Fortune | FORTUNE 09月19日
从知识到能力:在AI时代实现价值的转型
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文章探讨了在人工智能(AI)日益普及的背景下,企业和个人如何在新经济中创造价值。作者指出,AI正在使大量知识变得触手可及,导致许多传统知识型岗位(尤其是中层管理者)面临被淘汰的风险。文章强调,未来 differentiating factor 不再是“知道得多”,而是“做得好”,即拥有将知识转化为实际行动和解决问题的能力(Utility)。这种能力通过系统化、流程化地执行,能够稳定地提供高质量的结果。作者以一个客户投诉的案例说明,操作员因各自接受的培训不同而采用不同方法,导致结果不一致,这正是“做不同的事情却期望相同结果”的警示。文章认为,AI将成为组织知识的终极管理者,而企业成功的关键在于建立标准化的流程,从而实现“可重复的卓越”,并在此基础上持续改进,从“奇迹”转向“方法”。

💡 **AI驱动的组织变革与知识的贬值:** 文章指出,AI技术的进步使得知识获取成本急剧下降,大量信息触手可及,这正在颠覆传统的知识壁垒。特别是中层管理者,其核心价值往往在于掌握信息和知识,在AI时代,这种“知道更多”的优势将逐渐减弱,甚至可能被AI取代,导致组织结构的“大扁平化”,大量中层职位面临淘汰风险。这要求个人和组织必须认识到,单纯的知识储备已不再是核心竞争力。

🚀 **从“知道”到“做到”:能力(Utility)成为新价值创造核心:** 在AI时代,真正的价值在于“Utility”,即把知识转化为实际行动、解决问题的能力。这包括理解问题、提出正确的问题、以及执行解决方案的能力。文章强调,价值的创造将从“知道答案”转向“知道问题”和“如何执行”。这种能力通过系统化、流程化的执行,能够稳定地提供高质量的服务和产品,实现“按需交付,无戏剧性”。

⭐ **建立标准化流程,实现“可重复的卓越”:** 为了在AI时代保持竞争力并持续创造价值,企业需要建立和维护明确的、可解释的标准流程。文章认为,标准不是为了限制创新,而是为了确立一个稳定的基线,以便在“稳定”的基础上进行改进。当“周二”的表现可以被稳定复制时,才能更好地尝试“周三”的优化。这种从“奇迹”到“方法”的转变,是实现长期成功和适应“大扁平化”的关键,也是AI能够有效管理和扩展组织知识的基础。

🤔 **警惕陷阱:重复无效与随机应变失控:** 文章最后警示了两种可能导致失败的陷阱。一种是“做相同的事情却期待不同的结果”,即墨守成规,不思改变,这在AI时代将迅速被淘汰。另一种是“做不同的事情却期待相同的结果”,即缺乏标准化和流程控制,依赖随机应变,这在AI时代将带来巨大的风险,因为客户更看重可靠性和承诺的兑现,而非惊喜。因此,学习和实验固然重要,但不能将其与经过验证的标准混淆。

We all know the line usually (and wrongly) pinned on Einstein that the definition of insanity is doing the same thing over and over and expecting a different result. But here’s the thing few people in business truly understand when it comes to the products and services they deliver: “The enemy of delivering quality is doing different things yet expecting the same result.”

Improvement requires change; quality requires consistency. The art of leadership is knowing when to do which and building the muscle to do both on purpose.

Some have identified this current period in business as the Great Flattening, where AI puts vast reservoirs of knowledge at everyone’s fingertips in just milliseconds, making many middle managers and other knowledge workers obsolete. Gartner found that through 2026, 20% of the organizations they surveyed will use AI to flatten their organizational structure, eliminating over half of their current middle management positions. I expect this to only grow—and accelerate—in the coming years.

The upshot is this: if you’re a middle manager, you may already be on your organization’s endangered species list. The knowledge that used to differentiate you from everyone else will soon be table stakes. If your edge is “I know more,” prepare to be leveled.

The new differentiator is whether you can turn your knowledge into utility—the ability to do things that need to be done. It’s through utility that you create value by transforming the what into the how and why of systems, and execution that produce quality on demand, without drama. Value will be created in the new economy not by knowing the answer, but by knowing the question. Utility is the ability to execute, to know the problem, to have the question.

That distinction came home to me while coaching a team, a customer complaint led to a project to find the root cause. As the team peeled back the potential causes a pattern emerged. Each operator altered the equipment to run “according to their training,” it became clear that we all used the same machine and materials but used different methods. Each person followed the knowledge they received from different trainers.

Make no mistake: Everyone believed what they were doing was correct. Knowledge was scarce and highly specialized in the hands of a variety of experts and trainers. “We were doing different things but expecting the same result”.  It is a cautionary tale; you can delight once, but a system will deliver every time.

As I tell clients, you can’t sustain what you can’t explain. If you don’t know why a win happened, you can’t own it next time—let alone extend it across a network of sites, lines, or teams.

The elephant in every boardroom

Now add AI, that great big elephant in every boardroom. For a century, firms built moats around knowledge, their “Intellectual Property,” the experts in the middle who “Had the answers.” That layer, today mostly comprised of middle managers, is being thinned from the herd. Organizations that understand that AI will become the ultimate keeper of organizational knowledge, a resource for learning and standardizing on best practices, will be the winners.

In the Great Flattening, the premium shifts to utility and the hard, unglamorous capacity to execute with consistency. Front‑line leaders become pivotal; they’re the translators who turn “standards” into “how to adapt to this situation” through knowing how to ask the right questions, to read the situation, and to apply standardized knowledge.  My complaint team failed because of variation in knowledge, the risk shifts in the new reality to successfully applying that knowledge, to recognizing deviations and asking why?

This is not semantics. Value is what the customer actually receives. Utility is your organization’s ability to create and deliver that value on demand—on time, in spec, every time.

If that sounds rigid, remember that standards are how you earn the right to improve. Once you can do “Tuesday” on command, then you can experiment with a better Wednesday—because you’ll know what changed. That’s where standards shine they force questions that create clarity, reveal causes, and keep adjustments anchored in the work, not in a PowerPoint. The aim isn’t to freeze the world; it’s to stabilize what works and then extend it—across shifts, across sites, across partners—until your best performance becomes your normal performance and your new baseline for the next step up. You move from miracles to method.

Which brings us back to the twin aphorisms that began this piece. Einstein’s misattributed “insanity” quote warns against rituals that produce nothing new. My corollary warns against novelty that produces nothing reliable. In the Great Flattening, both traps are career‑ending. If you do the same thing and expect difference, you’re dreaming. If you do different things and expect sameness, you’re gambling with your reputation.

So, by all means, keep learning and experimenting. There’s value in discovery. But don’t mistake experiments and opinions for standards. Your customers don’t come back for surprises; they come back for promises kept. In a world where AI collapses the cost of knowledge, the scarce resource is the ability to execute—to make the same promise and keep it again and again. Utility creates value. Utility scales. Utility survives the Great Flattening.

And one last perspective worth taking to work tomorrow morning: if you want it to be there next week, capture the root cause of your success to establish the knowledge AI may hold for your organization, because you can’t sustain what you can’t explain.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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相关标签

AI 价值创造 组织变革 领导力 未来工作 能力 标准化 流程 The Great Flattening Utility Knowledge Management
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