A new study from MIT that shows that AI might be poised to replace a lot more jobs than what initial estimates might predict. According to researchers, a hidden mass of data reveals that AI is currently capable of taking over 11.7% of the labor market.
The new estimate comes courtesy of a project called The Iceberg Index, which was made through a partnership between MIT and Oak Ridge National Laboratory (ORNL), a federally funded research center in Tennessee. According to its website, the Iceberg Index “simulates an agentic U.S.—a human-AI workforce where 151M+ human workers coordinate with thousands of AI agents.” In simpler terms, the tool is designed to simulate precisely how AI is poised to disrupt the current workforce, down to specific local zip codes.
The Iceberg Index model treats America’s 151 million workers as individual agents, each categorized by their skills, tasks, occupation, and location. In total, it maps more than 32,000 skills and 923 occupations across 3,000 counties. In an interview with CNBC, Prasanna Balaprakash, ORNL director and co-leader of the research, described this as a “digital twin for the U.S. labor market.” Using that base of data, the index analyzes to what extent digital AI tools can already perform certain technical and cognitive tasks, and then produces an estimate of what AI exposure in each area looks like.
Already, state governments in Tennessee, North Carolina, and Utah are using the index to prepare for AI-driven workforce changes. Here are three main takeaways from the study:
AI is more pervasive in the workforce than we think
Perhaps the biggest finding from the study is the discovery of what it calls a “substantial measurement gap” in how we typically think about AI replacing jobs.
According to the report, if analysts only observe current AI adoption, which is mainly concentrated in computing and technology, they’ll find that AI exposure accounts for only about 2.2% of the workforce, or around $211 billion in wage value (the report refers to this as “Surface Index”). But, it says, that’s “only the tip of the iceberg.”
By factoring in variables like AI’s potential for automation in administrative, financial, and professional services, the numbers rise to 11.7% of the workforce and about $1.2 trillion in wages (this calculation is referred to as “Iceberg Index”).
The study’s authors emphasize that these results only represent technical AI exposure, not actual future displacement outcomes. Those depend on how companies, workers, and local governments adapt over time.
The AI takeover is not limited to the coasts
It’s fairly common to assume that the most AI job exposure is concentrated in coastal hubs, where tech companies predominantly gather. But the Iceberg Index shows that AI’s ability to take over work force tasks is distributed much more widely.
Many states across the U.S., the study shows, register small AI impacts when accounting solely for current AI adoption in computing and tech, but much higher values when other variables are taken into consideration.
“Rust Belt states such as Ohio, Michigan, and Tennessee register modest Surface Index values but substantial Iceberg Index values driven by cognitive work—financial analysis, administrative coordination, and professional services—that supports manufacturing operations,” the study reads.
How this data can actually make a difference
Now that MIT and ORNL have successfully established the Iceberg Index, they’re hoping it can be used by local governments to protect workers and economies. Local lawmakers can use the map to source fine-grain insights, like examining a certain city block to see which skill sets are most in use and the likelihood of their automation.
Per CNBC, MIT and ORNL have also built an interactive tool that lets states experiment with different policy levers—like adjusting training programs or shifting workforce dollars—to predict how those changes might affect local employment and gross domestic product.
“The Iceberg Index provides measurable intelligence for critical workforce decisions: where to invest in training, which skills to prioritize, how to balance infrastructure with human capital,” the report reads. “It reveals not only visible disruption in technology sectors but the larger transformation beneath the surface. By measuring exposure before adoption reshapes work, the Index enables states to prepare rather than react—turning AI into a navigable transition.”
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