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2026-06-20 10 浏览 公开

趋势解读:NYU finance professor Damodaran warns an AI crash,提升开发者接入体验

纽约大学金融教授达莫达兰警告AI行业崩溃可能比互联网泡沫更痛苦,质疑商业模式可扩展性,并指出AI投资的高债务风险和对社会的潜在冲击。

SOURCE / 全球热点解读 MIN / 4 ACCESS / 公开 POST / 2026-06-20 20:26:57

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作者:Matthias Bastian 来源站点:the-decoder.com 原贴时间:

原文

Aswath Damodaran, a finance professor at New York University, warns that a potential crash in the AI sector could be more painful than the bursting of the dot-com bubble around 2000. In the podcast "Intangible Economy," he explains that unlike the dot-com era, the AI industry needs massive investments in physical infrastructure and much of it is financed with debt. If a correction hits, the damage wouldn't just fall on shareholders but could ripple out across society. Damodaran also questions whether the AI business model can scale the way people expect. In his view, AI isn't a traditional software business. Costs don't automatically drop toward zero as more users come on board. Every additional use burns compute, similar to how Spotify pays for each stream. Ad That makes economies of scale far weaker than in Netflix's case, which Damodaran contrasts with Spotify: Netflix's high content costs get spread across a growing subscriber base, while Spotify pays per stream. Growth paired with thin margins could actually destroy value. Moreover, there's the risk of price erosion from Chinese competitors like Deepseek . Margins are already low. Ad DEC_D_Incontent-1 Damodaran also warns about the bull case, because the business model would then be about replacing entire jobs, not selling AI as a tool. If AI actually delivers on this promise, "half of white-collar workers" would lose their jobs. "The scary thing is the big stories you tell that can justify AI, if they come true, are going to create some insane costs for society that we better start thinking about right now," Damodaran says. He calls this scenario the "AI fever dream." Ad Damodaran says that he owns five of the seven so-called "Magnificent Seven" stocks, including Amazon, which he's held on and off since 1997. He says he has to accept that these companies are changing at a fundamental level because of their heavy AI investments. Instead of just tracking margins and new business lines, he now also has to analyze capital expenditures and depreciation. For companies that used to be capital-light, that never mattered. These companies grew with minimal capital spending. Now they're building massive factories and infrastructure that will be depreciated over ten years but could be obsolete after five. "I'm not sure they really know what they're getting themselves into," Damodaran says. Ad DEC_D_Incontent-2 Apple's cautious approach looks smarter to him. Many analysts have criticized Apple for not jumping in headfirst, but Damodaran sees it as a strength because "we undervalue restraint in business." Apple can sit back, watch others make mistakes, and learn from them instead of pouring billions into areas where it has no experience, Damodaran says. Ad Subscribe to THE DECODER for ad-free reading, a weekly AI newsletter, our exclusive "AI Radar" frontier report six times a year, full archive access, and access to our comment section.

中文翻译

纽约大学金融学教授阿斯瓦斯·达莫达兰 (Aswath Damodaran) 警告称,人工智能行业的潜在崩溃可能比 2000 年左右互联网泡沫的破裂更痛苦。他在播客“无形经济”中解释说,与互联网时代不同,人工智能行业需要对实体基础设施进行大规模投资,其中大部分是通过债务融资的。如果出现调整,损失不仅会落在股东身上,还会波及整个社会。达莫达兰还质疑人工智能商业模式是否能够按照人们期望的方式扩展。在他看来,人工智能不是传统的软件业务。随着更多用户加入,成本不会自动降至零。每次额外使用都会消耗计算资源,类似于 Spotify 为每次流媒体付费的方式。这使得规模经济远弱于 Netflix 的情况,达莫达兰将其与 Spotify 进行了对比:Netflix 的高内容成本分散在不断增长的用户群中,而 Spotify 则按流付费。增长与微薄的利润相结合实际上可能会破坏价值。此外,还存在来自 Deepseek 等中国竞争对手的价格侵蚀风险。利润率已经很低了。达莫达兰还对牛市情况发出了警告,因为商业模式将是取代整个工作岗位,而不是将人工智能作为工具出售。如果人工智能真的兑现这一承诺,“一半的白领”将失去工作。达莫达兰说:“可怕的是,你所讲述的可以证明人工智能合理性的大故事,如果它们成真,将会给社会带来一些疯狂的成本,我们最好现在就开始考虑这一点。”他将这种场景称为“人工智能狂热之梦”。达莫达兰表示,他拥有七只所谓“七大股票”中的五只,其中包括自 1997 年以来他一直持有的亚马逊。他说,他必须接受这些公司由于大量人工智能投资而正在发生根本性变化。他现在不仅要跟踪利润率和新业务线,还必须分析资本支出和折旧。对于曾经资本较少的公司来说,这从来都不重要。这些公司以最少的资本支出成长。现在他们正在建造大型工厂和基础设施,这些工厂和基础设施将在十年内折旧,但在五年后可能会过时。 “我不确定他们是否真的知道自己将面临什么,”达莫达兰说。苹果公司的谨慎态度在他看来更为明智。许多分析师批评苹果没有率先行动,但达莫达兰认为这是一种优势,因为“我们低估了商业中的克制”。达莫达兰表示,苹果可以袖手旁观,看着别人犯错误,并从中吸取教训,而不是向自己没有经验的领域投入数十亿美元。

