Why JobZone Risk Exists
Roughly 45 million Americans are in jobs where AI can already do most of the work. Scale that up globally and even conservatively, we’re talking about hundreds of millions of us in jobs where AI can replace us. The technology doesn’t care about borders. And most of us have no idea what’s coming.
That’s what this site is for. You type in your job and it shows you exactly how likely it is for you to be replaced by AI. Which parts are safe, which ones aren’t. Whether you’re in a RED zone, YELLOW zone, or GREEN zone. And if you are at risk, it shows you safer jobs and how to get there. Not a scary headline. A proper assessment based on real evidence.
How do I know this? I run a cybersecurity company. Over the last few months, I’ve built an AI system for my business that can do about 80% of what we do day to day. It does research that used to take someone a whole day in about ten minutes. It runs automated security testing. The underlying technology is available to any company that wants to build something like it. And it’s only a matter of time before they do.
So I’ve looked at 3649 jobs — nurses, truck drivers, accountants — and scored them on how automatable the work is, what’s happening in the job market, what barriers stand in the way, and where this is heading. Eight dimensions per job, drawing on Oxford, McKinsey, and OECD research.
But here’s the bit that matters most. Not every job is at risk. Some jobs will do really well alongside AI. I call them GREEN zone jobs. Once we can see that, we can start making better decisions about our careers. So have a look. Find your job. See where you stand. And if you need to move — this will show you where to go.
I hope this starts a conversation. Please share it with anyone you think needs to see it. It’s completely free. And as I get more data, I’ll keep adding advice on what you can actually do about it. Let’s solve this together.
Workers Affected by AI Displacement Risk
Based on our analysis of 3649 roles. US data from BLS; other countries estimated using IMF/OECD labour models. Full data monitor →
| Country | Workforce | At Risk | Changing | Safe |
|---|---|---|---|---|
| πΊπΈUnited States | 168.7M | 44.3M | 68.1M | 56.2M |
| π¬π§United Kingdom | 34.2M | 10.6M | 11.6M | 12.0M |
| πͺπΊEurope | 209.0M | 58.5M | 73.2M | 77.3M |
| π©πͺGermany | 46.0M | 12.9M | 16.1M | 17.0M |
| π―π΅Japan | 69.0M | 17.3M | 24.8M | 26.9M |
| π¨π¦Canada | 20.7M | 6.6M | 6.8M | 7.2M |
| π¦πΊAustralia | 14.6M | 4.5M | 4.8M | 5.3M |
| π°π·South Korea | 29.5M | 8.0M | 10.3M | 11.2M |
| πGlobal | 3.5B | 724.5M | 1.3B | 1.4B |
StationX is a cybersecurity and AI training platform with over 500,000 students worldwide. Founded by Nathan House, we provide practical, career-focused training that helps people break into cybersecurity and navigate the rapidly evolving tech landscape.
Our mission is simple: make cybersecurity education accessible, practical, and honest. No gatekeeping, no false promises — just clear paths to real careers.
About Nathan House
Nathan House is an AI and cybersecurity expert with 30 years of hands-on experience. He has worked with clients including Microsoft, Cisco, BP, Vodafone, and VISA.
He holds CISSP, CISM, CISA, CEH, OSCP, and ISO 27001 Lead Auditor certifications, was named Cyber Security Educator of the Year 2020, and is a UK Top 25 Security Influencer 2025. He has been featured as an expert on CNN, Fox News, NBC, and NDTV.
Nathan founded StationX to bridge the gap between learning cybersecurity and getting hired. JobZone Risk is an extension of that mission — ensuring people invest their career development in the right direction.
About StationX HAL
HAL is a custom AI infrastructure built by Nathan House for StationX. It powers research, development, content creation, and business operations across the team — with shared context that lets staff collaborate through it.
HAL co-develops JobZone Risk end-to-end: the AIJRI scoring methodology, the assessment generation pipeline, the web application, every role assessment, server provisioning, infrastructure maintenance, code review, penetration testing, and security auditing — all directed by Nathan and the StationX team.
It’s not replacing anyone. It’s a co-working system that accelerates delivery by roughly 50x, letting a small team ship what would normally require a department.
Our Approach
The AIJRI methodology (v3) analyses each role across multiple dimensions: current AI capability overlap, barrier to automation, evidence of displacement, protective factors, and AI-driven growth correlation. Every assessment is backed by data from 47 sources and reviewed for accuracy.
We currently cover 3649 roles across 28 domains and 194 specialisms, representing 100% of BLS-tracked US employment.
Our role database has been cross-validated against five international occupational classification systems — the US O*NET, the EU ESCO taxonomy (3,043 occupations), UK SOC 2020, Canadian NOC, and Australian/NZ ANZSCO — covering 6,427 classified occupations. Every classified occupation maps to an assessed role.