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AI股回档免惊?大摩120页报告拆解3大疑虑:真正被低估的是「这个」!

2026-09-18 07:20:41 网络 阅读(52)

今年 6 月底以来,全球人工智慧(AI)类股历经一波明显拉回,市场人心浮动,关于「AI 投资热潮是否已见顶」的讨论再度甚嚣尘上。面对这波疑虑,摩根士丹利 (MS-US) 在 7 月 27 日抛出重磅报告《Playing the AI Infrastructure Dip》,厚达 120 页,试图为投资人正本清源。

AI股回档免惊?大摩120页报告拆解3大疑虑:真正被低估的是「这个」!

大摩在报告中开宗明义给出结论:这波回档的根源在于技术面,包括过度拥挤的市场部位开始松动、融资保证金去杠杆,以及动能因子出现反转,而非 AI 基本面出现裂痕。

换句话说,这比较像是一次资金面的「洗牌」,而非产业逻辑被证伪。

该行进一步针对市场上流传的三大悲观论点逐一拆解,并提出一个此前较少被讨论、却可能是当前错价最严重的投资主题:「电力到位时间」。

疑虑一:企业卡 AI 用量预算,会不会拖累云端巨头营收?

近期部分企业开始为员工设下 AI Token 使用量的预算天花板,市场因此担心,这是否代表大型语言模型公司的营收成长动能将明显放缓。

大摩对此不以为然。报告指出,目前企业在 AI Token 上的支出基数其实极低,但投资报酬率却高得惊人。

根据该行对大量企业级 AI 应用场景的研究,平均一次 AI 调用即可替企业省下约 55 美元的人力成本,而透过 AI 代理协作完成一项企业任务,平均成本仅落在 2 至 5 美元之间,投报率超过十倍。

大摩认为,投报率破十倍的工具,早已不是「要不要编列预算」的财务问题,而是攸关企业能否维持竞争力的生存问题,迟迟不导入 AI 能力的公司,未来势必在市场上被拉开差距。

此外,随着 GPU 世代不断演进,资料中心的获利能力将持续垫高,这代表即便 Token 价格大幅下降,云端业者的获利仍能维持甚至改善,需求也将因而进一步释放。

大摩旗下 Intelligence Factory 模型测算,以现行 Blackwell 架构运算的资料中心,销售 Token 的净利率约在 58% 左右;一旦换装下一代 Rubin 与 Feynman 晶片,净利率可望分别攀升至约 80% 与 90%。

这也意味着,云端服务商理论上可在维持相同获利水准的前提下,把 Token 售价下砍约 75%。降价与获利,两者未必互斥。

疑虑二:中国低成本模型「Kimi 时刻」,戳破美系巨头的资本支出神话?

Kimi K3 模型问世后,市场开始重新质疑一个关键前提,即若中国团队能用远低于美国的成本,训练出效能相近的尖端模型,那么美系云端巨头每年动辄逾兆美元的 AI 资本支出,是否面临报酬率被下修的风险?

大摩给出的答案是否定的。报告认为,中美双方在模型训练效率上的竞赛,非但不会削弱市场对算力的需求,反而会强化「供给远远追不上需求」的结构性格局。

报告援引 19 世纪经济学家 William Stanley Jevons 的观察称,蒸汽机经瓦特改良后,燃煤效率大幅提升,但英国的煤炭总消耗量却不减反增,原因正是效率提升让蒸汽机的使用门槛大幅降低,进而被部署到远比过去更多的工厂与矿坑。

这个现象后来被称为「杰文斯悖论」(Jevons Paradox):某项资源的使用效率一旦提高,其总消耗量往往不降反升。

大摩认为,这套逻辑同样适用于当前的 AI 浪潮。运算效率的提升会压低单位 Token 成本,而成本下降则会带动更多应用场景、更多用户与更高的使用频次,最终推升整体运算需求的总量。

报告引用的一组数字凸显了这种供需落差的悬殊程度。Google 高层近期透露,公司未来可能需要每六个月将算力规模翻倍,换算下来相当于五年内成长千倍。

反观供给端,辉达 (NVDA-US) 在 2025 至 2028 年间 AI 晶片销售的年复合成长率约为 140%,即使以此速度外推五年,累计交付的算力也不到 Google 单一客户预估需求的十分之一。

换言之,就算全球最大的晶片供应商用历史最高速度全力生产,也仅能满足单一大客户需求的一小部分。

疑虑三:电力、人力、政治阻力,会不会成为 AI 扩张的硬上限?

