Mostly Resilient
Last Update: 8/30/2026
AI Resilience Score for Construction Trades Helper:
52.5%
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.
High
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.
Limited data sources are available, or existing sources show notable disagreement on the outlook for this occupation.
Contributing sources
AI Resilience Report forHelpers, Construction Trades, All Other
$42,670 median salary•2,300 annual openings•SOC Code: 47-3019.00
Helpers, Construction Trades, All Other are somewhat more resilient to AI impacts than most occupations, according to our analysis of 3 sources.
Construction helpers are labeled "Mostly Resilient" because job sites are messy, unpredictable, and safety-sensitive environments that make it genuinely difficult and expensive for robots to handle the wide variety of tasks a human helper does every day. While some specialized machines are starting to take over narrow, repetitive jobs like tying rebar or marking layouts, the broader "helper" work of fetching materials, cleaning up, and supporting tradespeople still relies heavily on human judgment and adaptability.
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Construction helpers are labeled "Mostly Resilient" because job sites are messy, unpredictable, and safety-sensitive environments that make it genuinely difficult and expensive for robots to handle the wide variety of tasks a human helper does every day. While some specialized machines are starting to take over narrow, repetitive jobs like tying rebar or marking layouts, the broader "helper" work of fetching materials, cleaning up, and supporting tradespeople still relies heavily on human judgment and adaptability.
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Construction Trades Helper
Updated Quarterly
How is AI changing Construction Trades Helper jobs?
If you work as a construction helper — carrying materials, cleaning up, and supporting skilled tradespeople — you might be wondering whether robots are about to take over. The honest answer for 2026 is: not yet, but the tools are getting closer. According to the U.S. Bureau of Labor Statistics, employment of construction laborers and helpers is projected to grow 6 percent from 2025 to 2035, faster than the average for all occupations [1], so demand for human workers is still strong.
Most on-site AI today lives inside specialized machines — think Dusty Robotics' layout bot or TyBot's rebar tier — where a construction robotics report co-published with Hilti Ventures found narrow, high-utilization tasks now show 30–50% material labor savings on the affected scopes [2]. More general "helper" tasks are still mostly human, though McKinsey argues humanoid robots could soon assist with lifting, carrying, and positioning tools, measuring surfaces, or cleaning targeted spaces [3]. Recently, Construction Dive reported Bedrock, Gravis and FieldAI have raised nearly $1 billion combined to push autonomous machines onto real jobsites [4].
Sources
How fast is AI adoption growing for Construction Trades Helper?
Adoption is happening — but slowly, and that's actually good news for helpers. The Associated General Contractors' 2026 outlook found contractors' biggest worries are tariffs, immigration enforcement, and finding qualified workers, not replacing them with robots [5]. Job sites are messy, unpredictable, and safety-sensitive, which makes robots expensive to deploy at scale.
Cost is a real barrier for smaller firms, and commercially available "helper robots" that can safely fetch a bucket or sweep debris are still rare. The likely path is augmentation: robots handling the most repetitive lifting while human helpers move into supervising machines, running data-collection drones, and learning the skilled trades that AI still can't touch. Your judgment, hands, and willingness to learn remain highly valuable.
Sources
Will AI replace Construction Trades Helper?
No. We don't think AI will replace Helpers, Construction Trades, All Other, though we do expect the job to change.
Our AI Resilience Score for this role sits at 52.5%, which puts it in "Mostly Resilient" territory. The reason is straightforward: job sites are messy, unpredictable, and safety-sensitive environments where general-purpose robots still struggle badly. Specialized machines can handle narrow tasks, and one construction robotics report found 30 to 50% labor savings on the specific scopes those machines target [2]. But fetching materials, supporting tradespeople, and adapting to a constantly changing site? That still takes a human.
The economic picture is more mixed. Contractors' top concerns heading into 2026 are tariffs, immigration enforcement, and finding qualified workers, not replacing helpers with robots [5]. That said, our demand and earnings scores for this role are low, so we want to be honest: the job market is not as strong as the human-contribution side of the score suggests.
The smarter path forward is to treat automation as a signal, not a threat. As machines take on the most repetitive lifting and layout tasks [3], helpers who learn to work alongside them, or who use this role as a stepping stone into skilled trades, will be in a much stronger position.
Sources
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Latest AI news for Construction Trades Helper
These articles highlight the evolving role of AI in construction, emphasizing that it won't eliminate jobs but will reshape them. For "Helpers, Construction Trades, All Other," AI can improve efficiency and reduce costs, creating new opportunities. For instance, one article discusses how AI helps companies address labor shortages, making these positions more critical. Another points out that hands-on training is essential to keep up with AI advancements, underscoring the need for workers to adapt. Embracing these changes can lead to a resilient and promising career path in construction.
The jobs likely to be affected in the AI era will be lower
www.facebook.com • 9/20/2026
The jobs likely to be affected in the AI era will be lower- wage ones in fields such as construction, maintenance, transportation, agriculture, ... Read more
Blue-collar workers don't realize that AI is the same threat ...
www.reddit.com • 9/20/2026
When office work is eliminated thanks to AI, there will be a brutal decline in demand for new kitchens, roof repairs, etc. Another part will be ... Read more
How AI is Changing Construction Jobs
www.just-constructionrec.com • 9/20/2026
AI isn't replacing construction jobs, it's reshaping them. In this article, we explore how AI is helping construction companies overcome labor shortages, ...
How Will AI Affect Construction Working Class? What to ...
careerhub.appstate.edu • 9/20/2026
Jul 29, 2025 — AI can help improve efficiency, handle administrative tasks, reduce costs, and create new opportunities for skilled workers in the construction ... Read more
AI Hits the Jobsite: The Workforce Training Gap
constructionexec.com • 9/20/2026
Jun 18, 2026 — A new DEWALT study shows construction pros are ready to embrace AI—but without hands-on training, the workforce risks falling behind just as ... Read more
More Career Info
Career: Helpers, Construction Trades, All Other
They assist skilled workers on construction sites by carrying materials, cleaning up, and doing simple tasks to support building projects.
Parent Careers
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Employment & Wage Data
Median Wage
$42,670
Jobs (2025)
25,200
Growth (2025-35)
-1.0%
Annual Openings
2,300
Education
No formal educational credential
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
