This is a research tool that visualizes 342 occupations from the Bureau of Labor Statistics Occupational Outlook Handbook, covering 143M jobs across the US economy. Each rectangle's area is proportional to total employment. Color shows the selected metric — toggle between BLS projected growth outlook, median pay, education requirements, and AI exposure. Click any tile to view its full BLS page. This is not a report, a paper, or a serious economic publication — it is a development tool for exploring BLS data visually.
LLM-powered coloring: The source code includes scrapers, parsers, and a pipeline for writing custom LLM prompts to score and color occupations by any criteria. You write a prompt, the LLM scores each occupation, and the treemap colors accordingly. The "Digital AI Exposure" option is one example — it estimates how much current AI (which is primarily digital) will reshape each occupation. But you could write a different prompt for any question — e.g. exposure to humanoid robotics, offshoring risk, climate impact — and re-run the pipeline to get a different coloring.
Caveat on Digital AI Exposure scores: These are rough LLM estimates, not rigorous predictions. A high score does not predict the job will disappear. Software developers score 9/10 because AI is transforming their work — but demand for software could easily grow as each developer becomes more productive. The score does not account for demand elasticity, latent demand, regulatory barriers, or social preferences for human workers. Many high-exposure jobs will be reshaped, not replaced.
AI Opportunity layers: To complement the exposure view, three positive-framing layers are available. AI Advantage (0–10) measures how much a worker can amplify their productivity by adopting AI tools. AI Growth (0–10) measures how much AI will expand demand or create new roles for an occupation. AI Opportunity is the composite average of Advantage and Growth. Green = high opportunity.