MIT study finds AI can already replace 11.7% of U.S. workforce (www.cnbc.com)

MIT and Oak Ridge National Laboratory released the Iceberg Index, an agent-based “digital twin” labor simulation that finds current AI systems could already replace 11.7% of the U.S. workforce — roughly $1.2 trillion in annual wages across finance, health care and professional services. The model treats 151 million workers as individual agents (tagged with skills, tasks, occupation and location), maps more than 32,000 skills across 923 occupations in ~3,000 counties, and measures where present AI can perform those skills. The study emphasizes that visible tech-sector changes (the “tip” of the iceberg) account for only 2.2% of wage exposure (~$211 billion); a much larger, less-noticed wave affects routine HR, logistics, finance and office-administration work. The Iceberg Index is designed as a forward-looking sandbox for policymakers rather than a timing prediction: states can run what-if scenarios, test policy levers (reskilling, funding shifts, adoption rates) and drill down to county or zip-code detail. Tennessee, North Carolina and Utah have validated and used the tool for planning, and researchers stress it exposes risk beyond coastal tech hubs into inland and rural areas. For the AI/ML community, Iceberg highlights concrete task-level substitution patterns and offers a practical framework to evaluate impacts, prioritize workforce investments, and design mitigation or augmentation strategies.