
人工智能革命正在改寫美國經濟的規則,但它并未帶來消費繁榮的黃金時代,而是引發了一場規模巨大、資源密集的基礎設施建設熱潮。在這場熱潮中,普通勞動者有可能被時代拋在身后。
根據摩根士丹利財富管理公司最新發布的一份戰略報告,市場已進入一個“由生成式人工智能資本支出驅動”的時代,體現從消費主導型增長轉向投資主導型的“再工業化復興”。重要的是,這種變化這與以往的技術革命(如互聯網、個人電腦或移動設備)都截然不同。
摩根士丹利財富管理公司首席投資官麗莎·沙萊特表示,當前的生成式人工智能浪潮“顯然還不是以消費者為中心”。相反,這一過程深深扎根于物理世界,以支持龐大的計算需求。
沙萊特的團隊指出,與數據中心相關的投資在2025年已占年度GDP增長的25%,并且正在以預測實際GDP增長率數倍的速度擴張。這種巨大的規模需要數萬億美元的投資,這些投資將波及實體市場,直接影響房地產、建筑、電力以及工業金屬。該公司認為,這種趨勢正在催生出一個長達數年的建設期,在此期間,“在經濟再平衡過程中,投資取代消費,成為增長驅動力”。
對人類并非利好
盡管這種基礎設施建設對工業指標來說是個利好,對人類卻意味著黯淡的前景。摩根士丹利警告稱,生成式人工智能的普及將給“勞動力市場帶來轉型風險”。
該報告認為美國消費市場的前景終將歸于“平平淡淡”,并受到“情緒低落、就業焦慮、3.6%的低儲蓄率以及不斷上升的債務和信貸違約”等因素制約。此外,該公司預測,由于就業市場低迷、人口老齡化和人口增長緩慢,消費增長可能會停滯,導致民眾陷入加劇不平等的"K型經濟"之中,而不是V型或U型復蘇。
有趣的是,這種新模式也迫使科技巨頭們面對嚴峻的現實。多年來,美國股指一直被“輕資產、經常性收入的科技商業模式”所主導,這些模式享受著近乎為零的邊際成本和不斷擴大的利潤率。然而,生成式人工智能革命從根本上就不同。它是一場"資金饑渴的研發軍備競賽",其經濟學核心是邊際成本。這意味著,隨著科技公司增加注冊用戶,它們必須為寶貴的"算力"能力投入巨額資金。
因此,這些昔日的輕資產寵兒正在轉變為“資本密集型、現金饑渴的企業”。摩根士丹利直言不諱地指出,對于這些超大規模企業而言,“那個基于看似永遠增長的利潤率來數倍擴大估值的時代,很可能已經結束”。
美國銀行研究部的首席股票策略師薩維塔·薩勃拉曼尼安也就科技行業背離輕資產模式發出了類似警告,而硅谷的高管們正逐漸意識到,人工智能可能終結了科技行業的利潤盛宴,甚至自動化了大部分的編碼工作。
最終,摩根士丹利對2026年及未來的展望描繪了一幅深刻的經濟重構圖景。生成式人工智能革命可能不會帶來一個消費市場烏托邦,但它正在推動一場由資本支出驅動的全球基礎設施建設熱潮。這是一個重型機械、電網和數據中心占據主導地位的時代,從根本上來看,至少就目前而言,人工智能的繁榮對計算機的好處遠大于對人類的好處。(財富中文網)
撰寫本報道時,《財富》雜志記者使用生成式AI作為研究工具。編輯在發布前核實了信息的準確性。
譯者:珠珠
人工智能革命正在改寫美國經濟的規則,但它并未帶來消費繁榮的黃金時代,而是引發了一場規模巨大、資源密集的基礎設施建設熱潮。在這場熱潮中,普通勞動者有可能被時代拋在身后。
根據摩根士丹利財富管理公司最新發布的一份戰略報告,市場已進入一個“由生成式人工智能資本支出驅動”的時代,體現從消費主導型增長轉向投資主導型的“再工業化復興”。重要的是,這種變化這與以往的技術革命(如互聯網、個人電腦或移動設備)都截然不同。
摩根士丹利財富管理公司首席投資官麗莎·沙萊特表示,當前的生成式人工智能浪潮“顯然還不是以消費者為中心”。相反,這一過程深深扎根于物理世界,以支持龐大的計算需求。
沙萊特的團隊指出,與數據中心相關的投資在2025年已占年度GDP增長的25%,并且正在以預測實際GDP增長率數倍的速度擴張。這種巨大的規模需要數萬億美元的投資,這些投資將波及實體市場,直接影響房地產、建筑、電力以及工業金屬。該公司認為,這種趨勢正在催生出一個長達數年的建設期,在此期間,“在經濟再平衡過程中,投資取代消費,成為增長驅動力”。
對人類并非利好
盡管這種基礎設施建設對工業指標來說是個利好,對人類卻意味著黯淡的前景。摩根士丹利警告稱,生成式人工智能的普及將給“勞動力市場帶來轉型風險”。
該報告認為美國消費市場的前景終將歸于“平平淡淡”,并受到“情緒低落、就業焦慮、3.6%的低儲蓄率以及不斷上升的債務和信貸違約”等因素制約。此外,該公司預測,由于就業市場低迷、人口老齡化和人口增長緩慢,消費增長可能會停滯,導致民眾陷入加劇不平等的"K型經濟"之中,而不是V型或U型復蘇。
有趣的是,這種新模式也迫使科技巨頭們面對嚴峻的現實。多年來,美國股指一直被“輕資產、經常性收入的科技商業模式”所主導,這些模式享受著近乎為零的邊際成本和不斷擴大的利潤率。然而,生成式人工智能革命從根本上就不同。它是一場"資金饑渴的研發軍備競賽",其經濟學核心是邊際成本。這意味著,隨著科技公司增加注冊用戶,它們必須為寶貴的"算力"能力投入巨額資金。
因此,這些昔日的輕資產寵兒正在轉變為“資本密集型、現金饑渴的企業”。摩根士丹利直言不諱地指出,對于這些超大規模企業而言,“那個基于看似永遠增長的利潤率來數倍擴大估值的時代,很可能已經結束”。
美國銀行研究部的首席股票策略師薩維塔·薩勃拉曼尼安也就科技行業背離輕資產模式發出了類似警告,而硅谷的高管們正逐漸意識到,人工智能可能終結了科技行業的利潤盛宴,甚至自動化了大部分的編碼工作。
最終,摩根士丹利對2026年及未來的展望描繪了一幅深刻的經濟重構圖景。生成式人工智能革命可能不會帶來一個消費市場烏托邦,但它正在推動一場由資本支出驅動的全球基礎設施建設熱潮。這是一個重型機械、電網和數據中心占據主導地位的時代,從根本上來看,至少就目前而言,人工智能的繁榮對計算機的好處遠大于對人類的好處。(財富中文網)
撰寫本報道時,《財富》雜志記者使用生成式AI作為研究工具。編輯在發布前核實了信息的準確性。
譯者:珠珠
The artificial intelligence revolution is rewriting the rules of the American economy, but rather than ushering in a golden age of consumer prosperity, it is sparking a massive, resource-heavy infrastructure boom that could leave the everyday worker behind.
According to a newly released strategic report from Morgan Stanley Wealth Management, the market has entered a “gen-AI-capex-powered” era that represents a rare shift away from consumption-led growth and toward an investment-led “reindustrialization renaissance.” The catch is it’s very unlike previous technological revolutions—such as the internet, personal computers, or mobile devices.
