking the sector, digital twins are evolving into systems that can actively support operations, including scheduling maintenance, allocating tasks, and optimising performance, which reduces the need for constant manual intervention. That means today's field workers are shifting toward monitoring dashboards, troubleshooting equipment, and interpreting AI outputs.

Sources

[1]jpt.spe.org

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How fast is AI adoption growing for Extraction Workers, Other?

Adoption is being pulled forward by tough economics. A McKinsey report summarized by Global Mining Review ^[2] found mining productivity decreased by half from 1997 to 2023 while manufacturing more than doubled, giving companies a huge incentive to try AI, robotics, and automation. Labor costs also justify the investment: BLS reports ^[3] that the oil and gas extraction industry had nearly 114,000 jobs in May 2025 and an annual mean wage of $122,890, making it one of the highest paying U.S. industries overall.

But adoption has real limits — remote sites, harsh weather, safety rules, and the need for skilled humans to handle unexpected problems slow things down. The good news for young people: industry recruiters report ^[4] growing demand for hybrid workers who mix hands-on field skills with data literacy, so learning both wrenches and dashboards makes you very hireable.

Sources

[2]globalminingreview.com

[3]bls.gov

[4]orionjobs.com

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Will AI replace Extraction Workers, Other?

In part. We think AI will eventually automate a real share of this work, but the full picture is more complicated than a simple "robots take over" story.

Our 33.9% AI Resilience Score reflects real pressure. Autonomous trucks, AI-driven drilling systems, and digital twins are already reshaping extraction sites, and the economics push companies to keep going. Mining productivity dropped sharply from 1997 to 2023, giving operators a strong incentive to automate wherever they can ^[2]. With oil and gas extraction jobs paying a mean wage of $122,890, labor costs make automation investments easy to justify ^[3]. The honest read: routine, repetitive field tasks are the most exposed, and job openings through 2034 look limited.

What stays human is the judgment call in unpredictable conditions, troubleshooting when equipment behaves unexpectedly, and keeping operations safe when things go sideways. Those skills do not disappear, they migrate. Recruiters in the sector report growing demand for workers who combine hands-on field knowledge with data literacy, people who can read a dashboard and fix what the algorithm flags ^[4]. If you are early in this career, the move is to build that hybrid profile. The field skills you already have are the foundation. Add data fluency on top, and you open doors in energy tech, equipment monitoring, and operations roles that AI needs humans to run.

Sources

[2]globalminingreview.com

[3]bls.gov

[4]orionjobs.com

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How can Extraction Workers, Other prepare for AI?

Learn to read and work with dashboards and digital monitoring tools.

The analysis mentions that today's extraction workers are shifting toward "monitoring dashboards, troubleshooting equipment, and interpreting AI outputs" rather than doing purely physical labor. This skill transfers everywhere. Start now by taking free courses on data visualization tools like Tableau or Google Data Studio, and practice reading real-time data displays. Whether you end up in mining, manufacturing, logistics, or healthcare, the ability to interpret what a system is telling you and respond quickly is one of the most in-demand skills across every industry being touched by AI.

Build the "hybrid worker" profile that industry recruiters are already asking for.

Recruiters tracked in the analysis (orionjobs.com) report growing demand for workers who combine hands-on field skills with data literacy, describing it as knowing both "wrenches and dashboards." You can start building this profile now by pairing any technical or vocational training you take (mechanics, electrical work, equipment operation) with a free online course in basic data analysis or Python. This combination makes you valuable not just in extraction, but in construction, energy, transportation, and advanced manufacturing, all of which are facing the same automation pressures.

Study how autonomous systems work, using real examples from the analysis as your starting point.

Rio Tinto's AutoHaul trains and fleet of 130 or more autonomous trucks are not science fiction. They are operating right now, and understanding how systems like these are supervised and managed is genuinely useful knowledge. Look up how autonomous vehicle supervisory systems work, explore free robotics and automation courses on platforms like Coursera or edX, and follow industry news from sources like the Society of Petroleum Engineers (jpt.spe.org). Workers who understand autonomous systems can transition into roles overseeing them, maintaining them, or improving them across many industries, not just mining.

Develop safety and risk management skills, because AI still needs humans when things go wrong.

The analysis specifically notes that remote sites, harsh weather, and unexpected problems slow down AI adoption, and that autonomous trucks were partly introduced to take workers "out of harm's way." This tells you something important: safety expertise is a durable, transferable skill that AI cannot fully replace. Take a first aid or workplace safety certification course, explore OSHA training programs (many are free online), and learn about risk assessment. Safety professionals are needed in extraction, construction, energy, and dozens of other fields, and this knowledge makes you a stronger candidate in any environment where physical or operational risk exists.

Follow the economics driving AI adoption so you can spot the next wave before it arrives.

The McKinsey report cited in the analysis found that mining productivity dropped by half from 1997 to 2023 while manufacturing more than doubled, and that gap is exactly what is pulling AI investment forward so fast. Learning to read industry trends like this gives you a career superpower: the ability to see disruption coming and move toward opportunity rather than away from it. Practice by reading free summaries from sources like McKinsey, the Bureau of Labor Statistics (bls.gov), and trade publications like Global Mining Review. Students who understand why industries adopt AI (not just how) can navigate transitions more confidently and position themselves for roles in technology consulting, policy, workforce training, and beyond.

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Latest AI news for Extraction Workers, Other

The recommended articles highlight the evolving role of AI in the extraction industry, emphasizing both challenges and opportunities. For instance, "Will AI Replace Helpers--Extraction Workers?" discusses how AI can assist roles like earth drillers, potentially increasing efficiency. Meanwhile, "Climate action and AI can create more and better jobs" suggests that the transition to a carbon-neutral economy may generate new roles for extraction workers. These insights underscore the importance of adaptability and embracing AI technologies to ensure resilience in a changing job landscape.

Will AI Replace Helpers--Extraction Workers?

aitakeovertracker.com • 9/20/2026

How AI Impacts Each Task ; Provide assistance to extraction craft workers, such as earth drillers and derrick operators. · 11.0% · 12% ; Observe and monitor ... Read more

Ghost Workers in the AI Machine:

cwa-union.org • 9/20/2026

Fifty-two percent of surveyed workers believe they are training AI to replace other workers' jobs, and 36% believe they are training AI to replace their own ... Read more