A new study from the Massachusetts Institute of Technology reveals that artificial intelligence is already capable of replacing 11.7% of the U.S. workforce, equivalent to about $1.2 trillion in annual wages. The findings span key sectors including finance, healthcare, and professional services, highlighting that AI’s impact extends far beyond tech hubs and into routine roles across the country. The research, conducted using a sophisticated labor simulation tool called the Iceberg Index, was developed by MIT in collaboration with Oak Ridge National Laboratory (ORNL). The index functions as a digital twin of the U.S. labor market, modeling the behavior of 151 million workers across 3,000 counties. Each worker is represented as an individual agent with specific skills, job tasks, occupation, and geographic location. The system maps over 32,000 distinct skills across 923 occupations, assessing which tasks today’s AI systems can already perform. The study shows that while only 2.2% of total wage exposure—around $211 billion—is tied to visible automation in tech and computing roles, the broader impact reaches $1.2 trillion. This hidden layer includes administrative, HR, logistics, and office support functions, often overlooked in traditional automation forecasts. Importantly, the Iceberg Index does not predict exact job losses or timelines. Instead, it provides a skills-based snapshot of current AI capabilities, enabling policymakers to explore hypothetical scenarios before investing in training programs or legislation. States including Tennessee, North Carolina, and Utah have partnered with the research team to validate and apply the model. Tennessee has already incorporated the Iceberg Index into its official AI Workforce Action Plan. Utah is preparing a similar report, while North Carolina Senator DeAndrea Salvador praised the tool for revealing localized impacts that traditional models miss. She emphasized the ability to drill down to the county or census block level, allowing for precise assessments of automation risk and its potential effect on local GDP and employment. The index also challenges the myth that AI disruption will be limited to coastal tech centers. Simulations show that exposed occupations are widespread, including in rural and inland communities often excluded from AI discussions. The Iceberg team has built an interactive platform where states can test policy interventions—such as adjusting workforce training budgets, redesigning education programs, or modeling different rates of AI adoption—to see how they affect employment and economic output. Prasanna Balaprakash, ORNL director and co-leader of the project, noted that while sectors like healthcare, nuclear energy, manufacturing, and transportation in Tennessee remain largely tied to physical labor and are less vulnerable to full automation, the real opportunity lies in using AI and robotics to enhance, not replace, these industries. The Iceberg Index is not a final product but a living tool—a sandbox for states to experiment, plan, and prepare. As AI reshapes the economy, the goal is to help leaders act proactively, using data-driven insights to build resilient, future-ready workforces.