即便前两项疑虑不成立,市场仍有第三个担忧:就算需求无虞,物理世界的种种限制,是否会让资料中心的建设速度跟不上需求成长?

大摩将这些现实限制归纳为「3P」,即 People(人力)、Power(电力)、Politics(政治)。

在人力方面,资料中心建设高度仰赖电工、焊工、管线工等技术工种,这些人才目前正处于结构性短缺状态。

在电力方面,部分地区的电网并网排队时间已延长至五至七年,成为资料中心能否如期投运的最大瓶颈。

在政治方面,资料中心的扩张正面临从地方到联邦层级愈趋升高的阻力,风向也正在出现结构性转变。

过去几年,各州政府争相祭出优渥的招商条件吸引资料中心进驻,如今风向已逆转,愈来愈多州开始暂缓、附加条件,甚至直接撤回相关租税优惠。

「减缓资料中心扩张、避免居民电费因基础建设成本而上涨」等议题,也逐渐成为各州州长选战的重要政见,预料将在 11 月的选举中成为选民关注焦点。

与此同时,美国联邦层级也正酝酿建立全国性的「资料中心关税」机制。

美国众议院目前正在审议《纳税人保护法》(Ratepayer Protection Act),要求各州公用事业公司研议设立「大用电户标准」,让资料中心自行负担电网升级的费用。

事实上,早在今年 3 月,亚马逊 (AMZN-US) 、Google(GOOGL-US) 、Meta(META-US) 、微软 (MSFT-US) 、甲骨文 (ORCL-US) 、xAI 等科技巨头已签署白宫发起的《Ratepayer Protection Pledge》,自愿承诺不让一般消费者为资料中心的基建成本买单,而这项法案的用意,正是要把这份自愿承诺正式法制化,实质形成一套全国性的资料中心电力附加费制度。

尽管如此,大摩承认这些疑虑确有其道理,但将其定性为「减速丘」,而非「结构性障碍」。

报告指出,随着部分地区电网并网排队时间拉长至五年以上,加上资料中心承受愈来愈大的「自备电力」压力,现场自行发电正逐渐成为解决问题的核心方案。

真正被低估的机会:「Time to Power」的时间套利空间

大摩在报告中亦针对美国资料中心的电力缺口进行量化测算。

结果显示,2026 至 2028 年间,美国资料中心的电力需求约达 68 吉瓦(GW),扣除目前在建设施的 15 吉瓦与已签约并网容量的 15 吉瓦后,潜在缺口高达 38 吉瓦;而部分地区的电网并网排队时间已长达五至七年。

在此背景下,大摩认为「电力到位时间」(Time to Power)是当前市场定价偏差最严重的投资主题,其逻辑链相当清晰:资料中心的投产进度受限于电力供应→电网并网动辄排队五至七年→凡是能在一至三年内提供电力的替代方案,都具备显著的时间套利价值。

报告点名两条可望加速「解瓶颈」的路径:

  • 其一是比特币矿场,这些业者本身已握有可观的电网并网容量与土地资源,可直接转作资料中心用途,潜在贡献约 10 至 19 吉瓦;
  • 其二是支援快速部署的发电方案,相较于传统电网并网具备一至三年的时间优势,其中天然气涡轮机可贡献约 15 至 20 吉瓦,燃料电池则约 5 至 8 吉瓦。

不过,即使把天然气涡轮机、燃料电池、核电厂直供,以及比特币矿场转型等各种「加速供电」方案,全部纳入机率加权后的测算,中性情境下美国电力缺口仍有约 1 吉瓦;若情势转向悲观,缺口更可能扩大至 11 吉瓦。

大摩由此得出一个关键判断,即对云端巨头而言,眼下真正稀缺的资源已不是资本支出本身,而是「有电可用的实体空间」。

报告认为,市场目前尚未充分反映这类「已具备供电能力的资料中心厂房」业者的价值。

为量化这种低估程度,大摩以传统再生能源购电协议(PPA)作为对照基准进行比较,发现目前这类业者的企业价值对用电瓦数比(EV/Watt)仅落在 2 至 4 美元区间,代表性公司包括 TeraWulf (WULF-US) 、Cipher Mining (CIFR-US) 、Hut 8 Corp(HUT-US) 、Riot Platforms (RIOT-US) 、Applied Digital (APLD-US) 与 Galaxy Digital (GLXY-US) l 等。

