- MIT report finds 11.7% of the current US workforce could be replaced by AI
- That’s not to say they will be – but their skills can be replicated
- MIT’s study is a great tool for policymakers to target specific populations
A new MIT study indicates 11.7% of the US labor market could currently be replaced by artificial intelligence, representing a loss of $1.2 trillion in wages across sectors like finance and healthcare.
The study bases its figures on the Iceberg Index, a labor simulation tool built jointly between MIT and Oak Ridge National Laboratory, which analyzes 151 million US workers, 923 different occupations and over 32,000 skills.
MIT splits AI’s effects on the US workforce into ‘visible’ impacts, such as tech sector layoffs and role shifts, and ‘hidden’ impacts, such as changes to HR, logistics and administration.
AI job threats
Although ‘visible’ job losses in tech and computing roles are largely concentrated in tech hubs, ‘hidden’ redundancies are much broder geographically, covering all 50 states including rural areas, not just cities.
States such as Delaware, South Dakota, North Carolina and Utah show higher ‘hidden’ exposure than California, which is home to a large concentration of tech firms.
MIT stressed the Iceberg Index isn’t a job loss prediction tool, but rather a tool that helps visualize which tasks AI can already handle. But it’s still proven useful in policymaking, with Tennessee citing Iceberg in its official AI Workforce Action Plan and Utah preparing a similar move.
North Carolina Senator DeAndrea Salvador also praised the index for its county-level detail (it covers about 3,000 US counties), which is helpful for mapping economic impacts on a local scale.
MIT explains that the research can be useful for policymakers to identify exposure hotspots in order to prioritize training, upskills and infrastructure investments. These places can also be good test locations before the US commits to spending billions on workforce programs.
“The Iceberg Index provides measurable intelligence for critical workforce decisions: where to invest in training, which skills to prioritize, how to balance infrastructure with human capital,” the researchers concluded.
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