AI systems can already perform tasks equivalent to 11.7% of the U.S. workforce, according to research of the Massachusetts Institute of Technology published Wednesday (November 26).
That’s about $1.2 trillion in wages tied to potentially automatable work in finance, healthcare, and professional services.
The estimate comes from MIT’s new labor analysis tool, the Iceberg Index, developed with Oak Ridge National Laboratory. The platform models how 151 million U.S. workers interact with thousands of AI tools to measure exposure to technical tasks rather than predicting if or when. jobs will be lost.
The study represents the first attempt to map AI capabilities across the entire U.S. labor market at the county level, CNBC reported Wednesday. Tennessee has already incorporated the results into its statewide study. Artificial Intelligence Advisory Council Action Planand Utah is preparing a similar report.
Visible adoption of AI in IT and technology represents only 2.2% of salary value exposure, or approximately $211 billion, according to the report. The remaining exhibit reflects tasks that AI can perform today, even though no employer has automated them. Again.
How the Iceberg Index measures exposure to AI
The Iceberg Index maps AI system capabilities to job skill requirements. Researchers have cataloged more than 13,000 AI tools and aligned them with Bureau of Labor Statistics taxonomies coating 32,000 skills distributed across 923 professions about 3,000 counties.
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The skills of each profession are weighted by importance, automatism and salary value. A skill is considered automatable when there are AI tools that a language model can use to perform this task. Co-responsible for research Prasanna Balaprakash of Oak Ridge National Laboratory described the platform as building a “digital twin for the U.S. job market,” according to the CNBC report.
The index measures exposure, not adoption, labor displacement or policy impacts. Concrete results depend on employer decisions, regulations, job design and the ability to retrain.
Which jobs are most exposed
AI deployment is concentrated in technology professions, which employ around 1.9 million workers. Software engineers, data scientists, and program managers have the highest degree of overlap with existing AI capabilities. Washington leads the nation with 4.2% exposure to tech roles, followed by Virginia with 3.6% and California with 3%.
The broader figure of 11.7% reflects capacity for document processing, financial analysis and routine administrative tasks. The exposure extends to routine functions in human resources, logistics, finance and office administration, CNBC reported.
The study distinguishes between task replacement and task augmentation. Some AI systems can fully automate specific functions, while others assist workers by handling repetitive or poor-judgment components. Many jobs at risk could evolve into hybrid models rather than disappearing.
MIT economist David Author told an audience at MIT AI Conference in March, AI will likely be increase human expertise more frequently than replacing it.
How exposure varies across regions and sectors
The exhibition is not concentrated only in coastal technology hubs. South Dakota, North Carolina, and Utah have higher index values than California or Virginia when administrative and financial sectors are included.
Industrial states also have high exposure to cognitive tasks. Tennessee records 11.6% while Ohio achieves 11.8%, thanks to administrative coordination and professional services integrated into manufacturing supply chains. The study used THE Herfindahl-Hirschman index has examine whether the exposure is concentrated in specific sectors or spreads widely. Northeastern states tend to to show concentrated exposure led by finance and technology, while states in the manufacturing belt show more distributed patterns across logistics, production, administration and services.
MIT researchers also developed an interactive simulation environment that allow States must model policy scenarios, including investments in workforce training and financing, before implementation.
The PYMNTS Intelligence report «No roadmap, no problem: How companies are reinventing the AI workforce” found that readiness levels for AI adoption inside companies vary. In total, 60% of financial directors said their companies are at least somewhat prepared to manage AI-driven change, including 12% who said they are very prepared. Almost everyone else, about 38%, was neutral, indicating uncertainty about their ability to adapt.
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