Key takeaways MIT's Iceberg Index finds AI can currently replace 11.7% of the US workforce, representing $1.2 trillion in wages across finance, healthcare, and professional services. The study reveals...
Artificial intelligence can already replace 11.7% of the US labor market, equivalent to $1.2 trillion in wages, according to a study released Wednesday by the Massachusetts Institute of Technology.
The research, conducted using a labor simulation tool called the Iceberg Index, challenges conventional assumptions about the scope and geography of AI-driven workforce disruption.
The findings suggest that AI's impact extends far beyond coastal technology centers, affecting workers across finance, healthcare, and professional services in all 50 states.
The Iceberg Index, developed through a partnership between MIT and Oak Ridge National Laboratory, simulates how 151 million US workers interact with AI systems.
The tool maps more than 32,000 skills across 923 occupations in 3,000 counties nationwide.
"Basically, we are creating a digital twin for the U.S. labor market," said Prasanna Balaprakash, ORNL director and co-leader of the research, in an interview with CNBC.
The index treats each worker as an individual agent, categorized by skills, tasks, occupation, and location.
It then assesses the ability of current AI systems to perform those same tasks, providing a granular view of potential automation down to the zip code level.
The study reveals what researchers call a "substantial measurement gap" in understanding AI's workforce impact.
When analysts only observe current AI adoption, concentrated primarily in computing and technology sectors, AI exposure accounts for just 2.2% of the workforce, or approximately $211 billion in wages. The report refers to this as the "Surface Index."
However, when factoring in AI's potential for automation in administrative, financial, and professional services, the numbers surge to 11.7% of the workforce and $1.2 trillion in wages.
According to the research, routine roles in HR, logistics, finance, and office administration represent a much larger underlying impact than visible tech layoffs.
Tennessee became the first state to act on the findings, incorporating the Iceberg Index into its official AI Workforce Action Plan released in November. Utah and North Carolina are developing similar strategies based on the research.
North Carolina State Senator DeAndrea Salvador, who has worked closely with MIT on the project, highlighted the tool's ability to provide local-level insights.
"One of the things that you can go down to is county-specific data to essentially say, within a certain census block, here are the skills that is currently happening now and then matching those skills with what are the likelihood of them being automated or augmented, and what could that mean in terms of the shifts in the state's GDP in that area, but also in employment," she said to CNBC.
The Iceberg team has built an interactive simulation environment that allows states to experiment with different policy approaches, from adjusting workforce funding and training programs to exploring how changes in technology adoption might affect local employment and GDP.
"Project Iceberg enables policymakers and business leaders to identify exposure hotspots, prioritize training and infrastructure investments, and test interventions before committing billions to implementation," the report states.
Contrary to common assumptions that AI risk concentrates in coastal technology centers, the research shows that automation threats reach across all 50 states, including rural and inland regions.
The study notes that Rust Belt states such as Ohio, Michigan, and Tennessee register modest Surface Index values but substantial Iceberg Index values driven by cognitive work in financial analysis, administrative coordination, and professional services that support manufacturing operations.
Balaprakash, who also serves on the Tennessee Artificial Intelligence Advisory Council, noted that many of Tennessee's core sectors, including healthcare, nuclear energy, manufacturing, and transportation, still depend heavily on physical work, offering some protection from purely digital automation.
The research team emphasizes that the Iceberg Index is not a prediction engine for exactly when jobs will disappear.
Instead, MIT is positioning it as a policy sandbox that allows states to test different intervention scenarios before committing resources to training programs or infrastructure investments.
"It is really aimed towards getting in and starting to try out different scenarios," Salvador said.
The study's findings come as lawmakers across the country prepare billion-dollar reskilling and training investments.
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