Metro Area
AI Job Risk in Boston-Cambridge-Nashua, MA-NH
Boston-Cambridge-Nashua, MA-NH scores 55.8/100 for AI job risk, ranking #16 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 #16 of 396 us metro areas
Rank
#16
more exposed than most
Total Workforce
2.9 M
jobs analysed
High-Risk Jobs
85 K
3% of workforce
Out of
396
us metro areas
Most at Risk
Jobs in Boston-Cambridge-Nashua, MA-NH most likely to be automated or transformed by AI
Telemarketer
540 employed
Data Entry Keyer
1.6 K employed
Transcriptionist
180 employed
Tax Preparer
1.7 K employed
Customer Service Representative
49 K employed
Bookkeeper
26 K employed
Proofreader
560 employed
Computer Programmer
3.5 K employed
Copywriter
980 employed
Translator
1.5 K employed
Safest from AI
Jobs in Boston-Cambridge-Nashua, MA-NH least likely to be affected by AI
Tree Trimmer
Roofer
1.5 K employed
Landscaper
15 K employed
Zookeeper
6 K employed
Lifeguard
2 K employed
Tile Setter
250 employed
Farm Worker
780 employed
Concrete Finisher
1.2 K employed
Janitor
44 K employed
Pest Control Technician
1.2 K employed
What this means
The exposure score (55.8/100) measures how much of Boston-Cambridge-Nashua, MA-NH'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 Boston-Cambridge-Nashua, MA-NH, 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 32% of occupation categories in this area