相较之下,成熟的资料中心营运商如 Equinix(EQIX-US) 、数位不动产信托 (DLR-US) ,其 EV/Watt 普遍落在 20 至 25 倍之间。

大摩据此给予这批正从比特币挖矿转型至 AI 资料中心的业者 15 倍 EV/Watt 的折价目标估值,代表在其眼中,这个族群仍存在不小的重估空间。

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    "title": "AI股回档免惊?大摩120页报告拆解3大疑虑:真正被低估的是「这个」!",
    "shortTitle": "AI股回档免惊?大摩120页报告拆解3大疑虑:真正被低估的是",
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    "description": "摩根士丹利发布 120 页 AI 基础建设报告,认为近期 AI 概念股回档主要源于技术性修正,而非基本面恶化。报告拆解 AI Token 需求、中国低成本模型、资料中心建设三大疑虑,并指出美国资料中心最大瓶颈已从 GPU 转向电力供应,「T",
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    "content": "<p>今年 6 月底以来,全球人工智慧(AI)类股历经一波明显拉回,市场人心浮动,关于「AI 投资热潮是否已见顶」的讨论再度甚嚣尘上。面对这波疑虑,摩根士丹利 (<a data-symbol-template=\"USS:MS:STOCK:COMMON\" href=\"#\">MS-US</a>) 在 7 月 27 日抛出重磅报告《Playing the AI Infrastructure Dip》,厚达 120 页,试图为投资人正本清源。</p>\n<p style=\"text-align:center;\"><img src=\"https://cimg.cnyes.cool/prod/news/6555942/l/e396c60c92bf127112a92234ef40b321.jpg\" alt=\"AI股回档免惊?大摩120页报告拆解3大疑虑:真正被低估的是「这个」!\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\"></p>\n\n\n<p>大摩在报告中开宗明义给出结论:这波回档的根源在于技术面,包括过度拥挤的市场部位开始松动、融资保证金去杠杆,以及动能因子出现反转,而非 AI 基本面出现裂痕。</p>\n\n<p>换句话说,这比较像是一次资金面的「洗牌」,而非产业逻辑被证伪。</p>\n\n<p>该行进一步针对市场上流传的三大悲观论点逐一拆解,并提出一个此前较少被讨论、却可能是当前错价最严重的投资主题:「电力到位时间」。</p>\n\n<h6>疑虑一:企业卡 AI 用量预算,会不会拖累云端巨头营收?</h6>\n\n<p>近期部分企业开始为员工设下 AI Token 使用量的预算天花板,市场因此担心,这是否代表大型语言模型公司的营收成长动能将明显放缓。</p>\n\n<p>大摩对此不以为然。报告指出,目前企业在 AI Token 上的支出基数其实极低,但投资报酬率却高得惊人。</p>\n\n<p>根据该行对大量企业级 AI 应用场景的研究,平均一次 AI 调用即可替企业省下约 55 美元的人力成本,而透过 AI 代理协作完成一项企业任务,平均成本仅落在 2 至 5 美元之间,投报率超过十倍。</p>\n\n<p>大摩认为,投报率破十倍的工具,早已不是「要不要编列预算」的财务问题,而是攸关企业能否维持竞争力的生存问题,迟迟不导入 AI 能力的公司,未来势必在市场上被拉开差距。</p>\n\n<p>此外,随着 GPU 世代不断演进,资料中心的获利能力将持续垫高,这代表即便 Token 价格大幅下降,云端业者的获利仍能维持甚至改善,需求也将因而进一步释放。</p>\n\n<p>大摩旗下 Intelligence Factory 模型测算,以现行 Blackwell 架构运算的资料中心,销售 Token 的净利率约在 58% 左右;一旦换装下一代 Rubin 与 Feynman 晶片,净利率可望分别攀升至约 80% 与 90%。</p>\n\n<p>这也意味着,云端服务商理论上可在维持相同获利水准的前提下,把 Token 售价下砍约 75%。降价与获利,两者未必互斥。</p>\n\n<h6>疑虑二:中国低成本模型「Kimi 时刻」,戳破美系巨头的资本支出神话?</h6>\n\n<p>Kimi K3 模型问世后,市场开始重新质疑一个关键前提,即若中国团队能用远低于美国的成本,训练出效能相近的尖端模型,那么美系云端巨头每年动辄逾兆美元的 AI 资本支出,是否面临报酬率被下修的风险?</p>\n\n<p>大摩给出的答案是否定的。