Somewhat Resilient
Last Update: 8/30/2026
AI Resilience Score for Maint. Workers, Machinery:
42.6%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Low
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Low
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forMaintenance Workers, Machinery
$60,850 median salary•4,400 annual openings•SOC Code: 49-9043.00
Maintenance Workers, Machinery are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Machinery maintenance work earns a "Somewhat Resilient" label because AI is genuinely changing how this job works, even though it is not replacing the workers who do it. The paperwork side of the job (logging repairs, tracking parts, analyzing data) is getting automated, and AI tools are now predicting equipment failures 30 to 90 days before they happen, which means your daily routines will look pretty different than they did for workers a decade ago.
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Machinery maintenance work earns a "Somewhat Resilient" label because AI is genuinely changing how this job works, even though it is not replacing the workers who do it. The paperwork side of the job (logging repairs, tracking parts, analyzing data) is getting automated, and AI tools are now predicting equipment failures 30 to 90 days before they happen, which means your daily routines will look pretty different than they did for workers a decade ago.
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Maint. Workers, Machinery
Updated Quarterly
How is AI changing Maint. Workers, Machinery jobs?
If you're thinking about becoming a machinery maintenance worker, here's some good news: AI is showing up in your future workplace mostly as a helpful teammate, not a replacement. According to the third annual MaintainX State of Industrial Maintenance report [1], a majority of teams (58%) are already using AI in their operations, and 75% report measurable ROI in under six months. Workers are using AI for everything from maintenance data analytics and knowledge capture to real-time repair assistance and root cause analysis.
That matches the automation scores for this job — the paperwork-heavy tasks (logging repairs, tracking parts, reading work orders) are the ones getting automated, while the hands-on tasks like dismantling machines or chipping off hardened material still need human hands.
The biggest AI use case is predictive maintenance. According to IIoT World [2], AI systems now use machine learning and sensor data to predict equipment failures 30 to 90 days before they happen, cutting unplanned downtime by 30–50%. But the International Society of Automation's 2025 position paper on Industrial AI [3] stresses that this technology works best when combined with competency development, change management and upskilling — meaning workers who learn the tools become more valuable, not less.
Sources
How fast is AI adoption growing for Maint. Workers, Machinery?
Adoption is moving fast because the money makes sense. AI catches problems early and saves companies from paying $260,000 per hour in downtime costs, and platforms are already commercially available and easy to plug into existing systems.
But adoption also has real limits. The U.S. Bureau of Labor Statistics [4] projects employment for industrial machinery mechanics, machinery maintenance workers, and millwrights to grow 14 percent from 2025 to 2035, much faster than the average for all occupations, with about 51,900 openings projected each year. In other words, there aren't enough workers — so companies are using AI to help the workers they have, not replace them.
The MaintainX report even notes that labor shortages and poor knowledge transfer rank among the top causes of unplanned downtime, and skills gaps remain one of the biggest barriers to improving maintenance programs. On top of that, the World Economic Forum [5] points out that AI-driven change in manufacturing has to be paired with reskilling to actually work.
The bottom line: physical repair skills, teamwork, and safety judgment stay human. If you learn to work with AI dashboards and diagnostic tools, you'll be in high demand for years to come.
Sources
Will AI replace Maint. Workers, Machinery?
Not entirely. We think AI will take over some tasks, but not the whole job.
Machinery maintenance workers score a 42.6% AI Resilience Score, which puts them in "somewhat resilient" territory. That means real change is coming, but not a full replacement. The tasks most at risk are the administrative ones: logging repairs, tracking parts, reading work orders. Those are already being automated. Meanwhile, the physical work of dismantling machines, diagnosing problems in person, and making safety calls on the spot still needs a human.
The biggest shift is predictive maintenance. AI systems now use sensor data to flag equipment failures 30 to 90 days before they happen, cutting unplanned downtime by 30 to 50% [2]. Workers who learn to read those dashboards and act on those alerts become more valuable, not less. The International Society of Automation agrees that this technology works best when paired with worker upskilling [3].
The economic picture is more cautious, though. Employer demand and long-term earning potential both score low on our scorecard, so this is not a field where you can coast. Workers who treat AI tools as part of their skill set, rather than a threat, will be in a much stronger position than those who don't [5].
Sources
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Latest AI news for Maint. Workers, Machinery
These articles highlight how AI is reshaping careers in maintenance and machinery. For instance, the piece on predictive maintenance shows how AI can enhance machinery efficiency, reducing downtime and costs. Additionally, the South Carolina manufacturing report emphasizes that assembly line and maintenance roles will remain in demand, despite AI advancements. This indicates that while AI may change job dynamics, it can also create new opportunities, underscoring the importance of adaptability and continuous learning in building a resilient career in this field.
SC manufacturing economy continues to grow, but AI could tamp down workforce demands
scdailygazette.com • 2/13/2026
Assembly line workers, maintenance and mechanics are projected to be the most in-demand manufacturing jobs in South Carolina study shows.
From Waste Reduction to Predictive Maintenance: AI’s Impact on Machinists
www.thomasnet.com • 12/10/2025
Artificial intelligence is changing the machining industry by boosting precision, lowering costs through predictive maintenance and waste...
Agents, robots, and us: Skill partnerships in the age of AI
www.mckinsey.com • 11/25/2025
Learn how AI is transforming work, focusing on the collaboration between humans, agents, and robots.
Job loss or job growth: The impact of AI and advanced robotics on the CEA workforce
www.greenhousemag.com • 10/14/2025
AI and advanced robotics are reshaping controlled environment agriculture, creating new roles for greenhouse workers while boosting...
Artificial intelligence in the office and the factory: Evidence from administrative software registry data
cepr.org • 9/9/2025
The rapid adoption of AI in the workplace has raised concerns about job loss. This column uses data covering all AI-related commercial...
More Career Info
Career: Maintenance Workers, Machinery
They keep machines running smoothly by checking, fixing, and cleaning them to prevent breakdowns and ensure everything works safely and efficiently.
Parent Careers
Similar Careers
Employment & Wage Data
Median Wage
$60,850
Jobs (2025)
59,700
Growth (2025-35)
-1.9%
Annual Openings
4,400
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Collaborate with other workers to repair or move machines, machine parts, or equipment.
2
Dismantle machines and remove parts for repair, using hand tools, chain falls, jacks, cranes, or hoists.
3
Reassemble machines after the completion of repair or maintenance work.
4
Remove hardened material from machines or machine parts, using abrasives, power and hand tools, jackhammers, sledgehammers, or other equipment.
5
Replace or repair metal, wood, leather, glass, or other lining in machines, or in equipment compartments or containers.
6
Install, replace, or change machine parts and attachments, according to production specifications.
7
Lubricate or apply adhesives or other materials to machines, machine parts, or other equipment according to specified procedures.
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.
