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.