Advanced and affordable artificial intelligence can now handle tasks equivalent to approximately 12% of employment in the United States, as indicated by a recent MIT investigation. This development is expected to escalate the urgency for businesses, employees, and government officials to adapt to swift transformations within commerce and the financial landscape.
TL;DR
- AI can perform tasks equivalent to 11.7% of U.S. employment, costing less than human labor.
- This impacts white-collar sectors like finance, healthcare, and law, not just technical roles.
- MIT's Project Iceberg models the U.S. labor market to assess AI's technical and economic viability.
- Businesses and governments must adapt to AI's growing capabilities and potential workforce shifts.
MIT’s research, written in October but released on Wednesday, estimates that current AI systems could already take over tasks tied to 11.7% of the U.S. Labor market, representing about 151 million workers and roughly 11.7% of total wage value, or around $1.2 trillion in pay. Unlike earlier estimates that focused on theoretical “exposure” to automation, the MIT research focuses on jobs where AI can perform the same tasks at a cost that’s either competitive with or cheaper than human labor.
These discoveries originate from Project Iceberg, an extensive labor simulation created by MIT alongside Oak Ridge National Laboratory, which houses the Frontier supercomputer.
Researchers have developed a model, referred to as a “digital twin of the U.S. Labor market,”, which replicates 151 million laborers as distinct entities, each possessing unique proficiencies, professions, and geographical settings. This system monitors over 32,000 abilities within 923 job categories across 3,000 districts, correlating them with the current capabilities of AI technologies.
“We’re effectively creating a digital twin of the U.S. Labor market,” Prasanna Balaprakash, a director at Oak Ridge National Laboratory and co-leader of the study, told CNBC.
A key caveat
A report from MIT clarifies that the 11.7% figure represents technical capacity and economic viability, rather than an forecast of job displacement on a specific schedule. Furthermore, it points out a disparity between current observable conditions and future potential.
Thus far, AI's integration has primarily focused on technological roles, especially programming, accounting for approximately 2.2% of compensation value, or approximately $211 billion in earnings. However, the study's authors observe that AI can already manage intellectual and clerical duties within the financial, medical, and professional sectors, which collectively account for roughly $1.2 trillion in salaries—around five times the effect currently apparent.
Initial assessments suggest substantial impact within white-collar, information-intensive sectors that were previously thought to be largely immune to automation. Sectors like finance, healthcare administration, human resources, logistics, and professional fields such as law and accounting are among those where current AI technologies, encompassing large language models (LLMs) and other software agents, are capable of performing numerous standard duties. This implies that a considerable portion of the anticipated disruption is concentrated in more conventional administrative and professional positions that have received less public focus during AI discussions.
Concurrently, economists at MIT and elsewhere advise that the potential for AI doesn't inherently guarantee extensive job displacement. Prior research from MIT’s Computer Science and Artificial Intelligence Laboratory indicated that for numerous positions, fully replacing human workers with AI remained too expensive or impractical in the near term, even when the technology was capable of handling the duties. Separate research from MIT Sloan determined that between 2010 and 2023, AI's influence did not result in significant overall job reductions and frequently aligned with accelerated revenue and workforce expansion in companies that adopted it.
The Iceberg Index is not designed to forecast specific layoffs. Instead, it gives policymakers and business leaders a way to stress-test different scenarios before they commit training dollars, infrastructure spending or new regulations. Tennessee, North Carolina and Utah have already begun using the platform to evaluate how AI might reshape their workforces and to inform state-level AI workforce action plans, the MIT report said.
The research highlights that businesses are running out of time to consider AI a concern for the far future. For public administrations, it prompts concrete inquiries regarding how to re-skill employees, assist areas and industries significantly impacted, and modify fiscal and welfare frameworks for an employment landscape where digital programs can already perform a substantial portion of tasks.
For this story, Coins2Day generative AI assisted in creating a preliminary version. A human editor confirmed the data's correctness prior to its release.