First-line supervisors of construction trades and extraction workers

SOC 47-1011 · 47-0000 · Score reference month August 2026

Directly supervise and coordinate activities of construction or extraction workers.

In short

The national Job Market Health score is in the Balanced band for August 2026.

Job Market Health score

55/ 100
Balanced

Stable · +1

Confidence
High
Restated score
55
Methodology
v1.0
Geography
US
  • At least 90% of required inputs and occupation-industry mapping are covered.

Job Market Health scores are derived indicators based on published data, informational only, not a forecast or guarantee.

$79,920Median annual wageOEWS May 2025
67,000Projected annual openingsBLS Employment Projections 2025-2035
+5.0%Projected growth2025–2035
812,210Total employmentOEWS May 2025

Latest interpretation

What stands out for first-line supervisors of construction trades and extraction workers

The clearest signals from the latest validated score, outlook and metro data.

Occupation fundamentals is the strongest component

Occupation fundamentals scores 73/100, compared with 43/100 for current demand, a 30-point difference.

JobMarketHealth score components

Published long-term outlook

BLS projects 67,000 average annual openings and +5.0% employment growth from 2025 to 2035. Projected openings are a modeled annual average, not vacancies open today.

BLS Employment Projections

Largest published metro market

New York-Newark-Jersey City, NY-NJ has the largest published metro employment count for first-line supervisors of construction trades and extraction workers, at 28,220 jobs. The next-largest published metro is Houston-Pasadena-The Woodlands, TX with 24,570 jobs. This measures employment scale, not market quality.

BLS OEWS

Local market context

QCEW industry conditions for this occupation’s employment mix

Choose a state to see how the industries that employ this occupation are performing locally.

Choose a state above to explore its available industry context.

How to read this section

QCEW measures employment and wages by industry, not by occupation. We weight those industry conditions using the published industry mix for this occupation. These figures describe the industries that employ this occupation; they are not direct counts of people working in the occupation or jobs currently open.

Source: BLS QCEW. This section is not part of the national 0 to 100 Job Market Health score. See the methodology.

Compare states for first-line supervisors of construction trades and extraction workersSide-by-side published industry conditions for two or three states. There is no state-level health score; the 0 to 100 score is national.

How to read this page

The score is a national composite from 0 to 100 that weights near term hiring demand at 50 percent, the occupation's own employment fundamentals at 30 percent, and long-term outlook at 20 percent. Wages and occupation profile details are context shown alongside it, not score inputs. See the full methodology.

Median annual wage and metro employment come from BLS OEWS, which is annual. Projected annual openings and projected growth come from BLS Employment Projections and describe the published projection horizon, so they are not a count of jobs open today. Values shown as not published are suppressed by the source rather than filled in here.

Job Market Health trend

Published composite score · 0–100 · by reference month

Latest published values
  • Aug 2655 / 100
View values: Job Market Health history
Job Market Health history
Reference monthScore / 100
Jan 2549
Feb 2549
Mar 2551
Apr 2551
May 2550
Jun 2549
Jul 2550
Aug 2549
Sep 2549
Oct 2546
Nov 2549
Dec 2551
Jan 2654
Feb 2652
Mar 2652
Apr 2651
May 2653
Jun 2654
Jul 2654
Aug 2655

Score components

The three published inputs behind the composite · each 0–100

Current demand43 / 100
Occupation fundamentals73 / 100
Long-term outlook56 / 100

Largest metro markets by employment

OEWS employment count, where the jobs are, not a quality ranking

OEWS May 2025. These occupation counts describe the survey reference period.

Linked metro names open overall job-market profiles.

