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    Home»Money»Why AI hasn’t replaced every ‘automatable’ job — yet
    Money

    Why AI hasn’t replaced every ‘automatable’ job — yet

    Press RoomBy Press RoomMay 27, 2026No Comments4 Mins Read
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    80,000 Hours president Benjamin Todd
    80,000 Hours president Benjamin Todd says AI still cannot automate the messiest parts of many jobs.

    Courtesy of 80,000 Hours

    • AI researchers and tech CEOs predicted AI would replace some jobs by now.
    • 80,000 Hours president Benjamin Todd says many survived because key tasks aren’t yet automatable.
    • Todd said workers should focus less on “safe jobs” and more on “safe skills.”

    Radiologists, software engineers, pilots — AI was supposed to come for them first.

    Yet after nearly 4 years of AI in mainstream society, those roles are still very much alive.

    That’s because AI often automates only part of a job, not the entire role, Benjamin Todd, president of the nonprofit 80,000 Hours, told Business Insider.

    “We should caveat all of this with ‘survived so far,'” Todd told Business Insider.

    AI’s limits

    As AI is spreading across ever more industries, some AI researchers and tech leaders have predicted that the tech could threaten or outright replace some jobs.

    While Anthropic CEO Dario Amodei predicted in March that AI could be writing all of the code in our software in a year, pioneering computer scientist Geoffrey Hinton predicted in 2016 that AI would render radiologists obsolete within five years.

    However, the reality of automation has turned out to be more complicated than many experts predicted, Todd said.

    “I actually think this is what a lot of white-collar jobs are like,” Todd said. “The defined, clean bit is actually a minority of the work, and most of it is this coordination type stuff.”

    Todd pointed to radiologists. A 2013 observational study published in the “Journal of the American College of Radiology” found that radiologists spent just 36.4% of their time interpreting images.

    The remaining time went toward tasks including consulting with physicians, supervising studies, caring for patients, and administrative work — the kind of tasks machines can’t yet fully replicate, Todd said.

    That same pattern is playing out in software engineering, one of the professions AI has disrupted most aggressively so far, as AI tools have taken over coding.

    While hiring for junior software engineers has weakened, Todd said overall employment in the field has still increased since ChatGPT launched.

    Data from tech hiring analytics firm TrueUp showed software engineering job openings at tech companies climbed to more than 67,000 in 2026 — the highest level in more than three years — with listings roughly doubling since mid-2023.

    “I think for software engineers, it’s more the productivity effect,” Todd said. “Most software engineers I know now say they’re just producing a lot more code than they did before.”

    Todd said translators are another example. Even after the rise of Google Translate, translator employment remained slightly up overall from 2023 to 2024, he said, citing an analysis by Virginia University professor Basil Halperin based on Bureau of Labor Statistics Occupational Employment and Wage Statistics data.

    The AI-proof traits

    The real risk, Todd said, comes when AI systems can handle enough of a role to make the worker unnecessary altogether.

    He said wages are also more likely to come under pressure once AI systems can automate a large enough share of a job’s tasks.

    That’s why Todd said people should focus less on “safe jobs” and more on “safe skills.”

    In an updated version of his book “80,000 Hours: How to Have a Fulfilling Career that Does Good,” Todd lays out four characteristics of skills most likely to increase in value in the age of AI: they are hard for AI to do, complement AI systems, produce things society wants much more of, and are difficult for other people to master.

    Todd told Business Insider that the jobs most likely to survive tend to involve work that is “data-poor, long-horizon, messy, and where we want a person in the loop,” such as strategy, long-term research, social coordination, and relationship-heavy work.

    Still, Todd warned the balance could shift quickly if AI systems become capable of handling larger, more autonomous projects.

    “The process takes longer than people expect,” Todd said. “But it really is a matter of degree.”

    Read the original article on Business Insider
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