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The conventional fear about artificial intelligence and jobs runs something like this: the robots are coming for everything, and only the most creative, deeply human work will survive. A new paper by one of the world\u2019s leading economists of automation turns that assumption on its head\u2014and in doing so, arrives at a conclusion that is simultaneously more reassuring and more unsettling than the standard nightmare scenario.<\/p>\n
Pascual Restrepo, an associate professor of economics at Yale University and one of the field\u2019s foremost researchers on automation and labor markets, argues in a working paper published by the National Bureau of Economic Research that most human work won\u2019t be automated in an era of artificial general intelligence. The reason isn\u2019t that AI lacks the capability. It\u2019s that most of what people do for a living simply isn\u2019t important enough to bother replacing.<\/p>\n
\u201cThe model opens up the intriguing possibility that much of today\u2019s work may not be essential for future growth and may never be automated,\u201d Restrepo writes in the paper, titled\u00a0We Won\u2019t Be Missed: Work and Growth in the AGI World. \u201cInstead, compute may be directed toward bottleneck work critical for future progress\u2014such as reducing existential risks, defending against asteroids, or mastering fusion energy\u2014leaving large parts of the labor market unchanged.\u201d<\/p>\n
Not obsolete\u2014just irrelevant<\/p>\n
The main point, he argues, is that fundamentally, \u201cAGI does not render human skills obsolete; it revalues them.\u201d The new scarcity in the economy isn\u2019t skilled labor or intelligence; it\u2019s compute. This means that skills are valued at the opportunity cost of compute required to replicate them. <\/p>\n
\u201cIn fact, if compute and human skill are the only scarce resources, average wages are higher in a post-AGI world. On the other hand, labor\u2019s relative role shrinks.\u201d <\/p>\n
His analysis extends this logic to assume that compute will go to the areas that are most valuable for economic growth, leaving jobs that are less important to be filled by humans.<\/p>\n
Two kinds of work in the AI economy<\/p>\n
The paper draws a sharp distinction between two types of work. \u201cBottleneck\u201d work consists of tasks that are essential for economic growth\u2014things like producing energy, maintaining infrastructure, advancing science, and national security. <\/p>\n
\u201cSupplementary\u201d work, by contrast, is everything the economy can do without and still expand: arts and crafts, customer support, hospitality, design, academic research, even the work of professional economists. In Restrepo\u2019s framework, the economy will eventually automate every bottleneck task using compute\u2014the raw computational resources of AI systems. But supplementary work? AI may simply ignore it.<\/p>\n
That sounds like good news for the baristas and the novelists. Jobs in hospitality, live performance, and socially intensive work could survive largely intact, Restrepo argues, not because of any special human magic, but because the massive computing resources needed to fully replicate them would never justify the expense when AI has bigger problems to solve.<\/p>\n
Crucial bottleneck work, in Restrepo\u2019s telling, is very science-fiction sounding: \u201creducing existential risks, defending against asteroids, or mastering fusion energy.\u201d Socially intensive work, on the other hand will include hospitality, live performances and entertainment: non-essential for future growth, costly to replicate with compute, and thus likely to remain human. \u201cThese domains could continue to offer familiar and meaningful work.\u201d<\/p>\n
Surviving automation is not the same as sharing in growth<\/p>\n
But here is where the paper delivers its more sobering message. Surviving automation and prospering from economic growth are two very different things.<\/p>\n
In an AGI world, Restrepo shows, wages would become decoupled from GDP. Today, as the economy grows, workers tend to share in that growth as wages rise and living standards improve. In the post-AGI economy he models, that link breaks. Once AI systems handle all the tasks essential for growth, economic expansion is driven entirely by adding computational resources. <\/p>\n
Human work, whether essential or supplementary, is valued not by its contribution to growth, but by what it would cost to replace it with compute. That ceiling is, in the long run, a low one.<\/p>\n
Labor\u2019s share of GDP goes to zero<\/p>\n
The paper\u2019s starkest finding is that labor\u2019s share of GDP converges to zero. Total computational resources in the economy could eventually reach 10\u2075\u2074 floating-point operations per second. The computing power of all human brains combined amounts to roughly 10\u00b9\u2078 flops. <\/p>\n
