CAMBRIDGE, Mass.–Artificial intelligence systems can already perform tasks equal to 11.7% of the workforce in the United States, according to new research from the Massachusetts Institute of Technology.
According to the research, that figure represents about $1.2 trillion in wages tied to potentially automatable work across finance, healthcare and professional services.
The findings were released as part of MIT’s new labor analysis tool, the Iceberg Index, which was developed with Oak Ridge National Laboratory. That platform models how 151 million U.S. workers interact with thousands of AI tools to measure technical task exposure rather than forecast whether or when jobs will be eliminated, according to MIT.
The researchers said the study represents the first attempt to map AI capabilities against the entire U.S. labor market at the county level. CNBC reported that Tennessee has already incorporated the findings into its statewide Artificial Intelligence Advisory Council Action Plan, and Utah is preparing a similar report.
The MIT report states that visible AI adoption in computing and technology accounts for just 2.2% of wage value exposure, or roughly $211 billion, while the remaining exposure reflects tasks that AI can perform today, even if no employer has automated them yet.
How The Iceberg Index Works
According to MIT’s researchers, the Iceberg Index maps AI system capabilities onto occupational skill requirements. The researchers said they cataloged more than 13,000 AI tools and aligned them with Bureau of Labor Statistics taxonomies covering 32,000 competencies across 923 occupations in about 3,000 counties.
In addition, each occupation’s skills are weighted by importance, automatability and wage value. MIT defined a skill as being “automatable when AI tools exist that a language model can use to execute that task.”
The Jobs at Risk
Not surprisingly, MIT found AI deployment is concentrated in technology occupations, employing about 1.9 million workers, with software engineers, data scientists and program managers showing the highest degree of overlap with existing AI capabilities.
Areas at Risk
The state of Washington leads the nation with 4.2% exposure in tech roles, followed by Virginia at 3.6% and California at 3%, the MIT research said. In addition, South Dakota, North Carolina and Utah show higher index values than California or Virginia when administrative and financial sectors are included.
According to CNBC, the broader 11.7% figure reflects capability in document processing, financial analysis and routine administrative tasks.
Exposure is not concentrated solely in coastal technology hubs. South Dakota, North Carolina and Utah show higher index values than California or Virginia when administrative and financial sectors are included, MIT said.
Challenges to Industrial States
Industrial states also show high cognitive-task exposure. Tennessee registers 11.6% while Ohio reaches 11.8%, driven by administrative coordination and professional services embedded within manufacturing supply chains, according to the study, which used the Herfindahl-Hirschman Index to examine whether exposure clusters in specific industries or spreads broadly.
Northeastern states tend to show concentrated exposure led by finance and technology, while Manufacturing Belt states display more distributed patterns across logistics, production, administration and services, the researchers said.
Specific Areas Affected
“Exposure extends to routine functions in human resources, logistics, finance and office administration,” CNBC added.
The MIT researchers further said the study distinguishes between task replacement and task augmentation.
“Some AI systems can fully automate specific functions, while others support workers by handling repetitive or low-judgment components,” the researchers said. “Many exposed jobs may shift toward hybrid models rather than vanish.”