报告认为,中美双方在模型训练效率上的竞赛,非但不会削弱市场对算力的需求,反而会强化「供给远远追不上需求」的结构性格局。</p>\n\n<p>报告援引 19 世纪经济学家 William Stanley Jevons 的观察称,蒸汽机经瓦特改良后,燃煤效率大幅提升,但英国的煤炭总消耗量却不减反增,原因正是效率提升让蒸汽机的使用门槛大幅降低,进而被部署到远比过去更多的工厂与矿坑。</p>\n\n<p>这个现象后来被称为「杰文斯悖论」(Jevons Paradox):某项资源的使用效率一旦提高,其总消耗量往往不降反升。</p>\n\n<p>大摩认为,这套逻辑同样适用于当前的 AI 浪潮。运算效率的提升会压低单位 Token 成本,而成本下降则会带动更多应用场景、更多用户与更高的使用频次,最终推升整体运算需求的总量。</p>\n\n<p>报告引用的一组数字凸显了这种供需落差的悬殊程度。Google 高层近期透露,公司未来可能需要每六个月将算力规模翻倍,换算下来相当于五年内成长千倍。</p>\n\n<p>反观供给端,辉达 (<a data-symbol-template=\"USS:NVDA:STOCK:COMMON\" href=\"#\">NVDA-US</a>) 在 2025 至 2028 年间 AI 晶片销售的年复合成长率约为 140%,即使以此速度外推五年,累计交付的算力也不到 Google 单一客户预估需求的十分之一。</p>\n\n<p>换言之,就算全球最大的晶片供应商用历史最高速度全力生产,也仅能满足单一大客户需求的一小部分。</p>\n\n<h6>疑虑三:电力、人力、政治阻力,会不会成为 AI 扩张的硬上限?</h6>\n\n<p>即便前两项疑虑不成立,市场仍有第三个担忧:就算需求无虞,物理世界的种种限制,是否会让资料中心的建设速度跟不上需求成长?</p>\n\n<p>大摩将这些现实限制归纳为「3P」,即 People(人力)、Power(电力)、Politics(政治)。</p>\n\n<p>在人力方面,资料中心建设高度仰赖电工、焊工、管线工等技术工种,这些人才目前正处于结构性短缺状态。</p>\n\n<p>在电力方面,部分地区的电网并网排队时间已延长至五至七年,成为资料中心能否如期投运的最大瓶颈。</p>\n\n<p>在政治方面,资料中心的扩张正面临从地方到联邦层级愈趋升高的阻力,风向也正在出现结构性转变。</p>\n\n<p>过去几年,各州政府争相祭出优渥的招商条件吸引资料中心进驻,如今风向已逆转,愈来愈多州开始暂缓、附加条件,甚至直接撤回相关租税优惠。</p>\n\n<p>「减缓资料中心扩张、避免居民电费因基础建设成本而上涨」等议题,也逐渐成为各州州长选战的重要政见,预料将在 11 月的选举中成为选民关注焦点。</p>\n\n<p>与此同时,美国联邦层级也正酝酿建立全国性的「资料中心关税」机制。</p>\n\n<p>美国众议院目前正在审议《纳税人保护法》(Ratepayer Protection Act),要求各州公用事业公司研议设立「大用电户标准」,让资料中心自行负担电网升级的费用。</p>\n\n<p>事实上,早在今年 3 月,亚马逊 (<a data-symbol-template=\"USS:AMZN:STOCK:COMMON\" href=\"#\">AMZN-US</a>) 、Google(<a data-symbol-template=\"USS:GOOGL:STOCK:COMMON\" href=\"#\">GOOGL-US</a>) 、Meta(<a data-symbol-template=\"USS:META:STOCK:COMMON\" href=\"#\">META-US</a>) 、微软 (<a data-symbol-template=\"USS:MSFT:STOCK:COMMON\" href=\"#\">MSFT-US</a>) 、甲骨文 (<a data-symbol-template=\"USS:ORCL:STOCK:COMMON\" href=\"#\">ORCL-US</a>) 、xAI 等科技巨头已签署白宫发起的《Ratepayer Protection Pledge》,自愿承诺不让一般消费者为资料中心的基建成本买单,而这项法案的用意,正是要把这份自愿承诺正式法制化,实质形成一套全国性的资料中心电力附加费制度。</p>\n\n<p>尽管如此,大摩承认这些疑虑确有其道理,但将其定性为「减速丘」,而非「结构性障碍」。</p>\n\n<p>报告指出,随着部分地区电网并网排队时间拉长至五年以上,加上资料中心承受愈来愈大的「自备电力」压力,现场自行发电正逐渐成为解决问题的核心方案。</p>\n\n<h6>真正被低估的机会:「Time to Power」的时间套利空间</h6>\n\n<p>大摩在报告中亦针对美国资料中心的电力缺口进行量化测算。</p>\n\n<p>结果显示,2026 至 2028 年间,美国资料中心的电力需求约达 68 吉瓦(GW),扣除目前在建设施的 15 吉瓦与已签约并网容量的 15 吉瓦后,潜在缺口高达 38 吉瓦;而部分地区的电网并网排队时间已长达五至七年。