Compare cities for this career →

Employment · number of jobs

  • New York-Newark-Jersey City, NY-NJ28,220
  • Houston-Pasadena-The Woodlands, TX24,570
  • Dallas-Fort Worth-Arlington, TX21,530
  • Los Angeles-Long Beach-Anaheim, CA19,690
  • Atlanta-Sandy Springs-Roswell, GA16,920
  • Phoenix-Mesa-Chandler, AZ16,770
  • Miami-Fort Lauderdale-West Palm Beach, FL16,720
  • Washington-Arlington-Alexandria, DC-VA-MD-WV14,660
  • Chicago-Naperville-Elgin, IL-IN13,420
  • Boston-Cambridge-Newton, MA-NH13,110
Largest metro markets by employment
Metro areaEmploymentJobs per 1,000Median annual wage
New York-Newark-Jersey City, NY-NJ28,2202.97$103,990
Houston-Pasadena-The Woodlands, TX24,5707.47$76,020
Dallas-Fort Worth-Arlington, TX21,5305.32$76,230
Los Angeles-Long Beach-Anaheim, CA19,6903.14$97,600
Atlanta-Sandy Springs-Roswell, GA16,9205.85$80,500
Phoenix-Mesa-Chandler, AZ16,7707.06$79,840
Miami-Fort Lauderdale-West Palm Beach, FL16,7205.93$77,530
Washington-Arlington-Alexandria, DC-VA-MD-WV14,6604.67$83,540
Chicago-Naperville-Elgin, IL-IN13,4202.97$111,260
Boston-Cambridge-Newton, MA-NH13,1104.85$99,890

Education & training

Typical entry requirements · BLS Employment Projections 2025-2035

Typical education
High school diploma or equivalent
Work experience
5 years or more
On-the-job training
None
Projected employment
959,400 jobs

Top skills

Occupation profile · O*NET 31.0 Database

  • Coordination
  • Active Listening
  • Speaking
  • Critical Thinking
  • Management of Personnel Resources
  • Monitoring
  • Reading Comprehension
  • Time Management
  • Judgment and Decision Making
  • Complex Problem Solving

Also known as: Coal Mine Production Foreman, Construction Foreman, Construction Supervisor, Electrical Supervisor, Field Operations Supervisor, Field Supervisor

AI & this occupation

How AI relates to First-line supervisors of construction trades and extraction workers work

Across 4 research exposure measures, First-line supervisors of construction trades and extraction workers is in the middle technical AI exposure band based on the mean of the available source-specific percentile ranks. Exposure describes how much of the work the studied AI capabilities could technically assist with; it is not a forecast of job loss.

Observed use of Claude for this occupation's tasks is in the middle third of occupations in the Anthropic Economic Index, a dated observed task-exposure benchmark, not conversation share or the share of workers using AI. Its observation window is not recorded in this saved release.

JobMarketHealth has not measured an AI effect on this occupation's employment or wages, and these figures do not enter its scores; there is no clear evidence of displacement in the data shown here.

Technical AI exposureMiddle exposureMean of 4 available source-specific percentile ranks (4 measures checked); fixed exposure bands, not a national rank of the composite
Dated Claude task exposureMiddle thirdObserved task-exposure benchmark 0.030; observation window not recorded
Business AI use (BTOS Core)24.6%U.S. businesses using AI, two weeks ending 2026-10-04; all industries, not this occupation
Historical task mix (2025)Not enough tasksFewer than 3 observed tasks
Measured labor-market effectNot estimatedJobMarketHealth does not attribute employment or wage changes to AI

Exposure measures (kept separate)

  • GPTs are GPTs exposure (β, GPT-4 rated): 0.40 of 1, national percentile 59 (middle third)
  • Microsoft AI applicability: 0.11 of 1, national percentile 37 (middle third)
  • AIOE (Felten, Raj & Seamans): -0.31 (standardized), national percentile 43 (middle third)
  • OECD AI Capability Gap (lower gap = higher potential exposure): gap 5.3 of 23, national percentile 23 (lower third)
OECD capability gap by domain

As published by the OECD: the gap between what the occupation demands (0-5) and current AI capability in each domain. A lower gap means AI is closer to the requirement (higher potential exposure); 0 means AI already meets it or the domain is not relevant.

