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Cailian PressUpdated Oct 25 19:46

Anthropic report projects AI could push US unemployment rate close to 12%, industry disputes the logic

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A report released by Anthropic in September this year projected an extreme scenario: with large-scale AI adoption, by 2030 US GDP would jump sharply, the share of capital income in national income would rise from about 40% to nearly 55%, and the unemployment rate would rise to close to 12%. Macro economist Tom Orlik and others question the logic of this projection, arguing that simultaneous surges in growth and unemployment are unrealistic in economic history. Another economic research team, measuring by the share of tasks in each occupation where AI can play a substantive role, estimates that about 26% of the US labor force (about 45 million people) faces impact, with white-collar positions such as financial practitioners hit first.

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The original text presents the Anthropic report's extreme projection of AI's impact on employment, and also lists economists' doubts about the logic of that projection, so readers can see the basis of both sides of the controversy.

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Anthropic predicts AI could push US unemployment rate close to 12% in extreme scenario, but industry remains divided

Cailianshe Li Ying, Editor Lin Qi 2026-10-23 17:58

①In a September report, Anthropic modeled an extreme scenario: AI could push the US unemployment rate close to 12% by 2030; ②One economic research team estimates that about 26% of the US workforce faces disruption, with white-collar jobs such as financial professionals bearing the brunt; ③However, how much of an impact AI can actually have on employment is still subject to multiple uncertainties, including AI's own capability shortcomings and the direction of policy.

Cailianshe, October 23 (Editor Li Ying) — Anthropic recently modeled that, with the large-scale adoption of AI, the US unemployment rate could approach 12% in an extreme scenario. However, whether this extreme scenario can become reality remains disputed.

According to media reports on October 23 local time, a report released by Anthropic in September this year modeled the impact of AI on the US economy and depicted an extreme scenario: with large-scale AI adoption, by 2030, US GDP would surge, and the share of capital income in national income would rise from about 40% to nearly 55%.

The report noted that in this scenario, the "pie" going to workers would continue to shrink, a large number of jobs would be replaced by AI, and the US unemployment rate would rise to close to 12%.

For reference, the US unemployment rate typically remains around 4% to 5% when the economy is operating normally, while during the Great Depression of the 1930s it was generally above 15%, peaking at about 25% in 1933.

US unemployment rate trend from 2000 to present, source: TradingView

However, the logic of the report's modeling itself has been questioned. Macro economist Tom Orlik and others pointed out that, from the perspective of economic history, simultaneous surges in growth and unemployment are unrealistic. If everyone is unemployed, who will buy the additional output?

Even if the extreme scenario does not necessarily come true, the risk of AI causing mass unemployment still cannot be ignored. According to reports, one relevant economic research team, based on the share of tasks in each occupation where AI can play a substantive role, estimates that about 26% of the US workforce (about 45 million people) faces disruption.

The team estimates that, excluding the Chinese market, the global revenue scale of knowledge-based work is about $30 trillion, which is precisely the market that AI companies, including Anthropic, are competing for.

According to reports, market investors expect Anthropic's annualized revenue to exceed $100 billion by the end of the year. Even if it grows to $1 trillion in the future, that would still be only about 3% of the labor income scale of the aforementioned knowledge-based work. In other words, for AI companies, a large portion of white-collar jobs can still be taken over by AI, and the market space is considerable.

It is worth noting that job replacement does not happen overnight. AI researchers often use the "jagged frontier" to describe the unevenness of model capabilities: AI performs outstandingly in areas such as programming, but is clearly inferior in tasks where results are difficult to verify or that require interaction with the physical world. This capability shortcoming both slows the pace of replacement and limits the profit space of AI companies.

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Cailianshe statement: The content of this article is for reference only and does not constitute investment advice. Investors who act on it do so at their own risk.

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