Editor’s Note: This story originally appeared on (un)Common Logic.
Technological advances have long transformed the way people work, but the current pace of change appears unprecedented.
From the advent of personal computers in the 1970s to the introduction of the World Wide Web in the 1990s, followed by the emergence of smartphones, social media, and cloud computing in the 2000s, recent decades have seen significant shifts in how we work. And now, in the 2020s, the latest transformational force appears to be artificial intelligence (AI).
With the proliferation of AI-related research and new AI-enabled technologies, computers now have the potential to disrupt many industries and occupations previously believed to be insulated from automation.
Due to the distribution of industries and jobs across the country, AI-driven job displacement is likely to impact some areas more than others.
The following is a breakdown of AI-related job displacement risks for major metropolitan statistical areas.
This analysis was conducted by (un)Common Logic, a data-driven digital marketing agency, using data from the U.S. Bureau of Labor Statistics and other sources. For more information, see the methodology section at the end.
1. Tampa-St. Petersburg-Clearwater, FL
- Share of workers at risk of AI-related automation: 11.5{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 161,827
- Share of workers at risk of any computerized automation: 45.0{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 635,836
- Median annual wage: $46,420
2. Miami-Fort Lauderdale-West Palm Beach, FL
- Share of workers at risk of AI-related automation: 10.8{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 294,157
- Share of workers at risk of any computerized automation: 46.3{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 1,260,383
- Median annual wage: $46,510
3. Birmingham-Hoover, AL
- Share of workers at risk of AI-related automation: 10.8{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 54,915
- Share of workers at risk of any computerized automation: 46.6{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 237,476
- Median annual wage: $44,830
4. Jacksonville, FL
- Share of workers at risk of AI-related automation: 10.7{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 79,026
- Share of workers at risk of any computerized automation: 46.0{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 340,637
- Median annual wage: $45,420
5. Buffalo-Cheektowaga-Niagara Falls, NY
- Share of workers at risk of AI-related automation: 10.4{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 54,745
- Share of workers at risk of any computerized automation: 44.1{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 232,621
- Median annual wage: $48,560
6. Austin-Round Rock, TX
- Share of workers at risk of AI-related automation: 10.3{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 126,753
- Share of workers at risk of any computerized automation: 40.2{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 496,209
- Median annual wage: $50,070
7. Kansas City, MO-KS
- Share of workers at risk of AI-related automation: 10.2{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 110,027
- Share of workers at risk of any computerized automation: 45.6{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 491,448
- Median annual wage: $48,040
8. Phoenix-Mesa-Scottsdale, AZ
- Share of workers at risk of AI-related automation: 10.2{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 233,338
- Share of workers at risk of any computerized automation: 44.2{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 1,012,755
- Median annual wage: $48,600
9. Denver-Aurora-Lakewood, CO
- Share of workers at risk of AI-related automation: 10.1{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 161,291
- Share of workers at risk of any computerized automation: 40.4{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 643,137
- Median annual wage: $58,490
10. New York-Newark-Jersey City, NY-NJ-PA
- Share of workers at risk of AI-related automation: 10.1{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 962,697
- Share of workers at risk of any computerized automation: 38.8{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 3,680,763
- Median annual wage: $59,390
11. Baltimore-Columbia-Towson, MD
- Share of workers at risk of AI-related automation: 10.1{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 131,647
- Share of workers at risk of any computerized automation: 39.3{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 513,065
- Median annual wage: $54,140
12. Richmond, VA
- Share of workers at risk of AI-related automation: 9.9{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 64,301
- Share of workers at risk of any computerized automation: 42.7{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 276,743
- Median annual wage: $48,470
13. Nashville-Davidson-Murfreesboro-Franklin, TN
- Share of workers at risk of AI-related automation: 9.7{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 104,407
- Share of workers at risk of any computerized automation: 47.3{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 508,631
- Median annual wage: $46,950
14. Raleigh, NC
- Share of workers at risk of AI-related automation: 9.7{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 68,125
- Share of workers at risk of any computerized automation: 42.6{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 299,004
- Median annual wage: $48,800
15. Orlando-Kissimmee-Sanford, FL
- Share of workers at risk of AI-related automation: 9.7{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of AI-related automation: 132,506
- Share of workers at risk of any computerized automation: 47.8{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760}
- Total workers at risk of any computerized automation: 652,685
- Median annual wage: $43,120
Methodology
Data sources include the U.S. Bureau of Labor Statistics’ Occupational Employment and Wage Statistics (2023), Frey and Osborne’s Probability of Computerization by Occupation (2013) and Felten et al.’s AI Occupational Exposure (2021).
To determine the locations with the most workers at risk of AI-related job displacement, researchers calculated the percentage of workers in occupations that have both high AI exposure and high probabilities of computerization.
For the purpose of this analysis, high AI exposure was defined as being at least one standard deviation above the mean and high probability of computerization was defined as being 70{c87e2df4b343d0515d304e127afe4653a549475791ab451641a18e09bd64e760} or more.
Researchers also calculated the percentage of workers at risk of any computerized automation, which is simply the share of workers in occupations with high probabilities of computerization, regardless of their AI exposure.