当所有人都在抛售软件股，汇丰说你们错了

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撰文：宇宙波鸣人，深潮 TechFlow2026 年 2 月，科技股市场正在经历一场被部分媒体称为 “SaaSpocalypse” （SaaS 末日）的系统性崩盘。Salesforce 股价从 2025 年高点跌去近 40%；ServiceNow 单季财报发布后单日暴跌超 11%，原因不过是管理层在电话会上提了一句“AI 智能体正在使席位增长的能见度变得复杂”；Workday 跌超 22%；整个 ...

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wrong","themeId":null,"isJumpTheme":false,"ttsUrl":null,"symbols_score_info":{"ORCU":0.6,"ORCL":1.86,"CRM":1.88,"ORCS":0.6,"ORCX":0.6,"HSBC":1.95,"00005":1.95,"HSBH":0.6,"MSFT":0.9},"content_text":"撰文：宇宙波鸣人，深潮 TechFlow2026 年 2 月，科技股市场正在经历一场被部分媒体称为 “SaaSpocalypse” （SaaS 末日）的系统性崩盘。Salesforce 股价从 2025 年高点跌去近 40%；ServiceNow 单季财报发布后单日暴跌超 11%，原因不过是管理层在电话会上提了一句“AI 智能体正在使席位增长的能见度变得复杂”；Workday 跌超 22%；整个 S&P 500 软件与服务指数在 2026 年开年六周内蒸发了近 1 万亿美元市值。市场的逻辑很直接：AI 智能体（Agent）已经能够替代大量人工操作，企业用 AI 做完了过去需要 100 个人完成的工作，自然就不再需要 100 个软件席位。按席位收费的 SaaS 商业模式，被认为已经走到了历史的终点。就在这场恐慌交易席卷整个行业的时候，汇丰银行美国科技研究主管 Stephen Bersey 发布了一份标题极具挑衅性的研究报告：《软件将吞噬 AI》（Software Will Eat AI）。他的核心观点，用一句话概括：市场的恐慌，是一场误判。逆势而来的报告“市场担忧 AI 将取代企业软件，这种担忧是错误的。”他在报告开篇写道。在他看来，AI 不会消灭软件，而是会被软件所吸收，成为嵌入在企业软件平台之内的能力层。软件不是 AI 的对手，软件是 AI 抵达现实世界的载体。这个逻辑翻转了当前市场的整个叙事框架。市场的恐惧是“AI 取代软件”，而 Bersey 的判断是“软件将驯化 AI”。他引用了一个来自互联网时代的历史类比：当年互联网爆发，最初的价值积累集中在物理基础设施，服务器、光纤电缆、数据中心。大量资本涌入硬件基础设施，而那些苦苦挣扎的早期互联网公司，反而是最终赢得长期价值的一方。软件，才是互联网价值的终点。AI 的演进，Bersey 认为，正在重演同一部剧本。2024 和 2025 年是基础设施的建设期，算力、模型、代码整合——这一切都是为软件层的爆发在铺路。而 2026 年，是引擎真正点火的一年。“软件将是 AI 在全球最大型企业中扩散的主要机制。我们认为 2026 年是软件变现的启动之年。”基础模型为什么替代不了企业软件？报告最有分量的论证，是对“AI 直接颠覆软件”这一逻辑的逐层拆解。批评者的观点看起来很有说服力：大型语言模型已经能写代码，vibe coding（通过自然语言描述直接生成可用软件）正在兴起，AI 模型公司已经在做更多应用层的尝试，那么，企业为什么还需要 Oracle、SAP、Salesforce 这些耗资巨大的传统软件系统？Bersey 的回答从三个层面展开。第一，基础模型有“先天缺陷”。报告明确指出，基础模型“存在内在缺陷”，无法胜任对大型企业核心平台进行“整体替换”的任务。它们在窄场景中表现良好，图像生成、小型应用开发、文本处理，但对于高保真度、企业级核心平台而言，这“并不现实”。根本原因在于训练数据的局限性。LLM 是在公开互联网数据上训练的，而企业软件系统数十年来积累的私有架构知识、业务逻辑、操作规范——这些核心知识产权根本不在公网上，AI 无从学习，也无从复制。Oracle、SAP 的系统护城河，不是靠写代码能追上的，它是靠时间和业务场景累积起来的。第二，Vibe Coding 的能力边界被严重高估。报告直接点名了 Vibe Coding 的致命弱点：它把设计的责任和负担完全压在了开发者身上。你告诉 AI“我想要一个能处理全球供应链的系统”，AI 可以生成代码，但“如何定义这个系统的架构、如何处理异常情况、如何确保在极端压力下不崩溃”，这些判断依然需要人。