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AI-resistant jobs

AI-resistant jobs in manufacturing

8 manufacturing occupations with low LLM exposure (β under 0.25) that BLS projects to add jobs in the industry through 2035, with wages and annual openings.

Data compiled 2026-10-09 · BLS 2025–35 · O*NET 31.0 · AEI May 2026

Industry average exposure (β)

22%

U.S. average across occupations: 30%.

Eloundou et al., Science 2024 · BLS National Employment Matrix 2025–35

Growing, low-exposure occupations

β under 0.25 and projected to add jobs in this industry, ranked by job gains

Jobs and change in this industry: BLS National Employment Matrix 2025–35. Exposure: Eloundou et al., Science 2024. Wage and openings (all industries): BLS Employment Projections 2025–35.
OccupationJobs in industry, 2025Change to 2035Exposure (β)Median wageU.S. openings / yr
Industrial Machinery Mechanics232,500+19.1%14%$64,52044,400
Packaging and Filling Machine Operators and Tenders299,900+4.4%8%$43,22041,400
Miscellaneous Assemblers and Fabricators1.1 million+1.1%9%$44,650138,700
Electrical, Electronic, and Electromechanical Assemblers218,500+5.2%3%$45,85025,900
Food Batchmakers147,700+6.7%15%$42,29023,100
Meat, Poultry, and Fish Cutters and Trimmers115,100+7.0%0%$38,30017,000
Inspectors, Testers, Sorters, Samplers, and Weighers382,700+1.8%18%$48,57066,700
Bakers81,400+7.9%12%$37,16036,500

Low exposure means fewer of an occupation's tasks suit large language models today. It is not a guarantee against other kinds of automation or demand shifts.

Industry context

Where the industry sits overall

+0.6%

Projected industry employment change, 2025–35

12.6 million jobs in 2025 (Manufacturing, NAICS 31-330).

BLS National Employment Matrix 2025–35

14.4%

Jobs in high-exposure occupations

Share of covered 2025 jobs in occupations with β of 0.5 or more. Exposure data cover 96.4% of the industry's jobs.

Eloundou et al., Science 2024 · BLS National Employment Matrix 2025–35

Sources & methodology

Every figure on this page comes from the public datasets below. We do not edit the source values; derived figures are explained here.

  1. Exposure is the human-annotator β score from Eloundou et al.: the share of an occupation's O*NET tasks that a large language model could do at least 50% faster at equal quality, counting tasks that need extra software (E2) at half weight. We label β under 0.25 low, 0.25–0.5 moderate, and 0.5 or more high; these bands are ours, not the authors'.
  2. An occupation qualifies for an industry when its β is under 0.25, the BLS National Employment Matrix projects its employment in that industry to grow from 2025 to 2035, and it has at least 5,000 jobs there in 2025. We rank by projected job gains in the industry and show up to eight.
  3. Wage and annual openings are national BLS figures for the occupation across all industries.
  4. Low exposure means fewer of the occupation's tasks are suited to LLMs today; it does not guarantee job security.
  5. BLS occupations are matched to O*NET-SOC codes with the BLS O*NET-to-NEM crosswalk; where a BLS occupation spans several O*NET occupations, we average their values.

  • Eloundou et al., Science 2024

    Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2024). "GPTs are GPTs: Labor market impact potential of LLMs." Science, 384(6702), 1306–1308. doi:10.1126/science.adj0998. Occupation- and task-level exposure data from the authors' public repository (openai/GPTs-are-GPTs).

    Vintage: Published June 21, 2024; human annotations of O*NET tasks collected 2023. License: Data repository: MIT License. Retrieved 2026-10-09.

  • BLS National Employment Matrix 2025–35

    U.S. Bureau of Labor Statistics, Employment Projections program. 2025–35 National Employment Matrix, industry-occupation employment.

    Vintage: 2025 base year, 2035 projection, released August 27, 2026. License: Public domain (U.S. federal government work). Retrieved 2026-10-09.

  • BLS Employment Projections 2025–35

    U.S. Bureau of Labor Statistics, Employment Projections program. Occupational projections, 2025–35, and worker characteristics, 2025 (Table 1.2); fastest growing occupations (Table 1.3); factors affecting occupational utilization (Table 1.12).

    Vintage: 2025–35 projections, released August 27, 2026. License: Public domain (U.S. federal government work). Retrieved 2026-10-09.

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