Press & Media Kit

Everything journalists need to cover JobZone Risk — the AI job displacement scoring system.

US Workforce AI Exposure

BLS verified · Direct assessment 79.4% services · 19% industry · 1.6% agriculture (World Bank 2024)

168.7M

workers in zone assessment

0M+

Jobs protected from AI

33% of workers

0M+

Jobs needing adaptation

40% of workers

0M+

Jobs at high risk from AI

27% of workers

US Workforce AI Exposure each figure = ~1 million people

56.2M protected 68.1M transforming 44.3M at risk

Zone Distribution

~168.7M workers

By Workers (BLS employment-weighted)

33% · 56.2M Protected

40% · 68.1M Transforming

27% · 44.3M At Risk

Show distribution by role count (US data)

AI Displacement by State

% workforce in Red Zone

Loading map…

AI Displacement by US State

Localise the story: how many workers in each state face AI displacement? Select a state to see its zone breakdown.

Why does this breakdown look like this?

The US has the highest services-sector share of any major economy (79%). Retail, food service, clerical, and admin roles employ tens of millions of workers — and these routine, rules-based jobs are overwhelmingly classified RED. Meanwhile, healthcare, skilled trades, and education keep roughly 40% of workers in the GREEN zone.

All 51 Ranked by RED Zone %

#	State	Green	Yellow	Red	Workers
1	South Carolina	28.5%	39.0%	32.4%	2.3M
2	Mississippi	31.1%	36.7%	32.2%	1.1M
3	Tennessee	27.9%	40.1%	32.0%	3.3M
4	New Hampshire	29.4%	38.6%	32.0%	666K
5	Indiana	28.3%	39.7%	32.0%	3.2M
6	Georgia	26.7%	41.3%	32.0%	4.8M
7	South Dakota	32.7%	35.5%	31.8%	447K
8	Kentucky	28.4%	39.8%	31.8%	2.0M
9	Michigan	28.3%	40.0%	31.6%	4.4M
10	Alabama	29.8%	38.7%	31.5%	2.1M
11	Utah	28.6%	40.2%	31.3%	1.7M
12	Kansas	31.2%	37.8%	31.0%	1.4M
13	Arkansas	30.1%	38.9%	31.0%	1.3M
14	New Mexico	33.3%	35.8%	31.0%	842K
15	Oklahoma	30.2%	38.8%	31.0%	1.7M
16	North Carolina	29.9%	39.2%	30.9%	4.9M
17	Iowa	29.7%	39.4%	30.8%	1.6M
18	Delaware	29.6%	39.7%	30.7%	461K
19	Nebraska	31.4%	37.9%	30.7%	1.0M
20	Wisconsin	29.7%	39.8%	30.5%	2.9M
21	Idaho	30.1%	39.5%	30.4%	828K
22	New Jersey	30.9%	38.8%	30.3%	4.2M
23	Florida	28.6%	41.1%	30.3%	9.8M
24	Texas	29.9%	40.0%	30.1%	13.7M
25	Arizona	30.3%	39.6%	30.1%	3.2M
26	Missouri	30.9%	39.0%	30.0%	2.9M
27	Ohio	29.7%	40.4%	29.9%	5.5M
28	Washington	32.3%	37.9%	29.8%	3.5M
29	Maine	33.4%	37.0%	29.6%	627K
30	Hawaii	29.4%	41.0%	29.6%	605K
31	Oregon	29.3%	41.2%	29.5%	1.9M
32	North Dakota	34.5%	36.2%	29.3%	417K
33	Vermont	33.7%	37.1%	29.2%	293K
34	Minnesota	32.1%	38.8%	29.1%	2.9M
35	Montana	33.3%	37.6%	29.1%	501K
36	Colorado	30.9%	40.0%	29.1%	2.9M
37	Nevada	27.4%	43.6%	29.0%	1.5M
38	Virginia	31.3%	39.8%	28.8%	4.0M
39	West Virginia	35.9%	35.4%	28.7%	695K
40	Maryland	30.7%	40.7%	28.6%	2.7M
41	California	30.9%	40.6%	28.5%	18.0M
42	Alaska	34.9%	36.6%	28.5%	313K
43	Illinois	29.6%	42.0%	28.5%	6.0M
44	Rhode Island	31.9%	39.9%	28.2%	473K
45	Louisiana	33.2%	39.0%	27.9%	1.9M
46	Connecticut	31.8%	40.4%	27.8%	1.7M
47	Pennsylvania	32.8%	39.5%	27.7%	6.0M
48	District of Columbia	26.2%	46.5%	27.4%	685K
49	New York	35.6%	37.2%	27.2%	9.5M
50	Wyoming	35.7%	37.2%	27.1%	274K
51	Massachusetts	33.8%	39.9%	26.3%	3.6M

State estimates derived from BLS Occupational Employment and Wage Statistics (May 2024) cross-referenced with JobZone zone classifications. Employment counts represent jobs, not individuals. Zone percentages reflect the occupational composition of each state’s workforce.

