Summarized by Gemini

The study you are referring to was released in late November 2025. It is titled “The Iceberg Index: Measuring Workforce Exposure in the AI Economy.” It was conducted by researchers from MIT and Oak Ridge National Laboratory (ORNL). Here are the key details from the study regarding that “more than ten percent” figure:

• The Statistic: The study found that existing AI systems (as of late 2025) already have the technical capability to perform the tasks of approximately 11.7% of the U.S. workforce.
• Economic Impact: This 11.7% equates to roughly $1.2 trillion in annual wages and affects about 17.7 million jobs.
• The “Iceberg” Metaphor: The study is named “The Iceberg Index” because the researchers argue that visible AI adoption in tech roles (like coding) is just the “tip of the iceberg” (about 2.2%). The larger, hidden mass of the iceberg (the other ~9.5%) consists of routine cognitive and administrative work in other sectors that is already technically automated but not yet fully visible in layout stats.
• Sectors Affected: Unlike previous waves of automation that hit blue-collar work, this study highlights that the jobs most exposed are in finance, healthcare, and professional services. It specifically notes that entry-level pathways in these fields are collapsing as AI takes over the “junior” tasks (like drafting documents or basic data analysis) that used to train new employees. Why it is different from previous studies: Earlier MIT studies (like one from early 2024) focused on economic feasibility (i.e., it might be possible to use AI, but it’s too expensive). This new 2025 study focuses on technical capacity—meaning the AI can do the work right now, and for many of these roles, it is already cost-competitive.

https://www.csail.mit.edu/news/rethinking-ais-impact-mit-csail-study-reveals-economic-limits-job-automation?hl=en-US#%3A~%3Atext=This+important+result+commands+a%2Cthe+barriers+are+too+high.”