AI Job Impact Analysis — Karpathy Releases Interactive Visualization of AI Exposure Across 342 Occupations
OpenAI co-founder Andrej Karpathy has released a free interactive tool that visualizes AI exposure scores (0–10) for 342 U.S. occupations covering 143 million jobs. Check how AI will impact your career right now.
"How much will AI change my job?" — One of the most prominent figures in AI has built a direct answer to this universal question. Andrej Karpathy, OpenAI co-founder and former head of Tesla AI, has released a free interactive visualization tool that analyzes all 342 U.S. occupations by AI impact. You can compare AI automation exposure across every job category at a glance, scored from 0 to 10.
AI Job Impact Analysis — 143 Million Jobs on a Single Screen
The tool is built on data from the Bureau of Labor Statistics (BLS) Occupational Outlook Handbook. It displays 342 occupations covering 143 million jobs across the entire U.S. economy in a single treemap — a visualization where each rectangle's size is proportional to employment numbers.
Each rectangle on the screen represents one occupation. The larger the rectangle, the more people work in that job, and the color changes based on the selected metric. You can toggle between four different color modes:
🔵 Growth Outlook — Whether the job is expected to grow or decline (green = growth, red = decline)
🟢 Salary Level — Median annual salary (green = $250K+, red = $25K or below)
🟣 Education Requirements — What degree is needed (green = no degree required, red = doctoral degree required)
🔴 AI Exposure — How much AI will transform this job, scored 0–10 (green = minimal impact, red = major transformation)
Hover over any occupation to instantly see its salary, employment count, growth rate, education requirements, AI exposure score, and the reasoning behind the score. Click to go directly to the BLS detailed occupation page.
AI Exposure Rankings — Most Transformed Jobs vs. Least Affected Jobs
Karpathy used Google's Gemini Flash AI model to assign an AI Exposure Score of 0–10 to each of the 342 occupations. The scoring criteria: "How digitally based is the work in this occupation, and can AI automate tasks or boost productivity enough to reduce the number of workers needed?"
AI Exposure Score 10 — Highest Impact Occupations
Customer Service Representatives — 2,814,000 workers, median salary $42,830
Court Reporters and Simultaneous Captioners — 17,700 workers, median salary $67,310
Repetitive tasks performed entirely in digital environments are projected to face the greatest AI impact.
AI Exposure Score 9 — Major Transformation Expected
• Bookkeeping, Accounting, and Auditing Clerks — 1,613,400 workers, $49,210
• Computer Support Specialists — 882,300 workers, $61,550
• Financial Clerks — 1,193,000 workers, $48,650
• Data Scientists — 245,900 workers, $112,590
• Computer Programmers — 121,200 workers, $98,670
• Editors — 115,800 workers, $75,260
• Financial Analysts — 429,000 workers, $101,910
The majority are occupations where work is done primarily at a computer.
AI Exposure Score 0–1 — Hands-On Jobs with Minimal AI Impact
• Construction Laborers and Helpers — 1,649,100 workers, $46,050 (score: 1)
• Athletes and Sports Competitors — 19,100 workers, $62,360 (score: 1)
• Roofers, Landscapers, Commercial Divers and other occupations in physical, unpredictable environments (score: 0–1)
Jobs that require physical labor and hands-on presence in the field are the least affected by AI.
AI Automation ≠ Job Elimination — Karpathy's Explanation
Karpathy was explicit on this point: A high AI exposure score does not mean "this job will disappear." For example, software developers scored a 9 — but as AI makes developers more productive, demand for software could actually increase.
The score reflects "how much AI will change the way work is done," not "how many jobs will be lost." Karpathy notes that factors like demand shifts, regulation, and social preferences ("I'd rather be served by a human") are not factored in — these are rough estimates.
AI Job Impact by the Numbers
The average AI exposure score across all 342 occupations is approximately 5.2. Jobs in the high-exposure bracket (8–10) account for roughly 7.2 million positions, or 26% of the total. The low-exposure bracket (0–2) covers about 3.1 million positions, or 11%. The remaining 63% fall in the middle range.
The relationship between salary and AI exposure is also notable. Both high-salary digital roles (financial analysts, data scientists) and lower-salary office jobs (customer service, bookkeeping) received high scores. Meanwhile, mid-salary skilled trades (electricians, plumbers) received relatively low scores.
Who Is Andrej Karpathy?
Andrej Karpathy is one of the most influential figures in AI. He was a founding member of OpenAI, served as head of Tesla's AI division, and designed Stanford University's first deep learning course (CS231n). He currently runs Eureka Labs, an AI education startup, and his YouTube series "Deep Dive into LLMs" has garnered millions of views.
This tool reflects his educator's mindset — focusing on making complex data visually accessible to everyone.
How to Check AI Impact on Your Job
No installation required — it works directly in your web browser:
👉 karpathy.ai/jobs — Open it in your browser to check the AI exposure score for your occupation.
Click the four buttons at the top (Growth Outlook / Salary / Education / AI Exposure) to switch color modes and explore the job market from different perspectives. Click any occupation rectangle to navigate to the BLS detailed page.
Developers who want to modify the data pipeline can grab the code from the GitHub repository and create their own scoring criteria — for example, rating occupations by "risk of robotic automation" or "offshoring potential."
While the data covers U.S. occupations, the underlying pattern — digital-based work is more exposed to AI than physical, on-site work — applies directly to job markets worldwide. If your work is done primarily at a computer, it's worth preparing for the changes AI will bring.
If you're curious about how AI will reshape your work, start by learning to use AI tools hands-on. Our Free Learning Guide covers everything from AI fundamentals to real-world automation, step by step.
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