All Content from Business Insider 10月29日 19:08
AI时代重塑企业运作模式,CEO需适应新生产函数
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微软CEO萨提亚·纳德拉强调,人工智能的崛起正在颠覆企业构建、销售和运营的传统方式。他指出,AI不仅是一次技术革新,更是一场商业模式和组织架构的全面重塑。纳德拉认为,成功的领导者需要掌握AI驱动下的“新生产函数”,即理解在智能系统辅助下如何高效完成工作。他强调,在AI时代,抛弃旧有习惯、拥抱变化至关重要,这比单纯的学习更具挑战性。AI带来了边际成本极低的软件产出,迫使企业从根本上重新思考生产、成本和人才的配置,以在新一轮的竞争中立于不败之地。

🚀 **AI驱动的生产函数变革:** 纳德拉指出,AI正在改变“生产函数”,即工作如何完成。智能系统能够生成代码、设计和内容,这要求CEO们学习如何利用AI优化生产流程,而不是仅仅依赖人力。这种转变意味着企业需要重新审视和构建其核心的生产力模型。

💡 **商业模式与组织架构重塑:** AI的冲击不仅在于技术层面,更在于其对商业模式和组织架构的颠覆。企业需要同时应对技术、商业模式和组织生产方式的转变,这是一种前所未有的挑战。纳德拉以微软从服务器业务转向云计算的转型为例,说明了适应这种商业模式转变的艰难与必要性。

🧠 **拥抱变化与“去学习”的重要性:** 在AI时代,CEO们面临的最大挑战是“去学习”(unlearning)旧有习惯。纳德拉强调,学习新事物是容易的,但抛弃根深蒂固的旧方法并采纳新模式则更为困难。组织适应性应被视为一项核心能力,而“去学习”可能是比学习更重要的领导力技能。

💰 **边际成本软件的出现:** AI带来了“边际成本软件”的概念,即软件的每个新输出单元(代码、设计、内容等)几乎可以零成本地创造。这与传统的SaaS模式不同,它要求企业认识到产品生产成本的根本性变化,并相应调整其盈利和定价策略。

"DeepSeek, and R1 in particular, was the first model I've seen post some points," Microsoft's CEO Satya Nadella said.

When Microsoft CEO Satya Nadella looks at the rise of artificial intelligence, he doesn't just see a new technology wave.

He sees a complete rewiring of how companies build, sell, and organize themselves.

Speaking to TBPN at GitHub Universe on Tuesday, Nadella said business leaders must prepare for a tech shift, a business model shift, and an organizational shift all at once — a combination he described as unlike anything the industry has faced before.

"This one is interestingly enough both a tech shift, a business model shift … and three, the way you produce your artifact — your software — is changing," Nadella said.

"The product development process is completely getting ripped and replaced."

A new production function

For Nadella, the CEOs who succeed in the AI age will be the ones who learn the new production function — how work gets done when code and knowledge can be generated by intelligent systems rather than humans alone.

"The key is learning the new production function," he said. "It's kind of like rewiring yourself — unlearning is the hardest part. Learning is easy. Sometimes if you have to unlearn and learn, it's much harder."

Microsoft, he said, has spent decades adapting through major transformations — from the rise of the internet to the shift to cloud computing.

But AI introduces something new: the arrival of true marginal cost software, where every new unit of output — from code to design to content — can be created almost costlessly.

"This is the first time you have marginal cost software — not just like the cogs of the SaaS world, but true marginal cost," Nadella said.

Shifting business models and mindset

Nadella compared the AI transition to Microsoft's own painful migration from its ultra-profitable server business to cloud computing in the 2000s.

"We've also navigated tough business model shifts," he said. "When you suddenly have a 98-99% gross-margin server business and you move to the cloud and you don't even know, 'Man, is there a margin here?' And yet you have to make the shift and figure it out."

He warned that companies can't cling to old models, even if they're still profitable.

"Given the binary nature, you've got to make it to the other side," he said.

Nadella argued that mindset applies equally to the AI revolution. Companies that hesitate — waiting to see the economics settle — will find their existing margins erode faster than expected.

Unlearning as a leadership skill

Nadella's advice to CEOs: treat organizational adaptability as a first-class capability. Learning is no longer enough; unlearning may matter more.

He pointed to younger engineers who've grown up coding alongside GitHub Copilot as a preview of the next generation's norms.

"It's the first cohort of developers who grew up with GitHub Copilot as standard issue," he said.

In that sense, Nadella's message was both a warning and a road map: the winners in the AI era will be those who rebuild their thinking about production, cost, and talent from the ground up.

Read the original article on Business Insider

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AI 人工智能 CEO 领导力 商业模式 生产函数 技术变革 AI Artificial Intelligence CEO Leadership Business Models Production Function Technological Disruption
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