In an economy where wages are anchored to what compute would cost to replicate human work, human labor becomes economically marginal\u2014not worthless, but negligibly small relative to the overall pie. \u201cMost income will accrue to owners of computing resources,\u201d the paper concludes.<\/p>\n
That means the distribution question of who owns the compute becomes the defining political and economic challenge of the AGI era. Already, that question is becoming urgent. BlackRock CEO Larry Fink warned in his closely watched annual letter that AI \u201cthreatens to repeat that pattern at an even larger scale\u2014concentrating wealth among the companies and investors positioned to capture it,\u201d noting that the top 1% of U.S. households now hold more wealth than the bottom 90% and that AI is likely to exacerbate this gap.<\/p>\n
Restrepo notes that in such an economy, \u201cone approach is to redistribute these gains through universal income. Another is to treat compute as a public resource\u2014akin to land or natural capital\u2014and distribute its returns broadly.\u201d<\/p>\n
Two modes of automation<\/p>\n
The paper also makes important distinctions about the path to that future, and not all of them are comforting for workers navigating the transition today. Restrepo identifies two modes of automation. In a \u201ccompute-binding\u201d transition, AI adoption is constrained by available hardware; adjustment is gradual, wages follow continuous paths, and workers have time to reallocate. <\/p>\n
In an \u201calgorithm-binding\u201d transition\u2014the one that looks more like the current moment, with AI capabilities advancing in sudden leaps\u2014the picture is jagged and destabilizing. \u201cInequality may rise sharply: workers whose tasks cannot yet be automated enjoy large temporary wage premiums, while others face sudden wage declines as theirs are,\u201d he writes.<\/p>\n
This bears a strong resemblance to what\u2019s happening in the trades as of 2026, with electricians, plumbers and HVAC technicians commanding strong premiums, especially on data-center construction. Construction workers on data center projects currently earn an average of about $81,800 annually\u2014roughly 32% more than those on non-data center builds\u2014according to data from Skillit, an AI-powered hiring platform. <\/p>\n
Some electricians are pulling in $260,000 a year, with electrical work accounting for an estimated 45% to 70% of total data center construction costs. The U.S. will need roughly 300,000 new electricians over the next decade, in addition to replacing the 200,000 expected to retire.<\/p>\n
We won\u2019t be poorer\u2014but we may not be richer either<\/p>\n
Restrepo does offer one piece of meaningful reassurance: workers as a group are not made worse off by the transition. Because AGI expands what the economy can produce, total labor income in the post-AGI world\u2014across all workers\u2014is higher than in the pre-AGI baseline. <\/p>\n
The arrival of AI cannot make us collectively poorer, the paper argues, because we could always retreat to a no-AI zone and produce exactly as we did before. The fact that we don\u2019t means the new arrangement is better in aggregate. \u201cThe arrival of AGI cannot make us collectively worse off,\u201d Restrepo writes.<\/p>\n
But that collective gain is cold comfort if it is concentrated at the top of the income distribution\u2014among the companies, investors, and nations that own the data centers. <\/p>\n
Indeed, 40% of Americans currently lack meaningful exposure to capital markets, according to Fink. And without structural intervention\u2014he suggests tools like tokenization and expanded retirement investment options\u2014the AI-driven boom will leave them further behind.<\/p>\n
\u2018We Won\u2019t Be Missed\u2019<\/p>\n
The paper\u2019s title, borrowed from its closing argument, captures the existential wager of the AGI economy. \u201cHistorically, work provided not only income but also recognition that one\u2019s efforts improved society\u2019s well-being,\u201d Restrepo writes. \u201cWork gave people the sense that they would be missed. In an AGI world, that connection is severed.\u201d <\/p>\n
Today, he notes, if half the workforce stopped showing up, the economy would collapse. In the AGI world, we would not be missed.<\/p>\n
For Restrepo\u2014whose work with Nobel laureate Daron Acemoglu has shaped the economics profession\u2019s understanding of automation for more than a decade\u2014the message is not one of despair, but of clear-eyed reckoning. The question is not whether AI will take your job. It may be that your job was never important enough for the question to matter.<\/p>\n
For this story,\u00a0Fortune\u00a0journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.<\/p>\n
#Yale #economist #AGI #wont #automate #jobsbecause #theyre #worth #trouble<\/p>\n","protected":false},"excerpt":{"rendered":"
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