The current generative AI wave is “not obviously consumer-centric yet,” according to Lisa Shalett, chief investment officer for Morgan Stanley Wealth Management. Instead, the build-out is deeply rooted in the physical world to support massive computing needs.
Shalett’s team noted data-center-related investment already accounted for a staggering 25% of annual GDP growth in 2025, and is expanding at a pace that is multiples of forecasted real GDP growth. This immense scale requires trillions of dollars of investment that will ripple through physical markets, directly impacting real estate, construction, power and electricity generation, and industrial metals. The firm argues this dynamic is catalyzing a multiyear period in which “investment dominates consumption as the growth driver amid economic rebalancing.”
About those humans
While this infrastructure build-out is a boon for industrial metrics, the outlook for humans is markedly less rosy. Morgan Stanley warns of “transformational risks to the labor market” brought on by the gen AI diffusion.
The report describes prospects for the U.S. consumer as ultimately “unremarkable,” weighed down by “depressed sentiment, job anxiety, a low 3.6% savings rate, and rising indebtedness and credit delinquencies.” Furthermore, the firm predicts consumption growth will likely stall owing to a lackluster job market, aging demographics, and slow population growth, leaving the populace trapped within “K-shaped economic dynamics” that exacerbate inequality, referencing the meme over the past five years that leaped from finance Twitter and into reality, with the wealthy and working class representing branching lines on the “K,” rather than a “V-shaped” or “U-shaped” financial recovery.
Interestingly, this new paradigm is also forcing a harsh reality check on tech titans. For years, U.S. indexes have been dominated by “asset-light, recurring-revenue tech business models” that enjoyed near-zero marginal costs and ever-expanding margins. However, the gen AI revolution is fundamentally different. It is a “cash-hungry R&D arms race” with marginal-cost economics, meaning as tech companies add subscribers, they must simultaneously spend vastly more on precious “compute” capacity.
Consequently, these former asset-light darlings are transforming into “capital-intensive, cash-flow-hungry businesses.” Morgan Stanley bluntly states that for these hyperscalers, “the era of multiple expansion based on seemingly ever-expanding profit margins is likely over.”
Bank of America Research chief equity strategist Savita Subramanian has sounded similar alarms about tech’s move away from an asset-light model, while Silicon Valley executives are waking up to the fact AI may have ended the tech industry’s profit gravy train, and even automated most coding work.
Ultimately, Morgan Stanley’s vision of 2026 and beyond is one of profound economic realignment. The gen AI revolution may not be delivering a consumer utopia, but it is fueling a global, capex-driven infrastructure boom. It is an era in which heavy machinery, power grids, and data centers reign supreme, fundamentally suggesting that, at least for now, the AI boom is far better for computers than it is for humans.
For this story, Fortune journalists used generative AI as a research tool. An editor verified the accuracy of the information before publishing.