Real‑time AI Job‑Exposure Index

Create an ongoing index that tracks AI substitution risk and actual reallocation at monthly cadence using a blend of sources: task‑level exposure maps (from models like OpenAI's), scraped company job postings and product announcements, regular short worker surveys, and platform telemetry (e.g., code‑repo edits, API billing signals). The index would separate potential exposure (what AI could do) from realized substitution (what firms and workers actually change) and publish sector, occupation and locality signals suitable for policymakers and labor groups. — A real‑time exposure index would let governments, unions and companies detect and respond to AI job disruption much earlier, turning slow retrospective debates into proactive policy and retraining interventions.