Santa Fe

๐Ÿ“ New MexicoยทPop. 130,638ยท61,400 employedยทRanked #28 of 393 metros
77

High Risk

AI Risk Score

โš ๏ธ

77/100

#28 of 393 ยท +7 vs avg

Workers Vulnerable

๐ŸŽฏ

20,420

33.3% of workforce

Average Wage

๐Ÿ’ฐ

$60K

+$519 vs national

Tech Employment

๐Ÿ’ป

2.3%

National avg: 2.0%

Service Employment

๐Ÿช

38.8%

National avg: 31.3%

WARN Notices (2025)

๐Ÿ“‹

0

Layoff filings

๐Ÿ’ก Santa Fe has an AI risk score of 77/100 with 33.3% of workers in vulnerable roles โ€” led by Retail. Average wages of $60K are above the national metro average. See New Mexico overview โ†’

AI Risk Analysis

The Santa Fe metropolitan area receives an AI displacement risk score of 77 out of 100, placing it at rank #28 among 393 US metros. This is 7 points above the national metro average of 70, reflecting moderately elevated risk. An estimated 20,420 workers โ€” 33.3% of the workforce โ€” hold positions in occupations highly susceptible to automation. This vulnerability rate exceeds the national average of 29.5% by 3.8 percentage points.

The primary driver of risk in Santa Fe is the concentration of employment in Retail, an industry where routine tasks, data processing, and customer interactions are increasingly being handled by AI systems. Among the most at-risk occupations in the area are Retail Salespersons, Secretaries and Administrative Assistants, Except Legal, Medical, and Executive, Fast Food and Counter Workers, and Cashiers โ€” roles where advances in natural language processing, computer vision, and robotic process automation are already reducing demand. The metro's heavy service sector concentration (38.8% vs 31.3% nationally) amplifies vulnerability, as customer-facing and back-office roles are prime targets for AI automation.

Average wages in the metro ($60K) are close to the national average, creating neither a strong pull toward nor away from automation investment. Workers in this metro should consider developing complementary AI skills, exploring transition paths to lower-risk occupations, and leveraging local workforce development resources.

Automation Vulnerability

20,420

workers at risk (33.3%)

0%33.3%33%+

Industry Breakdown

Top at-risk industry: Retail

Tech Sector2.3%

National avg: 2.0%

Service Sector38.8%

National avg: 31.3% โš ๏ธ High concentration โ€” elevated AI risk

โš ๏ธ Retail Trade โ€” Highest Risk Industry

National risk score: 56/100 ยท 26,703,360 employed nationally ยท Projected -2.1% job decline ยท Advanced AI adoption stage

Comparison to National Average

Risk Score

+7

vs 70 national avg

Average Wage

+$519

vs $60K national avg

Vulnerable Workers

+3.8%

vs 29.5% national avg

National Economic Context

Latest national labor market indicators from FRED (Federal Reserve Economic Data)

Unemployment Rate

4.4%

2026-02

Labor Participation

62%

2026-02

Weekly UI Claims

214,000,000

2026-02

Job Openings

6.9M

2026-01

๐Ÿ“Š Methodology

Metro area AI risk scores are calculated using a composite model that weighs multiple factors: occupational automation probability (based on Frey & Osborne methodology and updated GenAI exposure scores), industry concentration risk, local employment mix, wage levels, and historical WARN Act layoff notices.

Scores range from 0 (lowest risk) to 100 (highest risk) and represent relative vulnerability compared to other US metro areas. Individual occupation risk scores within the metro are estimated by applying the metro's employment share to national occupation-level data. Data sources include BLS Occupational Employment and Wage Statistics, Census Bureau population estimates, and state WARN Act filings.