Metro Area
AI Job Risk in San Juan-Carolina-Caguas, PR
San Juan-Carolina-Caguas, PR scores 53.5/100 for AI job risk, ranking #82 out of 396 us metro areas. That puts it in the top third for AI exposure — a relatively large share of local jobs are in occupations that AI can automate or significantly change.
Ranked #82 of 396 us metro areas
Rank
#82
more exposed than most
Total Workforce
720 K
jobs analysed
High-Risk Jobs
25 K
3% of workforce
Out of
396
us metro areas
Most at Risk
Jobs in San Juan-Carolina-Caguas, PR most likely to be automated or transformed by AI
Telemarketer
500 employed
Data Entry Keyer
1.9 K employed
Transcriptionist
90 employed
Bookkeeper
5.2 K employed
Tax Preparer
460 employed
Customer Service Representative
15 K employed
Computer Programmer
900 employed
Copywriter
170 employed
Translator
150 employed
Web Developer
180 employed
Safest from AI
Jobs in San Juan-Carolina-Caguas, PR least likely to be affected by AI
Tree Trimmer
80 employed
Zookeeper
290 employed
Landscaper
4.6 K employed
Roofer
280 employed
Lifeguard
80 employed
Pest Control Technician
340 employed
Glazier
50 employed
Janitor
24 K employed
Concrete Finisher
530 employed
Massage Therapist
120 employed
What this means
The exposure score (53.5/100) measures how much of San Juan-Carolina-Caguas, PR's workforce is in jobs that AI can automate or significantly change. It's not a prediction that jobs will disappear — it's a measure of how exposed the local economy is to AI-driven change.
How it works: We score 289 occupations from 0 (AI has little impact) to 100 (AI can do most of the job) using 10 research sources. We then match these scores to real employment data for San Juan-Carolina-Caguas, PR, weighting by how many people actually work in each role.
High-risk jobs (score 60+) include roles like customer service, data entry, and bookkeeping where AI can already handle most tasks. Low-risk jobs (score under 30) include trades, healthcare, and social work where physical presence or human judgement is essential.
Full methodology · Data covers 36% of occupation categories in this area