2026年的AI：两种叙事的交织

奥KA姆剃刀2025-12-28

2026 年将是数据中心与 AGI 的 “延迟之年”，同时也是终端用户加速采用 AI 的一年。12 月是投资界的复盘期，投资者会总结过往一年的表现，为来年布局。当下这一点尤为明显 —— 我们似乎处于一个过渡阶段：市场热情有所降温，但 AI 公司的业绩仍保持强劲。我对 2026 年的预测是：AI 将呈现两种截然不同的叙事。一方面，这会是 “延迟之年”—— 先是数据中心建设进度滞后，再是 AGI 的...

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EQUITY \"CRH\" (USDHDG) ACC","LU0784383803.USD":"BGF GLOBAL MULTI-ASSET INCOME FUND \"A\" (USD) INC A","LU2237443895.HKD":"abrdn SICAV I -  GLOBAL DYNAMIC DIVIDEND \"A\" (HKD) ACC","LU2506951958.HKD":"BNP PARIBAS SUSTAINABLE GLOBAL LOW VOL EQUITY \"CRH\" (HKDHDG) INC","LU1934455277.USD":"AB SICAV I LOW VOLATILITY TOTAL RETURN EQUITY PORT \"AD\" (USD) INC","BK4528":"SaaS概念"},"translate_title":"AI in 2026: The Interweaving of Two Narratives","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"TSM":0.9,"03145":0.6,"META":0.9,"AMZN":0.9,"MSFT":0.9},"content_text":"2026 年将是数据中心与 AGI 的 “延迟之年”，同时也是终端用户加速采用 AI 的一年。12 月是投资界的复盘期，投资者会总结过往一年的表现，为来年布局。当下这一点尤为明显 —— 我们似乎处于一个过渡阶段：市场热情有所降温，但 AI 公司的业绩仍保持强劲。我对 2026 年的预测是：AI 将呈现两种截然不同的叙事。一方面，这会是 “延迟之年”—— 先是数据中心建设进度滞后，再是 AGI 的落地时间表推迟；另一方面，AI 的普及速度会持续攀升。2025 年，初创企业提出了 “从 0 到 1 亿美元营收” 的 AI 快速扩张企业俱乐部；而 2026 年，我们将开始谈论 “从 0 到 10 亿美元营收” 的俱乐部。进入 2026 年，我看到的现状如下：科技巨头对 AI 资本支出的需求空前旺盛谷歌与 Meta 已押注全部资源在 AI 领域尽管微软与亚马逊 2025 年的投入相对同行略有收缩，但两者仍在积极布局 AI 未来供应链企业略显疲惫：他们客户的客户（终端市场）状况不如预期，担心自己最终积压库存相比数据中心与能源领域未来五年万亿美元级的投资规模，AI 带来的终端收入（每年数百亿美元量级）仍十分有限AI 领域有两大 “杀手级应用”：代码编写与 ChatGPT，两者今年的营收预计将接近或突破 100 亿美元。此外，还有近十家初创企业正迈向年营收超 1 亿美元的目标，覆盖各类应用场景大型企业在内部部署 AI 时遭遇困难，这导致了（对 AI 的）倦怠与失望情绪叙事一：延迟之年这些相互矛盾的力量将在 2026 年碰撞：科技巨头飙升的需求，将与扩张速度不足的供应链正面相遇。首先，台积电、ASML 等企业处于垄断地位，无法被强制扩大产能。本・汤普森将这一现象称为 “台积电刹车”，他在 10 月指出：尽管台积电 2022 年以来营收增长了 50%，但资本支出仅增长了 10%。他进一步解释：“台积电对此没有给出太多答案，这可以理解，毕竟他们要到下一季度才会公布明年的资本支出数据。魏哲家仅表示，台积电不仅会与客户沟通，还会与客户的客户交流。” 结合 Gemini 3 的成功发布与 TPU 的热度，我预测 2026 年台积电的产能限制可能会成为实质性问题。其次，工业领域的参与者（因分散性与缺乏市场影响力常被忽视）可能会在数据中心建设的最后阶段造成瓶颈。发电机与冷却设备是数据中心最重要的工业投入品之一，但类似的投入品多达数十种；只要其中任何一种延迟交付，整体工期就会被推迟。同时还要考虑劳动力限制 —— 技术工人短缺可能成为这些大型建设项目完工的关键瓶颈。许多 AI 公司共享同一供应链，而这些工业供应商也面临着自身的资本支出决策（比如要新建多少工厂）。2026 年我们就能知道，他们是否已充分提升了自身的产能。AI 数据中心的平均建设周期约为两年。如果说 2024 年是新项目公告频出的一年，2025 年是建设投资开始计入 GDP 的一年，那么 2026 年要么是大量新产能投产（带动算力成本进一步下降）的一年，要么是众多建设项目开始延迟的一年。2025 年第四季度已有部分延迟案例被公开报道。如果超大规模企业开始囤积新 AI 芯片、而非直接安装到数据中心，这将是 “延迟时代” 开启的明确信号。2026 年成为 “延迟之年” 的另一个原因，与 AGI 的时间表有关。长期以来，硅谷大佬们预测 AGI 即将到来，“2027 年实现 AGI” 的说法在对话中频繁出现。但自今年 6 月起，这一时间表被逐步推迟。德瓦克什・帕特尔近期对理查德・萨顿、安德里杰・卡帕西、伊利亚・苏茨克维的播客采访，成为了（观点转变的）分界线；新的共识是，AGI 最早也要到 2030 年代才会出现。未来一年，我预计这一 “更新后的认知” 会扩散到硅谷之外。这会带来多方面的影响，其中最显著的风险是：超大规模企业当前的资本支出，最终可能会过时。叙事二：AI普及的持续推进我认为不会出现延迟的领域，是 AI 的普及本身。热度的消退对基本面影响甚微；事实上，最优秀的初创企业正以更快的速度实现从 0 到 1 亿美元的营收增长。2026 年，我们将见证 “从 0 到 10 亿美元营收” 俱乐部的诞生。过去三年（且可能持续更久）的趋势是：初创企业正一步一个脚印地为未来经济奠定基础。许多优秀的创业者在探索新的细分领域，还有大量潜在价值尚未被释放。最顶尖的 AI 初创企业运营效率极高 —— 许多企业的人均营收超过 100 万美元。这意味着（市场）是 “拉动” 而非 “推动” 销售。如今的创业者正在打造 “自我提升” 的公司 —— 他们自身会用 AI 智能体处理法律、招聘、销售等工作，形成生态飞轮效应。AI 应用公司也在受益于算力成本曲线，这将推动边际利润提升，尤其是 2030 年前新数据中心投产后。最后，由于企业在自主部署 AI 时遭遇倦怠，初创企业获得了更强的发展动力。对一些人来说，AI 普及的速度太慢了。那些期待 AI 快速起飞的人，更希望出现一个 “Deus Ex Machina（机械降神）” 式的时刻，直接带我们抵达终点。我认为这个梦想可能会落空。相反，AI 故事的下一阶段需要付出努力、发挥创造力与耐力，才能达到 “AI 彻底重塑经济” 的新阈值。我们只需看看这些萌芽信号 —— 创始人的动力、进取精神、求胜欲、对客户的专注 —— 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