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    Home»Sectors»6.1 Million Workers Have the Most to Lose From AI
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    6.1 Million Workers Have the Most to Lose From AI

    Money MechanicsBy Money MechanicsFebruary 20, 2026No Comments2 Mins Read
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    6.1 Million Workers Have the Most to Lose From AI
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    Key Takeaways

    • There are 6.1 million workers in occupations highly exposed to AI and with low ability to find a new job, according to new research.
    • Customer service representatives are among the most at-risk careers with the lowest ability to adapt.
    • Careers least likely to be disrupted by AI include janitors and roofers.

    How likely is it that AI will take your job, and if so, how ready are you to switch careers? For 6.1 million workers, the risk of AI disruption is high and the ability to find a new job is low.

    That’s according to a paper by researchers at the Brookings Institution who measured occupations by how vulnerable they are to AI disruption and how capable the affected workers would be at finding new employment.

    For example, software developers have high exposure to AI and high adaptability, whereas customer service representatives get the short end of the stick in both categories. Dentists have little to fear from AI and high ability to adapt, while janitors are not very adaptable but also not very likely to have their jobs automated. Interpreters and translators were the most likely to have their jobs automated, according to the study.

    What This Means For The Economy

    The Brookings study identifies professions at greatest risk of AI-related job losses, giving individuals and policymakers an idea of which employees may need the most help transitioning to new careers.

    The 6.1 million people in the high-risk, low-adaptability quadrant of the chart are a significant chunk of the workforce, comparable to the 7.3 million people who are already unemployed.

    “These workers tend to be concentrated in clerical and administrative roles, and about 86% are women,” the researchers, led by senior research fellow Sam Manning, wrote in a blog post about their findings. “The combination of employment size, potentially elevated automation impacts, and precarious worker traits highlights occupations where policymakers may benefit from greater visibility into AI’s workforce effects.”



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