</p>\n\n<p>在此背景下,大摩认为「电力到位时间」(Time to Power)是当前市场定价偏差最严重的投资主题,其逻辑链相当清晰:资料中心的投产进度受限于电力供应&rarr;电网并网动辄排队五至七年&rarr;凡是能在一至三年内提供电力的替代方案,都具备显著的时间套利价值。</p>\n\n<p>报告点名两条可望加速「解瓶颈」的路径:</p>\n\n<ul>\n<li>其一是比特币矿场,这些业者本身已握有可观的电网并网容量与土地资源,可直接转作资料中心用途,潜在贡献约 10 至 19 吉瓦;</li>\n<li>其二是支援快速部署的发电方案,相较于传统电网并网具备一至三年的时间优势,其中天然气涡轮机可贡献约 15 至 20 吉瓦,燃料电池则约 5 至 8 吉瓦。</li>\n</ul>\n\n<p>不过,即使把天然气涡轮机、燃料电池、核电厂直供,以及比特币矿场转型等各种「加速供电」方案,全部纳入机率加权后的测算,中性情境下美国电力缺口仍有约 1 吉瓦;若情势转向悲观,缺口更可能扩大至 11 吉瓦。</p>\n\n<p>大摩由此得出一个关键判断,即对云端巨头而言,眼下真正稀缺的资源已不是资本支出本身,而是「有电可用的实体空间」。</p>\n\n<p>报告认为,市场目前尚未充分反映这类「已具备供电能力的资料中心厂房」业者的价值。</p>\n\n<p>为量化这种低估程度,大摩以传统再生能源购电协议(PPA)作为对照基准进行比较,发现目前这类业者的企业价值对用电瓦数比(EV/Watt)仅落在 2 至 4 美元区间,代表性公司包括 TeraWulf (<a data-symbol-template=\"USS:WULF:STOCK:COMMON\" href=\"#\">WULF-US</a>) 、Cipher Mining (<a data-symbol-template=\"USS:CIFR:STOCK:COMMON\" href=\"#\">CIFR-US</a>) 、Hut 8 Corp(<a data-symbol-template=\"USS:HUT:STOCK:COMMON\" href=\"#\">HUT-US</a>) 、Riot Platforms (<a data-symbol-template=\"USS:RIOT:STOCK:COMMON\" href=\"#\">RIOT-US</a>) 、Applied Digital (<a data-symbol-template=\"USS:APLD:STOCK:COMMON\" href=\"#\">APLD-US</a>) 与 Galaxy Digital (<a data-symbol-template=\"USS:GLXY:STOCK:COMMON\" href=\"#\">GLXY-US</a>) l 等。</p>\n\n<p>相较之下,成熟的资料中心营运商如 Equinix(<a data-symbol-template=\"USS:EQIX:STOCK:COMMON\" href=\"#\">EQIX-US</a>) 、数位不动产信托 (<a data-symbol-template=\"USS:DLR:STOCK:COMMON\" href=\"#\">DLR-US</a>) ,其 EV/Watt 普遍落在 20 至 25 倍之间。</p>\n\n<p>大摩据此给予这批正从比特币挖矿转型至 AI 资料中心的业者 15 倍 EV/Watt 的折价目标估值,代表在其眼中,这个族群仍存在不小的重估空间。</p>\n<div class=\"related-articles seo-links\">\n  <h4>相关阅读</h4>\n  <ul>\n    <li><a href=\"/new/mg/article-12398.html\" title=\"辉达财报下周揭晓!20季14度「三连胜」股价却连3次收跌 黄仁勋得端更大惊喜\">辉达财报下周揭晓!20季14度「三连胜」股价却连3次收跌 黄仁勋得端更大惊喜</a></li>\n    <li><a href=\"/new/mg/article-16389.html\" title=\"AI资料中心缺电催生「自己发电」潮INNIO拿下美国450MW表后发电大单\">AI资料中心缺电催生「自己发电」潮INNIO拿下美国450MW表后发电大单</a></li>\n    <li><a href=\"/new/mg/article-11251.html\" title=\"〈纽约汇市〉PPI持平缓解Fed升息押注 美元对主要货币涨跌互见\">〈纽约汇市〉PPI持平缓解Fed升息押注 美元对主要货币涨跌互见</a></li>\n    <li><a 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