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by United Kingdom

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

The UK’s services sector (83%) is the largest of any economy we track, but its composition differs from the US — a stronger NHS and public-sector healthcare workforce provides GREEN protection. Financial services, retail, and public-sector admin still drive significant RED exposure at levels comparable to (though slightly below) the US.

All 12 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	London	31.4%	33.9%	34.7%	5.3M
2	South East	34.6%	33.7%	31.7%	4.0M
3	East of England	35.2%	34.0%	30.9%	2.8M
4	South West	35.5%	34.0%	30.5%	2.5M
5	North West	35.7%	34.1%	30.2%	3.3M
6	Scotland	35.9%	33.9%	30.2%	2.5M
7	North East	36.2%	34.1%	29.7%	1.1M
8	Yorkshire & Humber	36.1%	34.2%	29.7%	2.5M
9	West Midlands	36.4%	34.1%	29.5%	2.6M
10	East Midlands	36.5%	34.2%	29.3%	2.1M
11	Wales	36.4%	34.4%	29.2%	1.4M
12	Northern Ireland	36.7%	34.3%	29.0%	820K

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by Europe

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

Europe’s lower services share (73%) and stronger manufacturing base shift more workers into YELLOW — roles that will be augmented rather than replaced. Countries like Germany and Italy retain significant industrial employment. Agriculture (3.3%) and traditional trades also contribute to a broader GREEN base.

All 29 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	Luxembourg	34.0%	35.0%	31.0%	275K
2	United Kingdom	35.0%	35.0%	30.0%	29.0M
3	Netherlands	35.0%	35.0%	30.0%	9.2M
4	France	36.0%	35.0%	29.0%	27.0M
5	Belgium	36.0%	35.0%	29.0%	4.6M
6	Sweden	36.0%	35.0%	29.0%	5.0M
7	Switzerland	36.0%	35.0%	29.0%	4.7M
8	Denmark	36.0%	35.0%	29.0%	2.8M
9	Norway	36.0%	35.0%	29.0%	2.6M
10	Ireland	36.0%	35.0%	29.0%	2.3M
11	Cyprus	36.0%	35.0%	29.0%	360K
12	Germany	37.0%	35.0%	28.0%	45.0M
13	Spain	37.0%	35.0%	28.0%	18.5M
14	Greece	37.0%	35.0%	28.0%	3.4M
15	Finland	37.0%	35.0%	28.0%	2.4M
16	Italy	38.0%	35.0%	27.0%	20.5M
17	Portugal	38.0%	35.0%	27.0%	4.5M
18	Austria	38.0%	35.0%	27.0%	4.1M
19	Croatia	38.0%	35.0%	27.0%	1.4M
20	Lithuania	38.0%	35.0%	27.0%	1.2M
21	Latvia	38.0%	35.0%	27.0%	780K
22	Estonia	38.0%	35.0%	27.0%	620K
23	Poland	39.0%	35.0%	26.0%	15.5M
24	Hungary	39.0%	35.0%	26.0%	4.0M
25	Bulgaria	39.0%	35.0%	26.0%	2.5M
26	Slovakia	39.0%	35.0%	26.0%	2.3M
27	Slovenia	39.0%	35.0%	26.0%	900K
28	Czechia	40.0%	35.0%	25.0%	4.9M
29	Romania	41.0%	35.0%	24.0%	7.5M

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by Germany

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

Germany’s industrial strength — 26% of employment vs. 19% in the US — is the key differentiator. Manufacturing, engineering, and skilled trades roles sit mostly in YELLOW and GREEN. However, Germany’s large admin and financial-services sector still generates significant RED exposure.

