If AI creates more jobs than it kills, who should pay for the road between them?
McKinsey projects AI will remove about 36 million US jobs by 2035 while creating about 41 million, but only about one in seven of the workers who must change occupations has a direct path into a growing one. If the jobs exist but the route to them requires months or years of retraining and credentials, who should carry the cost of that transition: the worker, the employer, or the public?
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The October 4, 2026 episode of Minds, Bodies, and Terawatts dug into a new McKinsey Global Institute report, covered by Fortune, that sounds like good news until you read the fine print. The net job count is positive, but about 11 million workers would have to leave their line of work entirely, and nearly half of them face what McKinsey calls an unpaved road: big skill gaps, a long wait for a credential, or lower pay at the end. The episode’s point is that the jobs going out and the jobs coming in belong to different people, and the ones with the longest road are the least able to afford the trip. That turns the debate from whether there will be enough work into who funds the time it takes a cashier to become a healthcare worker. Give the episode a listen and tell us where you land: is this a retraining problem, an income-support problem, or something else?
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