MIT and Oak Ridge National Laboratory’s Project Iceberg estimates current AI systems can economically substitute for tasks covering about 11.7% of U.S. wage value. The simulation mapped 32,000 skills across occupations and found AI is technically and economically competitive for a sizable share of work. Researchers including Prasanna Balaprakash built a ‘digital twin’ of the U.S. labor market to model adoption feasibility rather than theoretical exposure. The study flags concentrated near‑term impacts in cognitive and administrative tasks across finance, healthcare and professional services. For higher education, the finding has immediate implications for curriculum design, workforce development, and continuing education: programs must prioritize human‑centered skills, AI fluency, and retraining pathways. Clarification: a digital twin is a computational model that simulates real‑world systems for scenario testing.