Global Automation Shock Index (GASI)

The “Global Automation Shock Index (GASI)” isn’t an established metric used by institutions like the UN, IMF, or World Bank. However, the idea behind it is very real: it would measure how strongly automation and AI disrupt labor markets across different countries. In practice, this concept is already partially covered through research by the OECD, World Economic Forum, McKinsey, and the ILO, which analyze job automation risk, industry exposure, and workforce transitions. If a formal GASI were built at a high-level policy standard, it would likely combine several core dimensions: the percentage of jobs vulnerable to automation, the speed of AI and robotics adoption, the flexibility of labor markets, and the strength of retraining and education systems. It would also need to account for economic structure, since countries heavily reliant on routine manufacturing or administrative work tend to face higher disruption risk than those centered on knowledge-intensive or creative industries. In practical terms, such an index wouldn’t just be about predicting job losses, it would function as an early-warning and planning tool. High scores would signal that a country needs faster investment in reskilling, education reform, and social safety nets to manage transition pressures. The goal wouldn’t be to alarm governments, but to help them stay ahead of structural changes in the labor market before those changes turn into widespread economic stress.