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Occupation deep dive / O*NET-SOC 47-2061.00 / Last verified June 2026

Will AI replace construction laborers?

ILO 2025 places construction laborers in the low generative-AI exposure gradient. The role is heavy in physical work that current generative AI cannot perform; the disruption question for this occupation is robotics and prefabrication, which is a separate disruption category.

AI impact on construction jobs in 2025-2026

The direct answer: AI is changing construction work at task level, not eliminating the occupation outright. ILO 2025 places construction laborers in the low generative-AI exposure gradient, 0 of the top 5 O*NET tasks are classified displaceable, and BLS projects employment to grow 6% through 2035.

ILO 2025 exposure

LowFour-band gradient, refined index

Displaceable top tasks

0 of 5Brookings 2024 task rubric

BLS 2025-2035

+6%Faster than average, projected employment change

Will construction laborers jobs grow or shrink by 2035?

The BLS Employment Projections 2025-2035 put construction laborers at +6% projected employment change, classified faster than average. This is the official US decade projection from the National Employment Matrix, distinct from the ILO 2025 AI-exposure gradient above. Source: BLS Employment Projections 2025-2035.

Is this the 2024-2034 or the 2025-2035 projection?

The current BLS projection round is 2025-2035, released on 27 August 2026 (USDL-26-1422). It supersedes the 2024-2034 round. This page shows the 2025-2035 figures for construction laborers. If you have seen a different percentage quoted for this occupation elsewhere, it is most likely the retired 2024-2034 number rather than a contradiction. Across the whole economy the new round projects total employment rising from 170.3 million to 176.2 million jobs, a gain of 5.9 million or 3.5 percent, which is well below the 10.9 percent recorded over 2015-2025. Source: BLS Employment Projections 2025-2035 news release.

The new round also matters for this site specifically. Alongside the 2025-2035 projections, BLS published its own AI exposure categories for the first time, sorting the 831 detailed occupations it projects into Low, Moderate, High and Very High relative exposure. BLS builds the categories from three theoretical sources, which ask whether AI capabilities could match an occupation's tasks, and two observed sources drawn from 2023-2025 Claude and Copilot usage mapped to those tasks. BLS is explicit that the categories are relative rankings against other occupations, not absolute risk levels and not employment forecasts, which is the same caveat this site applies to the ILO gradient above. The two are independent measures and will not always agree. Source: BLS AI exposure categories. Checked 7 September 2026.

personalise this exposure

The ILO national-average exposure for Construction Laborers is 20%. Adjust the four inputs below to see how your specific role characteristics shift the number up or down.

Years in this kind of role

5 years

Your current AI-tool usage

% of work that is routine / repeatable

50%

% of work requiring judgement / relationships

30%

LOWER EXPOSURE

16%

personalised AI exposure score ยท -4% vs ILO baseline (20%)

adjustment breakdown

Years experience adjustment0%
AI tooling (moderate)-4%
Routine work share0%
Judgement / relational work share0%

Heavy AI tooling adoption reduces personalised exposure (you're already augmenting). Routine fractions above 50% raise exposure. Years of experience modestly insulate (institutional knowledge, judgement). Judgement / relational fractions reduce exposure most. The model adjusts the ILO baseline by these factors; treat as a personalised reading, not a precise forecast.

Panel 1 / Exposure

Low exposure

LOWMODERATEHIGHVERY HIGHILO 2025 EXPOSURE GRADIENT

ILO 2025 places construction laborers in the low generative-AI exposure gradient. The role is heavy in physical work that current generative AI cannot perform; the disruption question for this occupation is robotics and prefabrication, which is a separate disruption category.

Source: ILO 2025 refined Generative AI Occupational Exposure Index. ISCO-08 mapping 9313. View methodology.

Panel 2 / Tasks

Top tasks for this role

  • Clean or prepare construction sites to eliminate possible hazards.

    Physical site work is not in scope for generative AI displacement.

  • Read and interpret plans, instructions, or specifications to determine work activities.

    AI assists interpretation; physical execution remains human.

  • Signal equipment operators to facilitate alignment, movement, or adjustment of machinery, equipment, or materials.

    Real-time site signalling is physical and contextually constrained.

  • Lubricate, clean, or repair machinery, equipment, or tools.

    Equipment maintenance is physical and not displaceable at task level.

  • Tend pumps, compressors, or generators to provide power for tools, machinery, or equipment.

    Physical equipment operation is not in scope for generative AI displacement.

Source: O*NET 30.2 task list (CC-BY 4.0); Brookings 2024 task-level rubric. View methodology.

Panel 3 / What is growing

Growth and skills outlook

BLS 2025-2035

Faster than average

+6% projected change.

