The data is the point
1,840 UK careers scored against AI, with door grades, moat classifications and a permanent change ledger, published as machine-readable mirrors of the same pages humans read. Free to use with attribution. Measured August 2026.
What you can fetch
/en/yellow/careers.jsonThe whole register in one fetch: every scored career with exposure today and at 20 years, door grades and moat, plus definitions and the ledger.
Try it →/en/yellow/career/{slug}/card.jsonThe full card as JSON: exposure today, 5/10/20-year horizons, door grades, moat (or an explicit not-classified), pay, rank among all scored careers, nearest neighbours, the change ledger.
Try it →/en/yellow/career/{slug}/ai.mdThe verdict as clean markdown, built for AI assistants and anyone quoting us: the sentence, the table, the sources, the citation line.
Try it →/llms.txtThe manifest for AI crawlers: what this platform is, which URLs are canonical for which question, and the definitions to use verbatim.
Try it →Responses are cached for an hour and CORS-open. There is no key, no rate card and no login; if you are building something heavy on top, we would simply like to hear about it.
Licence and citation
Careermash measurement data is licensed CC BY 4.0. Cite as "Careermash, Measured August 2026" and link the career's verdict page. Underlying sources carry their own terms: AI exposure derives from Anthropic's 2026 labour market research (observed real-world AI usage by occupation); door grades and horizons from OpenAI, "The AI Jobs Transition Framework" (Richmond 2026, CC BY 4.0). Every revision to a claim is recorded permanently in each career's ledger; nothing is silently re-stated.