大多数公司根本未准备好迎接 AI

✍ Daniel Miessler🕐 2026-05-03📦 6.2 KB 🟢 已读 𝕏 文章列表

文章指出，大多数公司在采用 AI 时面临的核心阻碍并非技术不成熟，而是缺乏清晰的愿景、目标和自我认知。AI 无法执行未被明确定义的任务。成功利用 AI 的公司往往是那些已经清楚自己在做什么、如何运作以及面临何种挑战的企业。混乱且无法清晰描述自身业务流程的公司将被高效且认知清晰的小型公司取代。

AI 企业转型管理战略自动化 LLM

# Most Companies Aren't Anywhere Near Ready for AI **作者**: ᴅᴀɴɪᴇʟ ᴍɪᴇssʟᴇʀ **日期**: 2026-05-02T19:59:50.000Z **来源**: [https://x.com/DanielMiessler/status/2050666594188304484](https://x.com/DanielMiessler/status/2050666594188304484) --- ![Image](/doc/1486/image/img_a88ae7198d00.jpg) It's not that companies aren't using AI: it's that they can't. Most of the frustration people have with AI not being able to do what they want is actually them not being able to describe what they want. I have consulted for the world's largest companies, hundreds of startups, and tons of mid-size companies in the Global 1000. The number one issue I see is unclear and constantly-changing vision and goals. AI is about execution, and it's quite powerless when it doesn't know what to execute. Companies that know exactly what they want are thriving with AI. And the better the AI gets, the more they will crush it. But this is a small percentage of companies, because only a small percentage of companies are self-aware and together enough to give AI proper instructions. You can't optimize what you don't understand. And it's foolish to scale something that you shouldn't be doing in the first place. People talk about companies not being ready for AI and I don't think they realize how bad the problem is. This is not a technical maturity issue. It's a whole lot more fundamental than that. A massive percentage of companies are haphazardly successful despite themselves. It's not super clear what they're trying to accomplish or how exactly they're doing it, but they have a few tricks that work, that they're decent enough at executing, that they're still around. But if you were to walk into the company and say, OK, describe to me what you're trying to do, and what your strategies are, and what your challenges are, and what your work streams are — they would either stare blankly at you or laugh in your face. It would take them weeks to put together a project to find that out. And then months to actually do the project. I honestly believe the vast majority of companies are in grave danger because they are essentially chaotic black boxes that barely work. Having the board or leadership tell everyone in such a company to "use AI" is like looking at a screen of nothing but static and saying, "we gotta scale this thing." > Cool, boss. Do me a favor and point at the thing you want me to improve. (long pause) > Great question: Let's get some meetings together to figure that out. AI is mostly useless in these companies. And unfortunately, that means many (if not most) companies. The narrative right now is that AI isn't helping enough companies yet, so what's the problem? When will AI get good enough? Maybe AI isn't as good as people thought. What's hilarious, and easy to see, is that the companies AI is helping are somehow magically the same companies that already know what they're doing. They can tell you very quickly: - the problem or problems that they are solving for customers - the problem with existing solutions that their solution solves - the goals they have for the company - the metrics associated with those goals - the challenges that are stopping them from reaching their goals - the strategies they are pursuing to overcome those challenges - the projects they are doing to implement those strategies - the work that is being done within those projects - by what people - and how much it is costing them And crucially, companies that know what they're doing give largely the same answers to these questions across different quarters and years. A sure sign of a flailing company is when their departments spend massive amounts of time claiming to have those answers — but the answers significantly change every quarter because everything is constantly in flux. So people are just writing down whatever they think makes them look good. It takes them weeks to prepare, only to be discarded a few weeks later when the process starts over. AI can do basically nothing for these companies. In fact, it could even make it worse — because now it helps people flail more impressively. Like with more backflips and charts and stuff. And you may ask, "well, if they're so bad, then how are they still around?" The answer is simple: most of their competition is just as bad. So what's the point of all this? A few things. 