MIT researchers have created the Iceberg Index, a predictive tool that quantifies AI’s impact on the U.S. labor market, estimating disruption at about 11.7% of jobs and roughly $1.2 trillion in wages.

The study suggests AI can cost-effectively replace 11.7% of the workforce immediately, equivalent to around 19 million workers, due to favorable AI economics relative to human wages.

Project Iceberg, developed with Oak Ridge National Laboratory, uses a digital twin of 151 million workers and 32,000 skills across 923 occupations in 3,000 counties to simulate AI impact.

The analysis highlights implications for founders, VCs, and AI professionals to adapt, identify hidden automation exposure, and pursue responsible AI development and deployment.

Observations note practices like silent layoffs and non-replacement of retirees to shrink headcount, potentially narrowing the entry-level pipeline over time.

The project offers an interactive simulation for policymakers and business leaders to test retraining investments and infrastructure changes before committing resources.

Entry-level and routine cognitive tasks are primary targets, threatening traditional apprenticeship paths and the training ground for higher-skilled roles.

Collaboration with local governments, including input from North Carolina state Senator DeAndrea Salvador, feeds labor data and enables county- and state-level scenario testing.

State officials aim to use Iceberg to identify exposure hotspots, prioritize training, and explore policy levers to support critical industries like healthcare, manufacturing, and transportation.

AI agents are increasingly able to autonomously execute workflows and use tools, moving beyond chat interfaces to full task execution without human prompts.

Displacement is most pronounced in professional services, finance, and healthcare administration, with automation enabling higher throughput and margin recovery.

Researchers caution that the model does not predict exact outcomes but is designed to inform proactive policy testing for reskilling and infrastructure investments.