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    Home»SEO & Digital Marketing»New AI Jobs Index Ranks 784 Occupations By Loss Risk
    SEO & Digital Marketing

    New AI Jobs Index Ranks 784 Occupations By Loss Risk

    adminBy adminMarch 31, 2026No Comments3 Mins Read
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    New AI Jobs Index Ranks 784 Occupations By Loss Risk
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    Jobs with the highest potential for AI-assisted productivity gains also face the highest projected job losses, according to a new index from Digital Planet at Tufts University’s Fletcher School.

    The American AI Jobs Risk Index ranks 784 U.S. occupations, 530 metro areas, 50 states, and 20 industry sectors by vulnerability to AI-driven job loss.

    All figures are model projections based on AI adoption scenarios, not actual layoffs or employment changes. The median scenario estimates 9.3 million jobs at risk, ranging from 2.7 million to 19.5 million depending on AI adoption speed.

    Which Jobs Face The Highest Projected Risk

    Writers and authors top the list of occupations at risk at 57%. Computer programmers and web and digital interface designers follow at 55% each. Editors are at 54%, and web developers at 46%.

    Market research analysts and marketing specialists face a projected 35% job loss rate. Public relations specialists are at 37%. News analysts, reporters, and journalists face 35% risk.

    Earlier analyses, such as the Anthropic Economic Index and Stanford’s “Canaries in the Coal Mine,” measured how accessible jobs are to AI. This analysis goes further by estimating how likely that exposure is to translate into projected job loss.

    Augmentation & Loss Risk Go Together

    Authors refer to the connection between jobs that benefit from AI-driven productivity gains and those expected to lose jobs as the “augmentation-displacement link.”

    When AI increases individual workers’ efficiency, companies can produce the same output with fewer employees. This mainly affects entry-level and lower-seniority roles first, because companies can cut back on hiring rather than firing.

    Writing, programming, web design, technical writing, and data analysis are where this pattern is most evident. Tasks in these fields are cognitive, language-intensive, and structured enough for large language models to manage.

    By Industry

    Average vulnerability across all industries is about 6%. Sectors with the highest projected job loss are Information (18%), Finance and Insurance (16%), and Professional, Scientific, and Technical Services (16%).

    Software Developers, Management Analysts, and Market Research Analysts face the biggest total income losses. These three roles combine high pay with large workforces, accounting for a significant share of the projected $757 billion in total at-risk annual income.

    What The Analysis Doesn’t Include

    Note that job creation effects aren’t included in this version. The authors intend to add that data in future updates as they gather more evidence.

    Additionally, regulatory constraints, union bargaining power, and occupational licensing requirements that could help slow job losses in some sectors are not part of this analysis. The authors emphasize that their forecasts are based on different scenarios rather than being definitive.

    Why This Matters

    There’s a common assumption among digital professionals that using AI to boost productivity protects their jobs. However, this data challenges that idea.

    SEJ previously covered this tension in 2023 when Dr. Craig Froehle of the University of Cincinnati warned that companies not investing in employee retraining would see turnover costs double. The Tufts data puts numbers on the specific occupations where that pressure is building.

    Looking Ahead

    Updates to the American AI Jobs Risk Index will be made as AI capabilities and labor market conditions evolve. The authors mention that future versions will try to include job creation data along with loss estimates, providing a more complete view of AI’s overall impact on employment.

    The methodology is available on the Digital Planet site, which also links to a data download page.


    Featured Image: rudall30/Shutterstock

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