Massachusetts Institute of Technology on Wednesday released a study that found that artificial intelligence can already replace 11.7% of the U.S. labor market, or as much as $1.2 trillion in wages across finance, health care and professional services.
The study was conducted using a labor simulation tool called the Iceberg Index, which was created by MIT and Oak Ridge National Laboratory. The index simulates how 151 million U.S. workers interact across the country and how they are affected by AI and corresponding policy.
The Iceberg Index, which was announced earlier this year, offers a forward-looking view of how AI may reshape the labor market, not just in coastal tech hubs but across every state in the country. For lawmakers preparing billion-dollar reskilling and training investments, the index offers a detailed map of where disruption is forming down to the zip code.
“Basically, we are creating a digital twin for the U.S. labor market,” said Prasanna Balaprakash, ORNL director and co-leader of the research. ORNL is a Department of Energy research center in eastern Tennessee, home to the Frontier supercomputer, which powers many large-scale modeling efforts.
The index runs population-level experiments, revealing how AI reshapes tasks, skills and labor flows long before those changes show up in the real economy, Balaprakash said.
The index treats the 151 million workers as individual agents, each tagged with skills, tasks, occupation and location. It maps more than 32,000 skills across 923 occupations in 3,000 counties, then measures where current AI systems can already perform those skills.
What the researchers found is that the visible tip of the iceberg — the layoffs and role shifts in tech, computing and information technology — represents just 2.2% of total wage exposure, or about $211 billion. Beneath the surface lies the total exposure, the $1.2 trillion in wages, and that includes routine functions in human resources, logistics, finance, and office administration. Those are areas sometimes overlooked in automation forecasts.
The index is not a prediction engine about exactly when or where jobs will be lost, the researchers said. Instead, it’s meant to give a skills-centered snapshot of what today’s AI systems can already do, and give policymakers a structured way to explore what-if scenarios before they commit real money and legislation.
The researchers partnered with state governments to run proactive simulations. Tennessee, North Carolina and Utah helped validate the model using their own labor data and have begun building policy scenarios using the platform.
Tennessee moved first, citing the Iceberg Index in its official AI Workforce Action Plan released this month. Utah state leaders are preparing to release a similar report based on Iceberg’s modeling.
North Carolina state Sen. DeAndrea Salvador, who has worked closely with MIT on the project, said what drew her to the research is how it surfaces effects that traditional tools miss. She added that one of the most useful features is the ability to drill down to local detail.
“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.
Salvador said that kind of simulation work is especially valuable as states stand up overlapping AI task forces and working groups.
The Iceberg Index also challenges a common assumption about AI risk — that it will stay confined to tech roles in coastal hubs. The index’s simulations show exposed occupations spread across all 50 states, including inland and rural regions that are often left out of the AI conversation.
To address that gap, the Iceberg team has built an interactive simulation environment that allows states to experiment with different policy levers — from shifting workforce dollars and tweaking training programs to exploring how changes in technology adoption might affect local employment and gross domestic product.
“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 says.
Balaprakash, who also serves on the Tennessee Artificial Intelligence Advisory Council, shared state-specific findings with the governor’s team and the state’s AI director. He said many of Tennessee’s core sectors — health care, nuclear energy, manufacturing and transportation — still depend heavily on physical work, which offers some insulation from purely digital automation. The question, he said, is how to use new technologies such as robotics and AI assistants to strengthen those industries rather than hollow them out.
For now, the team is positioning Iceberg not as a finished product but as a sandbox that states can use to prepare for AI’s impact on their workforces.
“It is really aimed towards getting in and starting to try out different scenarios,” Salvador said.
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