Share and intensity of work current AI systems can materially affect.
SOC 47-1011
First-Line Supervisors of Construction Trades and Extraction Workers AI displacement risk
AI scheduling, photo documentation, and progress-tracking tools now automate much of a foreman's information work. Crew leadership, safety enforcement, subcontractor coordination, and split-second site judgment keep field supervision human.
Likely potential for exposed tasks to move to software after workflow integration.
This is the natural near move for the whole trades cluster: the tools change what a supervisor tracks, not whether a site needs one. Supervisors who master construction software run larger, tighter jobs than those who avoid it.
Distribution
Where First-Line Supervisors of Construction Trades and Extraction Workers sits across 620 tracked roles
Displacement pressure 22 — higher than 29% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
30 O*NET task statements matched to SOC 47-1011. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $79,920 (May 2025, US national). The latest BLS row matched SOC 47-1011.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify First-Line Supervisors of Construction Trades and Extraction Workers
SOC 47-1011 places this role in the paper's all-other occupation group. These group-level outcomes do not change the 22/100 role score and are not an occupation forecast.
+1.1% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +1.6% GDP and 3.9% unemployment.
+5.9% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +8.3% GDP and 4.6% unemployment.
+33.6% group wage
Employment rises and unemployment falls for the all-other group, but the paper does not publish a separate group rate.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for First-Line Supervisors of Construction Trades and Extraction Workers
The current evidence import matched 30 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks30
SOC47-1011
- Core task / ID 20291
Inspect work progress, equipment, or construction sites to verify safety or to ensure that specifications are met.
- Core task / ID 11424
Read specifications, such as blueprints, to determine construction requirements or to plan procedures.
- Core task / ID 11426
Supervise, coordinate, or schedule the activities of construction or extractive workers.
- Core task / ID 11432
Assign work to employees, based on material or worker requirements of specific jobs.
- Core task / ID 11428
Coordinate work activities with other construction project activities.
- Core task / ID 11425
Estimate material or worker requirements to complete jobs.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Supervise and schedule construction crews
Exposure 28, automation 11%, augmentation 50%.
O*NET evidence: Supervise, coordinate, or schedule the activities of construction or extractive workers. (ID 11426)
Inspect work for safety and specifications
Exposure 30, automation 12%, augmentation 52%.
O*NET evidence: Inspect work progress, equipment, or construction sites to verify safety or to ensure t... (ID 20291)
Read blueprints and plan procedures
Exposure 44, automation 20%, augmentation 64%.
O*NET evidence: Read specifications, such as blueprints, to determine construction requirements or to p... (ID 11424)
Record production and personnel data
Exposure 56, automation 31%, augmentation 64%.
O*NET evidence: Record information, such as personnel, production, or operational data on specified for... (ID 11431)
TaskExposureAutomationAugmentation
Supervise and schedule construction crews2811%50%
Inspect work for safety and specifications3012%52%
Read blueprints and plan procedures4420%64%
Record production and personnel data5631%64%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
LowProject Superintendent
Training horizon: 2-5 months. Skill overlap 80. Wage preservation signal 122.
- Own full-site coordination
- Manage subcontractor schedules
- Run safety programs
credentialed transition
LowConstruction Project Manager
Training horizon: 6-12 months. Skill overlap 66. Wage preservation signal 136.
- Learn project budgeting
- Study construction management coursework
- Manage client relationships
Comparison guides
Compare the next move before you commit
2-5 months
First-Line Supervisors of Construction Trades and Extraction Workers to Project Superintendent
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from First-Line Supervisors of Construction Trades and Extraction Workers into Project Superintendent.
6-12 months
First-Line Supervisors of Construction Trades and Extraction Workers to Construction Project Manager
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from First-Line Supervisors of Construction Trades and Extraction Workers into Construction Project Manager.
What the AI risk score means for First-Line Supervisors of Construction Trades and Extraction Workers
The displacement pressure score for First-Line Supervisors of Construction Trades and Extraction Workers is 22. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Record production and personnel data carries 31% automation pressure, while Read blueprints and plan procedures carries 64% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $79,920 (May 2025, US national). Employment context: Field leadership role atop the entire construction trades cluster. Typical education: Trade experience; degree increasingly preferred.
Wage vulnerability is 32, while transition feasibility is 72. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Low displacement pressure
- Field leadership is irreplaceable
- Software fluency widens the gap
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For First-Line Supervisors of Construction Trades and Extraction Workers, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Crew leadership
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Safety enforcement
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Blueprint reading
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Construction software
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Project Superintendent, such as own full-site coordination.
- By 90 days, compare internal openings and external postings for Project Superintendent or Construction Project Manager and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and First-Line Supervisors of Construction Trades and Extraction Workers
Will AI replace First-Line Supervisors of Construction Trades and Extraction Workers?
AI scheduling, photo documentation, and progress-tracking tools now automate much of a foreman's information work. Crew leadership, safety enforcement, subcontractor coordination, and split-second site judgment keep field supervision human. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of First-Line Supervisors of Construction Trades and Extraction Workers work are most exposed to AI?
Record production and personnel data and Read blueprints and plan procedures show the strongest automation pressure in this model. Read blueprints and plan procedures and Record production and personnel data are better treated as AI-augmented work.
What should First-Line Supervisors of Construction Trades and Extraction Workers learn next?
Start with Crew leadership, Safety enforcement, Blueprint reading. The most practical adjacent paths in this model are Project Superintendent and Construction Project Manager.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
OECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketMcKinsey Global Institute / 26 July 2023Generative AI and the Future of Work in AmericaO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics