Simon Janssen
Simon Janssen· CTO at HappyNurse · US AI Exposure Map 2026
Construction

First-Line Supervisors of Construction Trades Workers and AI

Moderate exposureAI score 4/10 · Construction
4out of 10
JPE Score
Median salary
$80K
OEWS May 2025
Forecast 2030
-5% to +10%
Employment
913K
BLS Employment Projections 2025
Employment growth 2021-2025 (OEWS)
+22%
Forecast trend 2025-2030
stable
Education
High school
Sector
Construction

Exposure scores

JPE (Practical Exposure)4/10 — Moderate exposure
Felten AIOE (academic reference)6.1/10
Employment growth 2021-2025 (OEWS)+22%

AI exposure explained

What does an AI score of 4/10 mean?

Interpretation

Moderate exposure — Parts of this work can be assisted by AI. The role will evolve but not disappear.

For First-Line Supervisors of Construction Trades Workers, AI exposure is moderate: some tasks will be assisted or automated, but the occupation as a whole is expected to evolve rather than disappear. Staying current with AI tools in the field is the key adaptation.


Forecast 2030

What changes for First-Line Supervisors of Construction Trades Workers?

Expected employment change, 2025 to 2030
-5% to +10%
Midpoint +2% · Stable: invest in AI skills
BaseBLS projection, AI not named by BLS+2%
Base + AIJPE 4/10: 0%+2%
Base + AI + roboticsno robotics effect before 2030+2%
Rows add up: the bottom row is the forecast.

The forecast starts from the national projection per occupation and adds AI and robotics as separate layers. The band of -5% to +10% matters more than the midpoint.

BLS AI exposure category: Moderate (context next to the JPE score, not used in the forecast)

Sources: base BLS Employment Projections 2025-35 · jobs: BLS Employment Projections, 2025 (incl. self-employed) · growth 2021-2025: OEWS May 2021 to May 2025 · salary: OEWS May 2025. BLS already builds AI and automation effects into its projection for some occupations; where it does, no separate layer is added on top.

Read the methodology →


Sector context

Construction and AI

First-Line Supervisors of Construction Trades Workers belongs to the Construction sector. This sector has an education level index of 1/4, indicating lower formal education requirements. Occupations in Construction with high AI exposure tend to remain relatively stable as the work relies primarily on physical, interpersonal, or contextual skills.


AI tools

Which AI tools are already making an impact?

Procore AIChatGPT

Career outlook

AI as an asset

This occupation is not directly threatened by AI. The smartest move is to learn the AI tools that strengthen your work: not because you have to, but because it makes you more productive and valuable.


Personal development

Personal development plan

Based on your sector (Construction) and AI exposure level, here are three concrete steps to future-proof your career.

Use AI for project estimation and bidding

AI-based estimates reduce cost overruns by 20-30%

→ Procore, Autodesk Construction Cloud
Adopt AI safety monitoring on-site

Computer vision detects hazards before incidents happen

→ Smartvid.io, OpenSpace
Integrate AI with BIM models

AI catches design conflicts and optimizes material use early

→ Autodesk Construction Cloud, Revit

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Similar occupations on the map

Construction Laborers
AI 2/10·+4% 2030
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International

This occupation in other countries

🇫🇷Conducteurs de travaux
AI 5/10Site Managers

About this analysis

AI scores are LLM-estimated using the same methodology as the Dutch AI Exposure Map, making scores directly comparable across countries. The Felten AIOE score is shown as an academic reference. Employment from BLS Employment Projections 2025-35 (2025, including self-employed); growth 2021-2025 and salaries from BLS OEWS May 2021 and May 2025 (an estimate where OEWS has no figure). The 2030 forecast (JPE-prognose v3) starts from the BLS Employment Projections and adds separate AI and robotics layers only where BLS does not already include those effects. These are modelled scenarios, not predictions. A high AI score does not automatically mean job loss. All data CC BY 4.0.

Full methodology, sources and download →


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