About

Our Mission

AI Workforce Watch is an independent research platform dedicated to providing rigorous, data-driven analysis of how artificial intelligence is reshaping the labor market. Our goal is to equip workers, employers, educators, and policymakers with the evidence they need to navigate workforce transformation responsibly.

We believe that informed decision-making requires transparent, methodologically sound research -- not speculation, hype, or fear. Every assessment we publish is grounded in peer-reviewed studies, government labor data, and verifiable AI capability benchmarks.

Our core commitment is to objectivity. We do not advocate for or against AI adoption. We measure, analyze, and report what the data shows about automation's trajectory and its implications for specific occupations and industries.

How We Work

Our analysis combines task-level occupational decomposition, AI capability assessment, labor market data from the Bureau of Labor Statistics and O*NET, and synthesis of research from institutions including McKinsey Global Institute, the World Economic Forum, Brookings Institution, and Stanford HAI.

Each occupation is evaluated across four dimensions: task composition, current AI capabilities, adoption barriers, and historical precedent. Risk scores are produced on a 0-to-100 scale and updated quarterly as new data becomes available.

For a complete description of our analytical framework, data sources, and scoring methodology, see our Methodology page.

Editorial Independence

AI Workforce Watch operates independently. We do not accept corporate sponsorship, and our research is not funded by any AI company, staffing firm, or industry lobbying group. This independence is essential to producing analysis that serves the public interest rather than commercial agendas.

Our research team draws on expertise in labor economics, machine learning, occupational analysis, and technology policy. All published assessments undergo internal review for methodological rigor, factual accuracy, and analytical balance before publication.

We welcome scrutiny of our work. If you identify an error, a gap in our analysis, or data that contradicts our findings, we want to hear from you. Corrections and updates are published transparently on our blog.

Get in Touch

We welcome inquiries from researchers, journalists, policymakers, and the public. Whether you have a question about our methodology, a suggestion for an occupation to analyze, or a media request, we are available to help.

Visit our Contact page to reach us directly.