All 16 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	Berlin	33.1%	34.1%	32.8%	1.8M
2	Hamburg	33.1%	34.4%	32.5%	1.0M
3	Hessen	34.2%	34.6%	31.2%	3.3M
4	Bayern	34.5%	34.8%	30.7%	7.4M
5	Bremen	34.7%	34.7%	30.6%	320K
6	Baden-Württemberg	34.7%	34.7%	30.5%	5.9M
7	Nordrhein-Westfalen	35.0%	34.9%	30.1%	8.9M
8	Rheinland-Pfalz	35.7%	35.3%	29.0%	2.0M
9	Niedersachsen	35.9%	35.2%	29.0%	4.0M
10	Schleswig-Holstein	35.5%	35.7%	28.8%	1.4M
11	Sachsen	36.0%	35.9%	28.1%	2.0M
12	Thüringen	36.4%	35.7%	27.9%	1.0M
13	Saarland	36.7%	35.4%	27.9%	480K
14	Brandenburg	36.2%	35.9%	27.9%	1.1M
15	Sachsen-Anhalt	36.5%	35.9%	27.6%	1.0M
16	Mecklenburg-Vorpommern	36.4%	36.1%	27.5%	750K

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by Japan

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

Japan has the smallest RED zone among major economies. Its unique combination of a large manufacturing sector (23%), strong robotics industry, and cultural emphasis on job retention means more workers sit in GREEN and YELLOW.

All 47 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	Tokyo	32.9%	34.9%	32.2%	7.7M
2	Osaka	34.6%	35.6%	29.8%	4.2M
3	Kanagawa	34.5%	35.8%	29.8%	4.3M
4	Saitama	34.5%	35.7%	29.8%	3.4M
5	Kyoto	34.5%	35.7%	29.7%	1.2M
6	Chiba	34.5%	35.8%	29.7%	2.9M
7	Hyogo	35.0%	35.9%	29.2%	2.5M
8	Aichi	34.9%	35.9%	29.1%	3.8M
9	Fukuoka	35.0%	35.9%	29.1%	2.4M
10	Miyagi	35.2%	35.9%	28.9%	1.1M
11	Hiroshima	35.2%	36.2%	28.6%	1.3M
12	Ishikawa	35.0%	36.7%	28.3%	540K
13	Ibaraki	35.3%	36.4%	28.3%	1.4M
14	Hokkaido	35.5%	36.2%	28.3%	2.4M
15	Nara	35.4%	36.3%	28.2%	570K
16	Tochigi	35.4%	36.5%	28.0%	920K
17	Gunma	35.4%	36.5%	28.0%	920K
18	Shizuoka	35.6%	36.3%	28.0%	1.8M
19	Okinawa	36.2%	35.8%	28.0%	650K
20	Okayama	35.6%	36.4%	28.0%	890K
21	Shiga	35.5%	36.5%	28.0%	665K
22	Fukushima	36.0%	36.4%	27.6%	870K
23	Kagawa	35.8%	36.7%	27.6%	450K
24	Toyama	35.6%	36.9%	27.5%	520K
25	Mie	36.1%	36.4%	27.5%	840K
26	Niigata	36.2%	36.4%	27.5%	1.1M
27	Shimane	35.8%	36.8%	27.4%	310K
28	Gifu	36.0%	36.6%	27.4%	950K
29	Nagano	35.9%	36.7%	27.3%	980K
30	Iwate	36.1%	36.6%	27.3%	590K
31	Fukui	36.4%	36.4%	27.3%	385K
32	Yamanashi	36.0%	36.8%	27.3%	400K
33	Kumamoto	36.1%	36.6%	27.3%	800K
34	Tokushima	36.1%	36.7%	27.2%	335K
35	Wakayama	36.2%	36.7%	27.1%	425K
36	Oita	36.3%	36.7%	27.0%	540K
37	Yamaguchi	36.3%	36.8%	26.9%	620K
38	Ehime	36.3%	36.8%	26.9%	620K
39	Saga	36.3%	36.8%	26.9%	375K
40	Tottori	36.2%	36.9%	26.9%	260K
41	Aomori	36.6%	36.6%	26.8%	590K
42	Miyazaki	36.5%	36.7%	26.7%	490K
43	Yamagata	36.3%	36.9%	26.7%	520K
44	Nagasaki	36.4%	36.9%	26.7%	585K
45	Kagoshima	36.5%	36.9%	26.6%	740K
46	Kochi	36.6%	36.9%	26.5%	325K
47	Akita	36.8%	36.8%	26.4%	440K

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by Canada

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

Canada closely mirrors the US pattern — a large services sector (80%) creates similar RED exposure through retail, admin, and customer-service roles. Strong natural-resources and healthcare sectors provide GREEN protection.

All 13 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	British Columbia	34.7%	32.8%	32.5%	2.6M
2	Ontario	34.9%	32.8%	32.2%	7.7M
3	Northwest Territories	32.0%	36.0%	32.0%	25K
4	Alberta	34.9%	33.2%	31.9%	2.4M
5	Quebec	35.1%	33.0%	31.9%	4.3M
6	Yukon	36.4%	31.8%	31.8%	22K
7	Nova Scotia	35.2%	33.5%	31.3%	460K
8	Saskatchewan	35.5%	33.4%	31.1%	560K
9	Manitoba	35.8%	33.3%	30.9%	660K
10	New Brunswick	35.6%	33.6%	30.8%	360K
11	Prince Edward Island	34.6%	34.6%	30.8%	78K
12	Nunavut	38.5%	30.8%	30.8%	13K
13	Newfoundland & Labrador	35.9%	33.6%	30.5%	220K

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by Australia

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

Australia’s economy is structurally similar to Canada and the US, with a dominant services sector (78%). Mining and natural resources provide some GREEN insulation, but the large retail, hospitality, and financial-services workforce drives RED percentages comparable to the UK.

