A groundbreaking study from the Massachusetts Institute of Technology has quantified the immediate impact of artificial intelligence on American employment, revealing that technology can already perform work equivalent to 11.7% of the US workforce. This represents approximately $1.2 trillion in wages across crucial sectors including finance, healthcare, and professional services.
The Iceberg Index: Mapping AI's Workforce Impact
The research utilized a sophisticated new analytical tool called the Iceberg Index, developed through collaboration between MIT and Oak Ridge National Laboratory. This innovative system simulates how 151 million US workers interact nationwide and measures how artificial intelligence and government policies might affect them.
Prasanna Balaprakash, ORNL director and co-leader of the research, explained the significance of their approach: "Basically, we are creating a digital twin for the US labour market." ORNL, a Department of Energy research centre in eastern Tennessee, houses the Frontier supercomputer that powers these extensive modelling efforts.
The Iceberg Index provides an unprecedented detailed view of how AI might transform employment landscapes - not just in technology hubs but across all states, down to specific zip code levels. For government officials planning substantial investments in worker retraining and education programs, the index serves as a strategic map identifying where job disruption will most likely occur.
How Researchers Calculated AI's Job Replacement Potential
The methodology behind the Iceberg Index involves running population-level experiments that demonstrate how AI transforms tasks, skills, and labour flows before these changes manifest in the actual economy. The system treats each of the 151 million workers as individual agents, tagging them with specific skills, tasks, occupations, and locations.
Researchers mapped more than 32,000 skills across 923 occupations in 3,000 counties, then measured where current AI systems can already perform these capabilities. Their analysis revealed that the visible portion of layoffs and role changes in technology, computing, and information technology represents just 2.2% of total wage exposure, equivalent to approximately $211 billion.
Beneath this surface lies the substantial total exposure: $1.2 trillion in wages, including routine functions in human resources, logistics, finance, and office administration positions that AI can already handle.
Policy Implications and State-Level Applications
Importantly, the researchers emphasize that the index does not predict when or where jobs will disappear. Instead, it provides policymakers with a structured framework to explore various scenarios before committing real funding and enacting legislation.
The research team partnered with Tennessee, North Carolina, and Utah, using their state labour data to validate the model's accuracy. Tennessee has already referenced the Iceberg Index in its official AI Workforce Action Plan released this month, while Utah is preparing a similar document.
North Carolina state Senator DeAndrea Salvador highlighted the value of accessing local-level details: "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."
The Iceberg Index demonstrates that exposed occupations extend across all 50 states, including inland and rural regions often overlooked in technology impact assessments. As the report notes: "Project Iceberg enables policymakers and business leaders to identify exposure hotspots, prioritise training and infrastructure investments, and test interventions before committing billions to implementation."
This comprehensive analysis arrives as Indian policymakers and business leaders increasingly confront similar automation challenges, making the methodology and findings particularly relevant for understanding potential impacts on India's rapidly evolving job market.
