Watch AI sweep the map.

393 US METROS · 6 EXPOSURE INDICES · BLS OEWS May 2025 · scenario, not forecast

POSITIONS ELIMINATED

OF JOBS · MODELED, NOT A FORECAST

Fig. 1. Each area's color is its standing that year — green is faring well, ember is worst hit. Press play to watch the loss spread; hover for the local toll; click through for the full breakdown.

MOST EXPOSED

#	Metro
1	Boulder, CO	57.3
2	San Jose, CA	56.8
3	Lexington Park, MD	56.5
4	Trenton, NJ	56.3
5	Durham, NC	56.0
6	Washington, DC	55.5
7	Tallahassee, FL	55.1
8	Olympia, WA	55.0
9	Ithaca, NY	54.9
10	Austin, TX	54.6

LEAST EXPOSED

#	Metro
393	Salinas, CA	39.8
392	Visalia, CA	40.1
391	Hanford, CA	41.5
390	Yakima, WA	42.3
389	Bakersfield, CA	42.4
388	Albany, OR	42.6
387	Merced, CA	42.7
386	Stockton, CA	42.9
385	Elkhart, IN	42.9
384	Vineland, NJ	43.0

Abstract. We compute metro-level exposure to AI-driven job displacement by weighting six published occupation-level exposure indices by each metro's occupational employment mix, reported with the full range across methodologies — never a bare point estimate. The map's timeline is a clearly-labeled scenario layer with every assumption adjustable. Methods · Data & validation.