Metro Area
AI Job Risk in Palm Bay-Melbourne-Titusville, FL
Palm Bay-Melbourne-Titusville, FL scores 54.1/100 for AI job risk, ranking #53 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 #53 of 396 us metro areas
Rank
#53
more exposed than most
Total Workforce
250 K
jobs analysed
High-Risk Jobs
13 K
5% of workforce
Out of
396
us metro areas
Most at Risk
Jobs in Palm Bay-Melbourne-Titusville, FL most likely to be automated or transformed by AI
Telemarketer
120 employed
Data Entry Keyer
270 employed
Transcriptionist
120 employed
Bookkeeper
2.3 K employed
Customer Service Representative
5.4 K employed
Tax Preparer
70 employed
Copywriter
50 employed
Computer Programmer
180 employed
Software Developer
4.7 K employed
Web Developer
Safest from AI
Jobs in Palm Bay-Melbourne-Titusville, FL least likely to be affected by AI
Landscaper
2 K employed
Zookeeper
510 employed
Roofer
740 employed
Lifeguard
190 employed
Concrete Finisher
410 employed
Pest Control Technician
350 employed
Massage Therapist
160 employed
Janitor
2.9 K employed
Tile Setter
200 employed
Drywall Installer
170 employed
What this means
The exposure score (54.1/100) measures how much of Palm Bay-Melbourne-Titusville, FL'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 Palm Bay-Melbourne-Titusville, FL, 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 41% of occupation categories in this area