All 8 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	Australian Capital Territory	32.1%	32.1%	35.8%	240K
2	Northern Territory	35.0%	32.5%	32.5%	120K
3	Victoria	34.9%	32.8%	32.3%	3.5M
4	New South Wales	34.7%	33.0%	32.3%	4.1M
5	Western Australia	34.9%	33.2%	31.9%	1.4M
6	Queensland	35.5%	33.3%	31.2%	2.6M
7	South Australia	35.6%	33.5%	30.9%	860K
8	Tasmania	36.4%	33.5%	30.2%	242K

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by South Korea

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

South Korea’s significant manufacturing sector (24%) — especially electronics, automotive, and shipbuilding — places more workers in the YELLOW adaptation zone. Higher agriculture (5.2%) compared to other advanced economies adds a small GREEN buffer.

All 17 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	Seoul	34.5%	34.1%	31.5%	5.3M
2	Gyeonggi	35.6%	34.8%	29.6%	7.0M
3	Daejeon	35.8%	34.7%	29.4%	720K
4	Sejong	36.1%	35.0%	28.9%	180K
5	Incheon	36.1%	35.1%	28.8%	1.4M
6	Busan	36.4%	35.2%	28.4%	1.6M
7	Gwangju	36.6%	35.1%	28.2%	680K
8	Daegu	36.6%	35.2%	28.2%	1.1M
9	South Chungcheong	36.5%	35.7%	27.8%	1.0M
10	Ulsan	36.9%	35.5%	27.6%	510K
11	South Gyeongsang	36.9%	35.7%	27.4%	1.5M
12	North Chungcheong	37.2%	35.5%	27.3%	740K
13	Gangwon	37.3%	35.8%	26.9%	670K
14	North Gyeongsang	37.5%	35.8%	26.7%	1.2M
15	North Jeolla	37.6%	35.9%	26.5%	800K
16	Jeju	37.4%	36.1%	26.5%	310K
17	South Jeolla	37.9%	36.2%	25.9%	810K

AI Displacement by Region

% workforce in Red Zone

Loading map…

AI Displacement by Global

Localise the story: how many workers in each region face AI displacement? Select a region to see its zone breakdown.

Why does this breakdown look like this?

The global average has a larger GREEN zone and significantly smaller RED zone than advanced economies. Agriculture employs 26% of the world’s workers in roles with physical and environmental complexity that resists near-term automation. Lower-income economies have less services-sector employment, which substantially reduces RED exposure — consistent with IMF estimates that low-income countries face roughly half the AI displacement risk of advanced economies.

All 30 Ranked by RED Zone %

#	Region	Green	Yellow	Red	Workers
1	Canada	35.0%	33.0%	32.0%	19.0M
2	Australia	35.0%	33.0%	32.0%	13.1M
3	United Kingdom	35.0%	34.0%	31.0%	29.0M
4	France	35.0%	34.0%	31.0%	27.0M
5	Italy	35.0%	34.0%	31.0%	20.5M
6	Spain	35.0%	34.0%	31.0%	18.5M
7	Poland	35.0%	34.0%	31.0%	15.5M
8	Netherlands	35.0%	34.0%	31.0%	9.2M
9	Sweden	35.0%	34.0%	31.0%	5.0M
10	United States	29.0%	40.0%	31.0%	155.0M
11	Germany	35.0%	35.0%	30.0%	45.0M
12	Japan	35.0%	36.0%	29.0%	63.0M
13	South Korea	36.0%	35.0%	29.0%	25.5M
14	China	50.0%	28.0%	22.0%	760.0M
15	Mexico	52.0%	27.0%	21.0%	55.0M
16	Saudi Arabia	52.0%	27.0%	21.0%	11.0M
17	Malaysia	52.0%	27.0%	21.0%	14.0M
18	Brazil	52.0%	28.0%	20.0%	90.0M
19	Russia	50.0%	30.0%	20.0%	66.0M
20	Turkey	52.0%	28.0%	20.0%	30.0M
21	Thailand	52.0%	28.0%	20.0%	35.0M
22	Philippines	58.0%	24.0%	18.0%	42.0M
23	South Africa	58.0%	24.0%	18.0%	14.0M
24	Egypt	60.0%	24.0%	16.0%	27.0M
25	India	62.0%	23.0%	15.0%	500.0M
26	Indonesia	62.0%	23.0%	15.0%	125.0M
27	Vietnam	62.0%	23.0%	15.0%	47.0M
28	Nigeria	64.0%	22.0%	14.0%	50.0M
29	Pakistan	64.0%	22.0%	14.0%	50.0M
30	Bangladesh	66.0%	21.0%	13.0%	67.0M

What Is JobZone Risk?

