Organizer brief
Fresno, CA
Fresno, CA metro area. Prepared Nov 5, 2026.
Cognitive exposure
44US average 50. Bottom fifth of metros for cognitive exposure.
18% of workers in high-exposure jobs (US about 25%).
Physical exposure
52US average 50. Second-highest fifth of metros for physical exposure.
30% of workers in high-exposure jobs (US about 25%).
47% of 476,890 workers are in jobs high on either measure (US about 49%), earning $12.8 billion a year, 43% of local pay in the jobs counted.
Farm work is undercounted. Federal wage data (OEWS) leaves out self-employed workers, private household workers, and most farms that hire directly, so farm-heavy metros are undercounted.
Most exposed local jobs: Farmworkers and Laborers, Crop, Nursery, and Greenhouse (28,570, physical); Home Health and Personal Care Aides (33,580, cognitive); Fast Food and Counter Workers (12,330, physical); Laborers and Freight, Stock, and Material Movers, Hand (8,050, physical); Heavy and Tractor-Trailer Truck Drivers (8,170, physical).
Fresno, CA: what AI and automation could touch
The Fresno, CA metro has 476,890 jobs in federal wage data. On generative AI (cognitive) exposure it scores 44, 6 points below the US average and in the bottom fifth of US metros. On robotics and autonomy (physical) exposure it scores 52, 2 points above the US average and in the middle fifth of US metros.
18% of local workers hold jobs in the most cognitively exposed quarter of US work (US: 25%), and 30% in the most physically exposed quarter (US: 25%).
Where the exposure sits
- Farmworkers and Laborers, Crop, Nursery, and Greenhouse: 28,570 workers, mainly physical, 35.1 times as common here as nationally.
- Home Health and Personal Care Aides: 33,580 workers, mainly cognitive, 2.5 times as common here as nationally.
- Fast Food and Counter Workers: 12,330 workers, mainly physical, about as common here as nationally.
- Laborers and Freight, Stock, and Material Movers, Hand: 8,050 workers, mainly physical, about as common here as nationally.
- Heavy and Tractor-Trailer Truck Drivers: 8,170 workers, mainly physical, about as common here as nationally.
- Stockers and Order Fillers: 8,850 workers, mainly physical, about as common here as nationally.
Data centers on the table
- Existing Fresno data centers are small internet-service facilities (operating): ABC30 reported in February 2026 that Fresno has three data centers, described as small and focused on internet services rather than AI, one of them in a north Fresno industrial park. A Bloomberg analysis cited by Fresnoland in 2025 found no AI data centers in the San Joaquin Valley.
- 100 MW AI-optimized data center at Naval Air Station Lemoore (adjacent, Kings County) (announced): In September 2025 Ameresco and the U.S. Navy announced a 100 MW AI-optimized data center on land Ameresco leases from the Department of Defense at NAS Lemoore, with CyrusOne delivering the data center infrastructure and Ameresco building co-located on-site generation as a microgrid.
- Global Stack edge computing proposal at Tulare County Fairgrounds tabled (adjacent, Tulare County) (paused): Global Stack proposed edge computing infrastructure on the Tulare County Fairgrounds. On July 21, 2026 the fair board tabled the rental agreement after public opposition over whether the project is a data center.
Questions for one-on-ones
- Where has AI or new automation already shown up in your work or your family's work?
- Who decided how it was used, and was anyone on the floor asked first?
- What would you want a say in before your employer, school or city adopts more of it?
- If a data center is proposed here, what would you want to know about power, water, jobs and tax breaks?
Read this before quoting the numbers
Exposure means AI or automation could touch a large share of the tasks in a job. It does not predict layoffs. Whether exposed work gets augmented or automated depends on employers, policy, bargaining and community choices. Federal wage data leaves out self-employed workers, private household workers and most farms that hire directly, so farm-heavy metros are undercounted.
Sources
- BLS Occupational Employment and Wage Statistics (OEWS), metropolitan areas, May 2025
- BLS Occupational Employment and Wage Statistics, national estimates, May 2025 (released 2026)
- Eloundou, Manning, Mishkin, Rock (2023), "GPTs are GPTs", occupation-level exposure, 2023 paper (Science 2024); repo commit dated 2025-10-04
- Felten, Raj, Seamans (2021), AI Occupational Exposure (AIOE), Data Appendix A, 2021 (Strategic Management Journal 42(12)); repo commit dated 2024-06-03
- BLS SOC 2010 to SOC 2018 crosswalk, November 2017
- O*NET Occupational Listings (taxonomy crosswalks, incl. O*NET-SOC 2010 to 2019), O*NET-SOC 2019 taxonomy (file dated 2019-12-04)
- O*NET 31.0 Database, Work Activities, O*NET 31.0
- O*NET 31.0 Database, Work Context, O*NET 31.0
- Webb (2020), "The Impact of Artificial Intelligence on the Labor Market", raw occupation exposure scores (final_df_out.dta), Data page "Version 0.1" raw scores (964 O*NET-SOC 2010 occupations, O*NET 22.0); paper working draft January 2020
- Webb (2020), exposure percentiles by occ1990dd, v0.2 (exposure_by_occ1990dd_lswt2010.csv), Data page "Version 0.2"
- Webb (2020), O*NET-SOC to occ1990dd crosswalk (onet_to_occ1990dd.dta), Data page "Version 0.1" crosswalks (Dorn occ1990dd as augmented by Deming)
- Anthropic Economic Index, release 2026-06-26 (Claude.ai, global, soc_occupation), Claude.ai conversations, April and May 2026 (release 2026-06-26)
Written by: template. Every number comes from the computed profile, not from the writer.