WEF 2025 / Top growing skills relevant to this role

  • Resilience, flexibility and agility (Self-efficacy)
  • Technological literacy (Technology)
  • Environmental stewardship (Ethics)

Brookings 2024 places construction work in the low-exposure category for generative AI: physical work is augmentation-prone but cannot be displaced at task level.

Source: BLS Employment Projections 2025-2035; WEF Future of Jobs Report 2025. View methodology.

What this occupation does

Construction laborers perform tasks involving physical labour at construction sites. The role spans site preparation, material handling, equipment operation, and assistance to skilled trades across building, road, and infrastructure projects.

The exposure score in context

The ILO 2025 refined Generative AI Occupational Exposure Index places construction laborers in the low exposure gradient. ILO 2025 places construction laborers in the low generative-AI exposure gradient. The role is heavy in physical work that current generative AI cannot perform; the disruption question for this occupation is robotics and prefabrication, which is a separate disruption category.

The mapping uses ISCO-08 code 9313 (BLS-published SOC-to-ISCO crosswalk). The full methodology, including the dominant-match rule for one-to-many crosswalks, is at /methodology/#algorithm.

The top five tasks, classified

The top five O*NET 30.2 tasks for this occupation, each tagged Displaceable / Changing / Growing per the Brookings 2024 task-level rubric. The tag definitions are at /glossary/#displaceable-task, /glossary/#changing-task, and /glossary/#growing-task.

  1. Growing: Clean or prepare construction sites to eliminate possible hazards. Physical site work is not in scope for generative AI displacement.
  2. Changing: Read and interpret plans, instructions, or specifications to determine work activities. AI assists interpretation; physical execution remains human.
  3. Growing: Signal equipment operators to facilitate alignment, movement, or adjustment of machinery, equipment, or materials. Real-time site signalling is physical and contextually constrained.
  4. Growing: Lubricate, clean, or repair machinery, equipment, or tools. Equipment maintenance is physical and not displaceable at task level.
  5. Growing: Tend pumps, compressors, or generators to provide power for tools, machinery, or equipment. Physical equipment operation is not in scope for generative AI displacement.

What is growing in this role

The BLS Employment Projections 2025-2035 outlook for construction laborers is faster than average (+6% projected change). Source: BLS Employment Projections 2025-2035.

Per the WEF Future of Jobs Report 2025, the top three growing skills relevant to this role are: Resilience, flexibility and agility, Technological literacy, Environmental stewardship. The skills are mapped to the occupation's O*NET skills profile.

Brookings 2024 places construction work in the low-exposure category for generative AI: physical work is augmentation-prone but cannot be displaced at task level.

Similar occupations

O*NET 30.2 lists the following related roles. Each links to its own deep dive where one is published.

Industry context

This role sits primarily in the Manufacturing industry. The industry-level rollup includes the cross-occupation exposure profile and the BLS-published industry-level outlook.

How this assessment was made

The full methodology is at /methodology/: ILO 2025 refined index for the gradient, Brookings 2024 rubric for the task tags, BLS 2025-2035 for the growth outlook, WEF 2025 for the skills demand. The pre-empted critiques are at /how-to-argue-with-this/.

AI impact on construction jobs: frequently asked questions

Will AI replace construction laborers in 2025-2026?

Not outright. The ILO 2025 refined Generative AI Occupational Exposure Index places construction laborers in the low exposure gradient, and none of the top 5 O*NET 30.2 tasks are classified fully displaceable: the exposed tasks are changing rather than disappearing. AI is changing construction work at task level in 2025-2026 rather than eliminating the occupation.

Are construction jobs growing or declining?

The US Bureau of Labor Statistics projects employment for construction laborers to grow 6% (faster than average) between 2025 and 2035. Source: BLS Employment Projections 2025-2035, National Employment Matrix.

What skills are growing for construction laborers?

Per the WEF Future of Jobs Report 2025, the top growing skills relevant to this role are Resilience, flexibility and agility, Technological literacy, Environmental stewardship.

Is this the BLS 2024-2034 or 2025-2035 employment outlook for construction laborers?

The current round is 2025-2035, released by BLS on 27 August 2026 (USDL-26-1422), and it supersedes the 2024-2034 round. This page reports the 2025-2035 figures for construction laborers, so a different percentage quoted elsewhere is most likely the retired 2024-2034 number. Economy-wide, the 2025-2035 round projects total employment rising from 170.3 million to 176.2 million jobs, a gain of 5.9 million or 3.5 percent, against 10.9 percent over 2015-2025. Alongside it BLS published its own AI exposure categories for the first time, sorting the 831 detailed occupations it projects into Low, Moderate, High and Very High relative exposure, built from three theoretical sources and two observed sources drawn from 2023-2025 Claude and Copilot usage. BLS states these are relative rankings, not absolute risk levels or employment forecasts. Sources: BLS Employment Projections 2025-2035 news release; BLS AI exposure categories.

From the cluster

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