核心信息

纽约大学金融教授达莫达兰警告AI行业崩溃可能比互联网泡沫更痛苦,质疑商业模式可扩展性,并指出AI投资的高债务风险和对社会的潜在冲击。

  • AI行业高债务和重资产模式使崩盘风险比互联网泡沫更可怕。
  • 每多一个用户就多一份算力成本,规模经济不如传统软件。
  • 若AI实现替代工作目标,白领失业将引发巨大社会成本。
  • 苹果的谨慎策略优于盲目追投,克制是价值的一部分。
  • 投资者需关注AI巨头资本支出和折旧,而非仅看利润。

详细解读

这是什么信号?

达莫达兰作为全球知名的估值专家,他的警告具有高度权威性。他明确指出AI行业与2000年互联网泡沫的本质区别:AI需要大量实体基础设施投资且依赖债务,一旦崩盘,损失将从股东蔓延至全社会。他还质疑AI的规模经济——由于每次推理都消耗计算资源,成本不会随用户增长下降,这与传统软件截然不同,可能导致增长反而摧毁价值。

为什么重要?

当前市场对AI普遍乐观,达莫达兰从商业模式底层逻辑出发,指出了两个关键风险:一是高固定成本与低边际利润的不可持续,二是可能被中国竞争者(如Deepseek)价格战侵蚀。此外,他警告若AI真正取代白领工作,社会成本将极其高昂。这些观点有助于投资者、创业者和管理者重新审视AI叙事中的泡沫成分。

对谁有价值?

投资者:需警惕Magnificent Seven因AI投资而改变资本结构,折旧加速可能侵蚀利润。AI创业者:应关注单位经济模型,避免陷入“增长但亏损”陷阱。企业高管:苹果的克制策略值得学习,不必盲目跟风AI投资。政策制定者:需提前考虑AI导致的就业替代和社会成本。

可以怎么行动?

  • 投资者:重新评估AI重仓股,关注资本支出与折旧,分散风险。
  • 创业者:设计有可持续毛利的产品,避免纯算力消耗模型。
  • 企业:像苹果一样“坐等”生态成熟,优先将AI作为工具增强而非替代人力。

风险或限制

达莫兰的悲观观点可能低估了AI长期生产力提升的乘数效应,且其自身持有AI巨头股票,观点或有矛盾。另外,基础设施成本可能因技术进步(如更高效芯片)而下降。

信息差价值

信息差价值:绝大多数AI报道聚焦于技术突破和融资新闻,而达莫达兰从财务估值底层逻辑切入,揭示了被忽视的商业模式隐患。对于读者来说,这意味着可以提前识别AI行业“故事”与“财务现实”之间的鸿沟,避免被FOMO情绪裹挟。

业务启发:如果OPC的用户中包含企业家或产品经理,这一信号提示:在构建AI产品时,必须确保单位经济模型(unit economics)成立——不能指望用户规模自然摊薄成本,而应设计高价值场景让用户愿为算力付费,或者通过硬件/算法优化降低边际成本。同时,警惕价格战,差异化是关键。

可沉淀动作:可在OPC内容中新增“商业模式拆解”系列,用同一框架分析其他热门AI公司(如OpenAI、Anthropic)的财务健康度;整理一份“AI投资避坑清单”,帮助读者评估AI公司的资本密集度和债务风险;建立关键词追踪(如“AI泡沫”、“股价修正”),当类似负面信号出现时即时推送深度解读。

参考来源

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