Metro Area
AI Job Risk in Baltimore-Columbia-Towson, MD
Baltimore-Columbia-Towson, MD scores 54.2/100 for AI job risk, ranking #48 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 #48 of 396 us metro areas
Rank
#48
more exposed than most
Total Workforce
1.4 M
jobs analysed
High-Risk Jobs
36 K
3% of workforce
Out of
396
us metro areas
Most at Risk
Jobs in Baltimore-Columbia-Towson, MD most likely to be automated or transformed by AI
Telemarketer
350 employed
Data Entry Keyer
940 employed
Transcriptionist
130 employed
Tax Preparer
430 employed
Bookkeeper
10 K employed
Customer Service Representative
22 K employed
Proofreader
40 employed
Computer Programmer
1.2 K employed
Copywriter
320 employed
Translator
300 employed
Safest from AI
Jobs in Baltimore-Columbia-Towson, MD least likely to be affected by AI
Tree Trimmer
410 employed
Lifeguard
1.6 K employed
Zookeeper
2.4 K employed
Roofer
1.3 K employed
Landscaper
7.6 K employed
Grounds Maintenance Worker
100 employed
Pest Control Technician
820 employed
Janitor
17 K employed
Concrete Finisher
1.8 K employed
Massage Therapist
770 employed
What this means
The exposure score (54.2/100) measures how much of Baltimore-Columbia-Towson, MD'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 Baltimore-Columbia-Towson, MD, 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 34% of occupation categories in this area