--- title: "Will AI Replace First-Line Supervisors of Construction Trades and Extraction Workers?" description: "BLS rates first-line supervisors of construction trades and extraction workers' exposure to AI as moderate. What that means, which parts of the work AI…" canonical: "https://nuecareer.com/careers/will-ai-replace-first-line-supervisors-of-construction-trades-and-extraction-workers" last-updated: "2026-10-15T08:19:32.066Z" --- # Will AI Replace First-Line Supervisors of Construction Trades and Extraction Workers? (2026) **Short answer:** Unlikely. BLS rates the work's exposure to AI as moderate, below the middle of the pack, and still projects employment to grow faster than average. The Bureau of Labor Statistics places first-line supervisors of construction trades and extraction workers in its moderate AI exposure category, below the middle of the pack: some of the work overlaps with what AI can do, much of it does not. BLS projects employment to change by +5.0% over 2025–2035, against 3.5% for all occupations, with about 67,000 openings a year. | Measure | Value | Source | | --- | --- | --- | | BLS relative AI exposure | Moderate | BLS Employment Projections, AI exposure categories | | NueCareer AI-resilience score | 62/100 | NueCareer analysis of O\*NET 31.0 Database | | Projected employment change | +5.0% | BLS EP 2025–2035 | | Openings a year | 67,000 | BLS EP 2025–2035 | | Median annual wage | $79,920 | BLS OEWS May 2025 | ## Exposure categories | BLS category | Occupations | | --- | --- | | Low | 203 | | Moderate (this job) | 194 | | High | 190 | | Very high | 199 | Exposure means AI could be or has been used to assist with or complete some of the work. BLS says it does not imply job loss, productivity gains, automation probability or wage effects. Method: https://www.bls.gov/emp/publications/ai-exposure-categories.htm ## What holds up - Face-to-face discussions: 5.0/5 (O\*NET work context) - Working outdoors in all weather: 4.4/5 (O\*NET work context) - Inspecting equipment, structures, or materials: 4.1/5 (O\*NET work activity importance) - Establishing and maintaining interpersonal relationships: 3.9/5 (O\*NET work activity importance) ## What AI reaches first - Processing information: 3.7/5 (O\*NET work activity importance) - Email: 4.6/5 (O\*NET work context) - Getting information: 4.1/5 (O\*NET work activity importance) - Scheduling work and activities: 3.9/5 (O\*NET work activity importance) ## O\*NET tasks - Inspect work progress, equipment, or construction sites to verify safety or to ensure that specifications are met. - Assign work to employees, based on material or worker requirements of specific jobs. - Coordinate work activities with other construction project activities. - Supervise, coordinate, or schedule the activities of construction or extractive workers. - Estimate material or worker requirements to complete jobs. - Provide assistance to workers engaged in construction or extraction activities, using hand tools or other equipment. ## Related careers less exposed to AI than first-line supervisors of construction trades and extraction workers - [Rotary Drill Operator, Oil and Gas](https://nuecareer.com/careers/rotary-drill-operator-oil-and-gas): BLS exposure Low, median $67,890 - [Terrazzo Worker and Finisher](https://nuecareer.com/careers/terrazzo-worker-and-finisher): BLS exposure Low, median $76,170 - [Roof Bolter, Mining](https://nuecareer.com/careers/roof-bolter-mining): BLS exposure Low, median $78,540 ## FAQ **Will AI replace first-line supervisors of construction trades and extraction workers?** Unlikely. BLS rates the work's exposure to AI as moderate, below the middle of the pack, and still projects employment to grow faster than average. BLS defines exposure as AI being able to assist with or complete some of the work, and says it does not imply job loss, productivity gains or wage effects. BLS projects employment to change by +5.0% over 2025–2035, against 3.5% for all occupations, with about 67,000 openings a year. **How exposed are first-line supervisors of construction trades and extraction workers to AI?** BLS sorts 786 occupations into four relative categories: low, moderate, high and very high. First-Line Supervisors of Construction Trades and Extraction Workers are in the moderate category, alongside 193 other occupations. The categories combine five public measures of where AI could be or already is used, and they compare occupations with each other rather than giving an absolute risk. **What parts of a first-line supervisor of construction trades and extraction workers's job can AI do?** In O\*NET's description of the work, the parts that overlap most with what AI handles well are processing information, email and getting information. The parts that hold up best are face-to-face discussions, working outdoors in all weather and inspecting equipment, structures, or materials. These come from O\*NET ratings of how important each activity is to the job, read through NueCareer's AI-resilience method. **Is being a first-line supervisor of construction trades and extraction workers a safe career from AI?** On NueCareer's AI-resilience score, built from O\*NET work activities, first-line supervisors of construction trades and extraction workers score 62 out of 100, higher than 88% of the occupations we score. The job pays a median of $79,920 a year (BLS OEWS, May 2025). No job is fully safe from technological change, but the federal exposure category and the projected openings are the two numbers worth weighing. **What careers similar to first-line supervisors of construction trades and extraction workers are less exposed to AI?** Rotary Drill Operator, Oil and Gas (low exposure, $67,890 median), Terrazzo Worker and Finisher (low exposure, $76,170 median), Roof Bolter, Mining (low exposure, $78,540 median). Each is in a lower BLS exposure category than first-line supervisors of construction trades and extraction workers, and most are listed by O\*NET as related to the work. Full profile: https://nuecareer.com/careers/first-line-supervisor-of-construction-trades-and-extraction-workers. --- This bank includes information from the O\*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O\*NET® is a trademark of USDOL/ETA. NueCareer has transformed the data by joining it to BLS wage and projection data and deriving facet, personality-fit and AI-resilience scores. BLS and BEA data are public domain (17 U.S.C. §105). O\*NET content is used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). How these figures are sourced and derived: https://nuecareer.com/careers/methodology