JobZone Risk is the world’s first comprehensive AI job displacement scoring system, rating 3,649 professions on a 0–100 scale across 8 dimensions. Every role is classified into a GREEN (AI-resistant), YELLOW (changing), or RED (high displacement risk) zone.

Built by Nathan House, CEO of cybersecurity training platform StationX, after realising AI would displace the very entry-level jobs his students were training for. The scoring methodology draws on 47 data sources including Oxford, McKinsey, OECD, BLS, and Anthropic research. Full methodology →

✓

Convergent Evidence: Anthropic’s Data Confirms JobZone Scores

March 2026 — Massenkoff & McCrory, “Labor market impacts of AI”

Two completely independent approaches — one measuring actual AI usage from inside the model (Anthropic), one measuring labour market impact from 47 external data sources (JobZone) — arrived at the same conclusions about which jobs face the highest displacement risk.

Result: 10 out of 10 match. Every occupation Anthropic flagged as highly exposed falls in JobZone’s Red or Yellow Urgent zone.

Occupation	Anthropic Exposure	JobZone Score	Zone
Computer Programmers	74.5%	10.2	Red
Customer Service Reps	70.1%	13.2	Red
Data Entry Keyers	67.7%	2.3	Red
Medical Records Specialists	66.7%	15.1	Red
Info Security Analysts	49.8%	22.9	Red
Market Research Analysts	64.0%	26.0	Yellow Urgent
Computer User Support	46.3%	26.3	Yellow Urgent
Sales Reps (Wholesale/Mfg)	42.8%	26.1	Yellow Urgent
Financial Analysts	37.2%	26.4	Yellow Urgent
Software QA Analysts	30.9%	26.0	Yellow Urgent

Anthropic Exposure = percentage of tasks actually performed by AI in production (Claude usage data). JobZone Score = 0–100 composite risk score (lower = higher displacement risk). Sorted by Anthropic exposure descending.

What Anthropic’s data doesn’t cover: Anthropic provides one number per occupation across 756 roles. JobZone scores 3,649 roles across 8 dimensions, differentiates by seniority level (a junior developer and a staff architect face very different risks), includes automation barriers, and provides individual survival strategies. Anthropic measured what AI does. JobZone measures what happens to the people.

Data: Anthropic Economic Index on HuggingFace

Key Findings

Attributed to Nathan House, CEO of StationX and creator of JobZone Risk. Click any quote to copy.

Ready-to-Publish Quotes

Top 10 Safest Roles

#	Role	Score	Zone
1	Electrical Power-Line Installer and Repairer (Mid-Level)	91.6	GREEN
2	Signalling Tester In Charge / STIC (Mid-Level)	87.7	GREEN
3	Model Alignment Researcher (Mid-Level)	86.1	GREEN
4	AI Safety Researcher (Mid-Senior)	85.2	GREEN
5	Foster Carer (Mid-Level)	84.5	GREEN
6	Leadworker (Mid-Level)	83.7	GREEN
7	Heat Pump Installer (Mid-Level)	83.5	GREEN
8	Trauma Surgeon (Mid-to-Senior)	83.2	GREEN
9	CCS Engineer (Control Command & Signalling) (Mid-Level)	83.2	GREEN
10	Chief Information Security Officer (CISO) (Senior/Executive)	83.0	GREEN

Top 10 Most At-Risk Roles

#	Role	Score	Zone
1	File Clerks (Mid-Level)	1.5	RED
2	Micro-Task Worker (Online) (Mid-Level)	1.7	RED
3	Data Entry Keyer (Mid-Level)	2.3	RED
4	Word Processor and Typist (Mid-Level)	2.6	RED
5	Vulnerability Tester / Scanner Operator (Entry-Level)	2.7	RED
6	Telephone Operator (Mid-Level)	3.0	RED
7	Virtual Assistant (Entry-to-Mid Level)	3.2	RED
8	Live Chat Support Agent (Entry-to-Mid Level)	3.4	RED
9	Telemarketer (Mid-Level)	3.4	RED
10	Medical Transcriptionist (Mid-Level)	3.6	RED

These are the extremes. Browse all 3,649 scored roles →

You’re in the data too.