1. AI has barely even started in the enterprise, because only a tiny fraction of companies have the self-knowledge and ability to articulate themselves well enough to be ready for AI. 2. We should stop looking at AI as the problem, or even technology as the problem. The issue is not being able to describe one's company clearly—including its goals, workflows, operations, decisions, teams, and spending —in a clear and consumable fashion. 3. Companies who are unable to do this are in grave danger from companies that can. 4. The primary danger to large unwieldy companies is that it's now possible for a smaller company to function with the strength of a much larger one. And it's far easier for a small company to be able to answer the questions above. 5. Because of this, all existing companies are about to face extraordinary downward force. And only companies who have their shit together will stay afloat and rise. 6. AI is a remarkably small part of who will win or lose in this initial phase. AI is what the winners will use to fight each other in the New World. Right now, the game is figuring out who's going to make it there. 7. The number one question you should be asking as a company is not what AI can do for you, but whether or not your company is in the state where AI can help at all. And if not, then you need to get into that state as quickly as possible. ## 相关链接 - [ᴅᴀɴɪᴇʟ ᴍɪᴇssʟᴇʀ](https://x.com/DanielMiessler) - [@DanielMiessler](https://x.com/DanielMiessler) - [7.5K](https://x.com/DanielMiessler/status/2050666594188304484/analytics) - [3:59 AM · May 3, 2026](https://x.com/DanielMiessler/status/2050666594188304484) - [7,551 Views](https://x.com/DanielMiessler/status/2050666594188304484/analytics) - [View quotes](https://x.com/DanielMiessler/status/2050666594188304484/quotes) --- *导出时间: 2026/5/3 14:48:06* --- ## 中文翻译 # 绝大多数公司远未为 AI 做好准备 **作者**: ᴅᴀɴɪᴇʟ ᴍɪᴇssʟᴇʀ **日期**: 2026-05-02T19:59:50.000Z **来源**: [https://x.com/DanielMiessler/status/2050666594188304484](https://x.com/DanielMiessler/status/2050666594188304484) --- ![Image](/doc/1486/image/img_a88ae7198d00.jpg) 问题不在于公司没有使用 AI，而在于它们根本做不到。大多数人对 AI 无法按预期工作的挫败感，实际上源于他们自己无法描述清楚想要什么。我曾为全球最大的公司、数百家初创企业以及全球 1000 强中的众多中型企业提供咨询服务。我看到的头号问题是：愿景和目标不清晰且 constantly-changing。 AI 是关于执行的，当它不知道该执行什么时，就几乎无能为力。那些确切知道自己想要什么的公司，正借助 AI 蓬勃发展。而且 AI 越强大，它们的领先优势就越明显。但这只占很小一部分公司，因为只有极少数公司具备足够的自知之明和组织能力，能够给 AI 下达正确的指令。你无法优化你不理解的东西。如果你根本不应该做某件事，却去扩大它的规模，那是愚蠢的。人们谈论公司未为 AI 做好准备，但我认为他们没有意识到问题有多严重。这不是一个技术成熟度的问题。这比那要根本得多。很大一部分公司的成功纯属侥幸，尽管它们本身一团糟。它们并不清楚自己到底想要达成什么目标，或者确切地是如何做到的，但它们掌握了一些管用的套路，执行得还凑合，所以存活了下来。但是，如果你走进这家公司说：“好吧，给我描述一下你们想做什么，你们的策略是什么，面临的挑战是什么，工作流程有哪些”——他们要么会茫然地盯着你，要么会嘲笑你。他们可能需要花几周时间组个团队来搞清楚这个问题。然后再花几个月的时间真正去执行这个项目。我真心相信绝大多数公司都处于极度危险之中，因为它们本质上就像是一个混乱的黑盒子，勉强维持运转。在这种公司里，董事会或高层领导对所有人喊话“我们要使用 AI”，这就好比看着满屏雪花的电视画面说：“咱们得把这东西规模化。” > 酷毙了，老板。劳驾您指一下，到底想让我改进哪玩意儿？（长时间的沉默） > 问得好：咱们这就安排几个会，把这事儿搞清楚。在这些公司里，AI 基本上毫无用处。不幸的是，这意味着许多（如果不是大多数的话）公司都是如此。目前的舆论是，AI 还没有帮助到足够多的公司，所以问题出在哪里？AI 什么时候才能变得足够好？也许 AI 并没有人们想象的那么厉害。但搞笑且显而易见的是，AI 正在帮助的那些公司，似乎神奇地恰好是那些本来就清楚自己在做什么的公司。它们能很快告诉你： - 他们正在为客户解决的一个或多个问题 - 他们的解决方案所解决的现有方案的问题 - 他们为公司设定的目标 - 与这些目标相关的指标 - 阻碍他们达成目标的挑战 - 他们正在采取的克服这些挑战的策略 - 他们正在实施的、以落实这些策略的项目 - 在这些项目中正在进行的具体工作 - 由谁负责 - 以及成本是多少关键是，那些知道自己在做什么的公司，在不同的季度和年份里，对这些问题的回答在很大程度上是一致的。一个苦苦挣扎的公司的明显标志是：其各个部门花费大量时间声称他们拥有这些答案——但每个季度的答案都会发生显著变化，因为一切都处于不断的变动之中。所以人们只是写下那些他们认为能让自己看起来不错的东西。他们花几周时间准备，结果几周后当流程重新开始时，这些就被丢弃了。 AI 对这些公司几乎无能为力。事实上，它甚至可能让情况变得更糟——因为它现在能帮人们更“华丽”地瞎折腾。比如弄出更多的花哨动作和图表之类的。你可能会问：“好吧，如果它们这么烂，那为什么还能活到现在？”答案很简单：它们的大多数竞争对手也同样烂。那么，说这一大堆的结论是什么？有几点。 1. AI 在企业界才刚刚起步，因为只有极少数公司具备足够的自知之明和自我表达能力，足以准备好迎接 AI。 2. 我们应该停止把 AI 视为问题所在，甚至停止把技术视为问题所在。关键在于无法清晰地描述自己的公司——包括其目标、工作流程、运营、决策、团队和支出——以一种清晰且易于理解的方式。 3. 无法做到这一点的公司，正面临那些能做到这一点的公司的巨大威胁。 4. 对于庞大而笨拙的公司来说，主要危险在于，一家小公司现在就有可能具备像大公司一样的实力。而小公司想要回答上述问题要容易得多。 5. 正因为如此，所有现有的公司即将面临巨大的下行压力。只有那些管理有序的公司才能生存并崛起。 6. 在这个初始阶段，谁赢谁输，AI 只是一个微不足道的因素。AI 是赢家们将在新世界中用来互相竞争的武器。目前的游戏在于找出谁能进入那个新世界。 7. 作为公司，你应该问的首要问题不是 AI 能为你做什么，而是你的公司是否处于 AI 能够提供帮助的状态。如果没有，那么你需要尽快进入那种状态。 ## 相关链接 - [ᴅᴀɴɪᴇʟ ᴍɪᴇssʟᴇʀ](https://x.com/DanielMiessler) - [@DanielMiessler](https://x.com/DanielMiessler) - [7.5K](https://x.com/DanielMiessler/status/2050666594188304484/analytics) - [2026年5月3日上午3:59](https://x.com/DanielMiessler/status/2050666594188304484) - [7,551 次观看](https://x.com/DanielMiessler/status/2050666594188304484/analytics) - [查看引用](https://x.com/DanielMiessler/status/2050666594188304484/quotes) --- *导出时间: 2026/5/3 14:48:06*

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