更关键的是，Bersey 指出，那些主要的 AI 模型公司“几乎没有创建企业级软件的经验”。他们是从零开始进入一个极其复杂的环境。而企业软件经过数十年迭代，已经进化到“几乎零错误、高吞吐量、高可靠性”的水准，这是 AI 新贵短期内无法企及的基准线。第三，企业切换成本是一道真实存在的高墙。即便假设 AI 真的能写出同等水准的代码，企业替换核心系统的代价依然极其高昂，收入中断风险、生产力损失、跨 IT 环境的系统兼容问题、对供应商品牌和服务能力的信任积累……这些都是真实的切换成本，不会因为 AI 能写代码而消失。企业级软件要求的，是多年来经过验证的 99.999% 正常运行时间，是在各种复杂 IT 环境下的无差错运行。这种信任，是时间换来的，不是代码堆出来的。谁将是 AI 变现的真正受益者？如果说前半部分是防守性的论证，那报告的后半部分则是进攻性的布局。Bersey 的核心判断是：AI 价值链的最大份额，最终将流向软件层，而非硬件和芯片层。“我们认为 AI 是软件栈中最主要的价值创造来源，长期价值的最大份额将归属软件，而非硬件。”他同时指出，硬件稀缺性，GPU 短缺、电力限制、数据中心瓶颈，在未来数年内都将持续存在。这种稀缺性，恰恰强化了软件平台的战略地位：只有软件平台，才能将 AI 能力转化为可规模化、可重复的商业价值。而具体的变现载体，报告指向了 AI 智能体（agentic AI）。Bersey 预测，2026 年将看到面向任务型、嵌入工作流的 AI 智能体在财富 2000 强企业和中小企业中的大规模部署。但他对智能体的定性，与市场上的主流叙事截然不同，他不认为智能体是替代软件的颠覆者，而是认为智能体必须在软件定义的参数和权限范围内运行，正是这种“有边界的智能体”，才能满足企业对 AI 风险管控的需求。换言之，企业不需要一个无所不能、自由奔跑的 AI，它们需要的是一个能被治理、被审计、在合规框架内运作的 AI。而这，只有深度嵌入企业软件系统的智能体才能做到。“软件是企业可控地使用 AI 的关键途径。”这是整份报告最核心的一句判断。同时，报告还预测推理（inference）需求将逐渐超过训练需求，成为算力消耗增长的主要驱动力，这意味着随着智能体的普及，算力消耗不会萎缩，而会持续增长，进一步支撑整个软件和基础设施生态。机会还是陷阱？报告发布时，软件板块整体估值已经跌至历史性低位。Bersey 的判断是：低估值叠加即将到来的变现元年，这是入场机会，而非离场信号。“软件估值处于历史低位，尽管该行业正处于大规模扩张的前夜。”在具体标的的推荐上，HSBC 的逻辑很清晰：那些已经建立了深厚数据护城河、具备嵌入 AI 智能体能力、且不依赖纯人头计费模式的软件公司，将是这轮 AI 变现浪潮的最大受益者。买入评级名单包括 Oracle、Microsoft、Salesforce、ServiceNow、Palantir、CrowdStrike、Alphabet 等，几乎涵盖了企业软件的所有核心玩家。值得注意的是，HSBC 同时下调了 IBM 和 Asana 的评级，将 Palo Alto Networks 列入“减持”，不是所有软件公司都能安全渡劫，关键在于能否成为 AI 智能体落地的基础设施，而不是被智能体绕过的人工界面。Bersey 的报告逻辑严密，时机精准，逆势而出的姿态本身就具有极强的传播效应。但有一个问题，报告没有正面回答：如果 AI 智能体真的能够在企业软件的框架内高效运作，企业对软件“席位”的需求，会不会仍然在悄悄萎缩？软件作为 AI 载体的价值或许成立，但“按人头收费”的商业模式是否能支撑当前的估值，依然是悬在空中的问题。软件吞噬 AI，还是 AI 吞噬软件，这场辩论，2026 年的每一份财报，都将是新的证据。","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"isVideo":false,"video":null,"symbols":[],"gpt_button":1,"need_auth":false,"need_login_tip":false,"code":"91000000","status":"200"},"commentList":[],"isCommentEnd":true,"newsSizeData":{"likeSize":0,"commentSize":0,"repostSize":1,"favoriteSize":1,"likeStatus":false,"favoriteStatus":false},"APP":{"userAgent":"Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; 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