A reporter scores RED. A foreign correspondent scores GREEN. Same profession, completely different AI future. Seniority and specialism change everything.

Investigative Journalist

Foreign Correspondent

50.9

GREEN

Generic reporting roles scored RED. Specialist and senior journalism roles scored GREEN. The pattern holds across the whole profession. See all journalism roles →

It’s Already Happening

These aren’t forecasts. Real companies are already cutting real jobs and citing AI as the reason. Every story below is independently sourced.

2026 tech layoffs reach 45000 in March, more than 9200 due to AI and automation

As of March 2026, over 9,200 of the 45,363 tech layoffs worldwide have been linked to AI implementation and organizat...

Google · 21d ago

Block spent 18 months 're-skilling staff' with AI. Now it is laying off 4,000 workers.

Google News · 27d ago

Verizon to Cut 13,000 Jobs, Set Up $20 Million “Reskilling” Fund for Laid Off Staff In “Age of AI”

Google News · 130d ago

Tech Layoffs Surge While AI Jobs Soar: Key Trends Shaping the 2026 Tech Industry

Early 2026 has seen over 45,000 global tech layoffs, largely driven by AI restructuring, even as hiring for AI-relate...

Google · 9d ago

AI is eating entry-level tech jobs, and young developers are paying the price

Employment for software developers under 25 declined nearly 20% by July 2025, while entry-level tech hiring dropped 2...

Google · 14d ago

Labor market impacts of AI: A new measure and early evidence - Anthropic

Anthropic introduces a new measure of AI displacement risk, 'observed exposure,' combining theoretical LLM capabiliti...

Google · 25d ago

Nordea plans job cuts amid restructuring initiatives - FinTech Futures

Nordea's plans are set to impact around 1,500 employees by 2027, with the restructuring expected to deliver cost savi...

Fintechfutures · 12d ago

Jamie Dimon just made a bold prediction about AI and your job - TheStreet

Jamie Dimon, CEO of JPMorgan Chase, predicts AI will lead to shorter workweeks (3.5 days) and longer, healthier lives...

Google · 25d ago

See all AI displacement news →

AI Also Creates Jobs — But Different Ones

Displacement is only half the story. AI adoption is simultaneously creating entirely new occupations that didn’t exist five years ago. The challenge: the people losing jobs aren’t the same people getting the new ones.

New Roles Hiring Now

JobZone has assessed 30 AI-created roles. These five have real job postings, real salaries, and measurable year-over-year growth based on our REL framework analysis.

AI Safety Researcher +78% YoY AI Agent Architect +71% YoY AI Red Team Specialist +63% YoY AI Governance Lead +50% YoY AI Auditor +50% YoY

Salaries range $95K–$300K+. Regulation (EU AI Act, NIST AI RMF) is a key driver of AI governance and safety hiring. Browse all assessed roles →

What the Forecasters Say

World Economic Forum (2025)

Projects 170 million new jobs created globally by 2030, against 92 million displaced — a net gain of 78 million. (Note: WEF’s 2023 report projected a net loss of 14 million. The revision reflects faster-than-expected AI-adjacent job creation.)

McKinsey Global Institute

Long-term net impact “likely positive” due to productivity gains, but up to 12 million U.S. workers may need to switch occupations by 2030. Massive reskilling required.

OECD Employment Outlook

Negative employment effects from AI have not yet materialised to a significant extent. 27% of OECD jobs at high risk. Outcome depends heavily on policy actions.

Indeed Hiring Lab (Jan 2026)

AI job postings growing 130%+ year-over-year, but in an otherwise weak “low-hire, low-fire” labour market. AI roles are bucking the trend.

Why this doesn’t solve the problem

Net job creation projections assume successful reskilling at scale. The new roles require significant technical skills, pay $100K+, and concentrate in metros with existing tech ecosystems. A displaced call centre worker in Ohio cannot become an AI Safety Researcher without years of retraining and likely relocation. The story: job creation numbers are meaningless without transition infrastructure.

Sources: WEF Future of Jobs 2025, McKinsey, OECD, Indeed Hiring Lab, PwC AI Jobs Barometer. AI-created role data from JobZone’s own REL framework assessment of 30 roles.

How Fast Is This Moving?

The question isn’t whether AI will reshape the labour market — it’s how quickly different sectors will be hit. Institutional forecasts and our own JobZone data converge on three overlapping phases.

Phase 1: Now

2024–2027

Already underway

Knowledge-work automation via LLMs. Entry-level white-collar displacement accelerating. First factory humanoid deployments.

