About

We believe the future of work should inspire hope, not fear. Learn how we make AI labor market data accessible to everyone.

About the Author

Heechang Han

Editor & Author

Heechang Han founded AI Changing Work in 2026 to make peer-reviewed labor market research accessible to workers in 11 languages. The project is an independent, owner-edited publication: AI assists with drafting and data processing, and Heechang Han holds editorial responsibility for what is published.

The motivation is simple. Most coverage of AI and jobs swings between hype and panic. Workers - from nurses to engineers to teachers - deserve a calmer, data-grounded view of what is actually changing, what is staying the same, and what concrete skills tend to remain valuable. This site is an attempt to provide that view.

AI-assistedAuthor-reviewed

Editorial transparency: content on AI Changing Work is AI-assisted — drafted and analyzed with Anthropic Claude. Every post carries that disclosure at the top of the page, above the article text; that disclosure is how we meet the transparency duty in EU AI Act Art. 50(4), and we do not rely on that article's human-review exemption. Every post is also published under a real-name byline ("Heechang Han") with structured data (Schema.org Article with Person author), and Heechang Han holds editorial responsibility for the publication — which is what FTC AI guidance and Google E-E-A-T standards ask for.

Our Mission

AI Changing Work was founded on a simple belief: people deserve clear, honest information about how AI is changing their jobs. Not hype. Not fear. Just data.

Hope, not fear. Courage, not despair.

The conversation about AI and jobs is often dominated by extremes - utopian promises or dystopian warnings. We started this project because workers deserve better than clickbait headlines. By translating peer-reviewed research into plain language, we help people make informed decisions about their careers, education, and future.

Our Data & Methodology

We cover 1,010 occupations. The AI exposure figures shown for each are reproduced from published external research, and the employment figures from U.S. Bureau of Labor Statistics projections. We do not publish exposure estimates of our own.

Exposure values come from Anthropic Economic Index (CC BY 4.0), OpenAI "GPTs are GPTs" exposure rubric (MIT License), ILO Working Paper 140 (CC BY 4.0), and BLS AI exposure categories (Public domain (17 U.S.C. §105)). Employment, wage and projected-change values come from the U.S. Bureau of Labor Statistics Employment Projections 2025–35. Each figure on the site names its source.

For editorial content and citations we prefer sources in this order: academic peer-reviewed research, then government statistical agencies, think tank reports, corporate research labs, and established media analysis. Where two sources conflict, we follow the higher one. Separately, the set of domains a post may cite at all is fixed in a reviewed allowlist that the database enforces, and each entry in it carries a reliability tier.

Exposure indices describe the state measured when each source dataset was published, not a forecast. AI Changing Work makes no projection of its own; forward-looking figures on the site — such as the BLS employment projections through 2035 — are republished from the publisher that produced them and named where they appear.

Our Coverage

We provide one of the most comprehensive free collections of published AI exposure figures for occupations, with the source named on every page.

  • 1,010 occupations across 14 industry categories, from healthcare to technology, education to construction.
  • Over 1,170 in-depth blog posts providing in-depth analysis of AI automation trends for specific occupations and industries.
  • Available in 11 languages: English, Korean, Hindi, French, Portuguese, Spanish, Arabic, German, Chinese, Japanese, and Bengali - making AI labor market data accessible to workers worldwide.
  • Our data and analysis are updated regularly as new research is published by AI labs, government agencies, and academic institutions.

Editorial Standards

Transparency and accuracy are central to everything we publish.

  • AI Changing Work is published by one person. Heechang Han holds editorial responsibility for everything on this site, and his name appears on every post. A manual approval step exists and has been used for part of what we publish, but we keep no per-post reviewer record, so we do not claim that every item was read line by line before it went out. What is enforced automatically, and can be checked, is narrower: a post may only cite sources from a reviewed allowlist, and the database rejects anything else. The occupation figures shown on this site are reproduced from external datasets rather than produced by us, and each names its source.
  • Our analysis posts use inline markers to separate the kinds of statements they contain — for example [Fact] for a figure reproduced from a named source, [Estimate] for a projection or a number we derived ourselves, and [Claim] for an attributed opinion. Which markers a post uses depends on what it contains, and the convention was adopted after the site launched, so some early posts from March 2026 carry none. Translations keep the markers in the body text rather than stripping them out.
  • Blog analysis carries source citations. Occupation figures carry their source dataset, licence and version on the page itself, so each can be traced back to the publication it came from.
  • We monitor a fixed list of research sources on a daily rotation, and if one of them publishes a revision that changes a figure on this site, we update it. The occupation figures are not fed by an external data source, so they change only when we re-run our own analysis.

About the Team

AI Changing Work is an independent research project, founded in 2026.

Our focus is making AI labor market data accessible to workers worldwide - from software engineers in Silicon Valley to teachers in rural India, from nurses in Germany to accountants in Brazil.

We are not affiliated with any AI company, tech corporation, or lobbying group. Our analysis is independent, and our only obligation is to accuracy and to the workers who use our data to make career decisions.

We believe that information about how AI affects jobs should be free and accessible. That is why all our core data and analysis are available at no cost, in 11 languages.

Contact Us

We welcome questions, feedback, corrections, and partnership inquiries.

Email us at: [email protected]

Found an error in our data? Have a suggestion for improvement? We take accuracy seriously and appreciate every correction.

For research collaborations, media inquiries, or data partnerships, please reach out via email.