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Metro Area

AI Job Risk in Tulsa, OK

Tulsa, OK scores 52.2/100 for AI job risk, ranking #155 out of 396 us metro areas. That puts it around the middle — a moderate mix of AI-vulnerable and AI-resistant jobs in the local economy.

52.2 /100
High Risk

Ranked #155 of 396 us metro areas

52.2
Low risk High risk

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Rank

#155

around the middle

Total Workforce

470 K

jobs analysed

High-Risk Jobs

17 K

4% of workforce

Out of

396

us metro areas

Most at Risk

Jobs in Tulsa, OK most likely to be automated or transformed by AI

1

Telemarketer

330 employed

95
2

Data Entry Keyer

560 employed

95
3

Transcriptionist

80 employed

92
4

Tax Preparer

440 employed

90
5

Bookkeeper

4.6 K employed

90
6

Customer Service Representative

9.2 K employed

90
7

Copywriter

88
8

Computer Programmer

200 employed

88
9

Translator

80 employed

86
10

Bank Teller

1.7 K employed

85

Safest from AI

Jobs in Tulsa, OK least likely to be affected by AI

1

Tree Trimmer

290 employed

8
2

Roofer

210 employed

10
3

Zookeeper

1 K employed

10
4

Lifeguard

90 employed

10
5

Landscaper

2.3 K employed

10
6

Park Ranger

30 employed

10
7

Janitor

5.2 K employed

12
8

Glazier

300 employed

12
9

Pest Control Technician

290 employed

12
10

Tile Setter

80 employed

12

What this means

The exposure score (52.2/100) measures how much of Tulsa, OK'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 Tulsa, OK, 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 37% of occupation categories in this area

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