Who’s affected:

RED-zone roles — data entry, bookkeeping, junior developers, admin assistants, SDRs.

Phase 2: Near-Term

2027–2032

Accelerating

Agentic AI handling multi-step workflows. Semi-structured robotics pilots in hospitals and new construction. Professional services disruption.

Who’s affected:

YELLOW-zone roles — analysts, mid-level tech, paralegals, some professional services.

Phase 3: Medium-Term

2032–2040+

Physical work enters

Robotics expands into unstructured environments — homes, existing buildings, bedside care. Task automation begins in trades and healthcare.

Who’s affected:

Currently GREEN roles with physical-world protection start eroding — but skilled trades and bedside care retain 20–35+ years of protection.

What the Data Shows

Entry-level employment in AI-exposed roles down ~13% since 2022 (up to 16% relative to less-exposed occupations). Entry-level software development job postings down nearly 20% from their late-2022 peak. The pipeline damage may be irreversible within 2–3 years without intervention.

Stanford Digital Economy Lab / Brynjolfsson et al.; SPARK6

300 million full-time jobs globally exposed to generative AI. Two-thirds of US occupations have some exposure, with 25–50% of workload potentially replaceable.

Goldman Sachs (March 2023)

40% of global employment exposed to AI — rising to 60% in advanced economies. In low-income countries, 26%. Of exposed jobs in advanced economies, roughly half may benefit; the other half face reduced demand.

IMF (January 2024)

50% of work activities could be automated between 2030 and 2060, with a midpoint of ~2045. Generative AI accelerated this estimate by roughly a decade compared to McKinsey’s pre-2023 forecast.

McKinsey Global Institute (June 2023)

PwC’s Three Waves: Algorithm wave (~3% of jobs, to early 2020s) → Augmentation wave (~20%, to late 2020s) → Autonomy wave (~30%, to mid-2030s). Each wave expands the blast radius from data tasks to physical-world tasks.

PwC (February 2018)

Both sides are accelerating

The gap between forecasts and reality is shrinking. WEF revised its 2023 projection (net −14 million jobs by 2027) to net +78 million by 2030 — not because displacement slowed, but because new-role creation is happening faster than expected. Displacement and creation are both accelerating. The story: the window for proactive intervention is narrower than it appears.

Sources: PwC Three Waves (2018), Goldman Sachs (2023), IMF (2024), McKinsey (2023), WEF Future of Jobs 2025.

Workers Affected by Country

US data from BLS; other countries estimated using IMF/OECD sector-weighted labour models.

Country	Workforce	At Risk	Changing	Safe
🇺🇸US	168.7M	44.3M	68.1M	56.2M
🇬🇧UK	34.2M	10.6M	11.6M	12.0M
🇪🇺Europe	209.0M	58.5M	73.2M	77.3M
🇩🇪Germany	46.0M	12.9M	16.1M	17.0M
🇯🇵Japan	69.0M	17.3M	24.8M	26.9M
🇨🇦Canada	20.7M	6.6M	6.8M	7.2M
🇦🇺Australia	14.6M	4.5M	4.8M	5.3M
🇰🇷South Korea	29.5M	8.0M	10.3M	11.2M
🌍Global	3.5B	724.5M	1.3B	1.4B

AI Resistance by Industry Domain

Average JobZone Risk Score per domain. Higher = more AI-resistant. Scores below 25 = RED zone, 25–47 = YELLOW, 48+ = GREEN.

Trades & Physical

60.5 Veterinary & Animal Care

59.8 Military

57.6 Healthcare

57.5 Sports & Recreation

56.2 AI

56.0 Social Services

55.8 Religious & Community

54.4 Public Safety

53.0 Utilities & Energy

46.0 Government & Public Admin

42.4 Retail & Service

40.8 Science & Research

40.7 Legal & Compliance

39.7 Library, Museum & Archives

39.4 Creative & Media

37.2 Development

36.0 Cloud & Infrastructure

35.1 Real Estate & Property

34.5 Manufacturing

31.1 Business & Operations

29.6 Data

28.6

Fact Sheet

Product	JobZone Risk
URL	jobzonerisk.com
What it does	Scores jobs for AI displacement risk (0–100)
Roles scored	3,649
Industry domains	28
US workforce covered	100% (168.7M workers)
Data sources	47 (Oxford, McKinsey, OECD, BLS, Anthropic)
Methodology	AIJRI v3.2
Updates	Continuous (news-fed, real-time)
Founded by	Nathan House, CEO of StationX
Price	Free
API access	Free API key available

Access the Data

All JobZone Risk data is free. Search roles, explore dashboards, or plug the full dataset directly into your own analysis.