  • Language: gap 0.05 (demand 3.05 of 5)
  • Social interaction: gap 1.85 (demand 3.85 of 5)
  • Problem solving: gap 1.95 (demand 3.95 of 5)
  • Creativity: gap 0.00 (demand 2.00 of 5)
  • Metacognition & critical thinking: gap 1.75 (demand 3.75 of 5)
  • Knowledge, learning & memory: gap 0.75 (demand 3.75 of 5)
  • Vision: gap 0.70 (demand 3.70 of 5)
  • Manipulation: gap 1.00 (demand 3.00 of 5)
  • Robotic intelligence: gap 1.60 (demand 3.60 of 5)

National context: what businesses used generative AI for

From the Census 2025-26 BTOS AI Supplement (all industries; businesses whose employees used generative AI). Census did not measure First-line supervisors of construction trades and extraction workers specifically.

  • Writing or editing documents, emails, or communications: 85.4%
  • Searching for information or technical help: 49.9%
  • Interpreting, analyzing, translating, or summarizing documents: 44.6%
  • Information processing, paperwork, or filing: 34.7%

Exposure and observed usage are separate measures and neither equals job loss. Census BTOS figures are business-level surveys and are not occupation-specific. Sources: GPTs are GPTs occupation exposure; Microsoft Working with AI: AI applicability; AI Occupational Exposure (AIOE); OECD AI Exposure Measure (AI Capability Gap); Anthropic Economic Index; Census BTOS Core AI Use; Census BTOS AI Supplement 2025-26. These figures do not affect Job Market Health scores. Explore AI & Jobs · How we use AI data.

Sources and methodology

The datasets behind the figures on this page

Job Market Health score
Score for reference month August 2026 · methodology v1.0 · MethodologyScore last recalculated Oct 2, 2026 · First published Sep 29, 2026
BLS Occupational Employment and Wage Statistics
Employment, wages and largest metros · OEWS May 2025 · publisher release May 15, 2026 · About this sourceRetrieved Sep 17, 2026
BLS Employment Projections
Projected growth, openings, education and training · BLS Employment Projections 2025-2035 · publisher release Aug 27, 2026 · About this sourceRetrieved Sep 17, 2026
O*NET
Skills, alternate titles and related occupations · O*NET 31.0 Database · publisher release date not verified · About this sourceRetrieved Oct 19, 2026

Values marked “Not published” are suppressed or not published by the source. We leave them blank rather than estimating them. Pipeline status for every source is on Data Status.

Evidence record

JobMarketHealth derived indicator; not a government statistic. The composite score is national and occupation level.

Occupation
First-line supervisors of construction trades and extraction workers
SOC code
47-1011
Geography
United States
Reference month
August 2026
Published Job Market Health score
55 / 100
Restated score
55 / 100
Band
Balanced
Current Demand component
43 / 10050% weight
Occupation Fundamentals component
73 / 10030% weight
Long-Term Outlook component
56 / 10020% weight
Confidence
HighAt least 90% of required inputs and occupation-industry mapping are covered.
Methodology version
v1.0
Source vintage: Annual
EP-2025-2035|CPS-25b-2025|OEWS-2020-2025
Source vintage: Monthly calculated at
2026-10-02T15:32:39.142Z
First published at
Sep 29, 2026
Recalculated at
Oct 2, 2026
Canonical record URL
https://jobmarkethealth.com/occupations/first-line-supervisors-of-construction-trades-and-extraction-workers#evidence-record
Derived by
JobMarketHealth

Keep going

Learn how to judge a market from these numbers in how to tell if a job market is healthy, or why projected growth and annual openings often disagree in projected growth vs projected annual openings. Coverage, revisions and limits are explained on about the data.

The datasets behind these figures, and what each one can and cannot show, are set out on data sources.