Search any role

Look up any of 3,649+ roles and see AI displacement scores, zone ratings, and task-level breakdowns.

Live data monitor

Real-time dashboard with country breakdowns, domain analysis, and zone distribution across the full workforce.

Compare & transition paths

Compare at-risk roles against safer alternatives to identify practical retraining pathways for displaced workers.

Full dataset for LLMs

The complete database in plain text — optimised for ChatGPT, Claude, and other AI assistants. Feed it in and ask questions about any role.

Embeddable widgets

Drop a live risk-score widget into your own site or report. Copy one line of HTML — scores update automatically as new data comes in.

Need something else? For bulk data exports, custom analysis, or integration support — get in touch.

Media Assets

High-resolution assets for editorial use. Click to download.

Workers at Risk by Country

Data visualisations ready for editorial use. Available in dark and light versions.

44.3 million Americans work in jobs where AI can already do most of the work

United States — 44.3M at risk

1200×630 PNG

Download Dark Download Light

All graphics based on JobZone scores mapped to national employment data. Jobs scoring under 25/100 are ones where AI can already perform most core tasks.

Plumber vs Programmer

A plumber scores 8× higher on AI resistance than a programmer. Our most contrarian finding.

Plumber scores 81.4, Programmer scores 10.2 on AI Job Resistance Index

Plumber 81.4 vs Programmer 10.2

1200×630 PNG

Download Dark Download Light

Junior vs Senior Developer

Seniority is the single biggest factor in AI resistance. A junior developer scores 9.3; a senior engineer scores 55.4.

Junior Developer scores 9.3, Senior Engineer scores 55.4 on AI Job Resistance Index

Junior 9.3 vs Senior 55.4

1200×630 PNG

Download Dark Download Light

Every Doctor is GREEN

All 20 physician and surgeon roles in our index scored GREEN. Scores range from 52.0 (Radiologist) to 76.7 (Orthopedic Surgeon).

20 out of 20 doctors scored GREEN on AI Job Resistance Index

20/20 Doctors — All GREEN

1200×630 PNG

Download Dark Download Light

Zero Analysts Score Safe

0 out of 17 business analyst roles scored GREEN. Six are RED. The highest (Quantitative Analyst) manages only 43.7.

0 out of 17 business analysts score safe on AI Job Resistance Index

0/17 Business Analysts — None Safe

1200×630 PNG

Download Dark Download Light

Blue Collar vs White Collar

Trades & Physical roles average 56.2 (GREEN). Business & Operations averages 28.3 (YELLOW). Hands-on work resists AI 2× better.

Trades & Physical average 56.2 vs Business & Operations average 28.3 on AI Job Resistance Index

Trades 56.2 vs Business 28.3

1200×630 PNG

Download Dark Download Light

Brand Assets

About Nathan House

Nathan House is a cybersecurity and AI expert with 30 years of hands-on experience. He has secured systems at companies including Vodafone, BP, ExxonMobil, and GSK, and trained organisations including Microsoft, Cisco, Siemens, and Thales. He built JobZone Risk after realising AI would displace the very entry-level cybersecurity jobs his 500,000+ students were training for — and that no rigorous, data-driven index existed to quantify the risk. He is founder of StationX, one of the world’s largest cybersecurity training platforms. Why I built this →

Awards & Recognition

Media

CNN, Fox News, NBC, NDTV
PC Extreme Magazine
Published white papers on AI, cybersecurity trends, and emerging threats

Certifications

CISSP, OSCP, CEH, CISM, CISA, ISO 27001 Lead Auditor, SABSA

Connect

55K+ LinkedIn followers

Press Contact

Nathan House is available for interviews, commentary, and data requests. For press enquiries:

[email protected] WhatsApp @GotoNathan on X

Typical response time: same business day.

Methodology

Every role is scored using an 8-dimension framework — the AI Job Resistance Index (AIJRI) — that measures current AI capability overlap, automation barriers, displacement evidence, protective factors, market dynamics, and growth correlation. Each dimension produces a sub-score; the weighted composite becomes the role’s overall JobZone Score (0–100).

Based on 47 data sources including Oxford, McKinsey, OECD, and BLS. Scores are re-evaluated as AI capabilities and labour market data change.

Scores aren’t static. JobZone Risk continuously monitors global news feeds, tracking AI capability announcements, labour market shifts, and regulatory changes. Each story is assessed for sentiment and relevance — when a material event occurs (new legislation, a major AI deployment, an industry restructuring), affected role scores are re-evaluated and updated. This means the data journalists cite today reflects the current state of AI displacement, not a one-time snapshot.

AIJRI v3.2 — February 2026 Full methodology