
多年來,微軟首席執(zhí)行官薩提亞·納德拉始終引領(lǐng)人工智能的發(fā)展浪潮,這得益于他與OpenAI首席執(zhí)行官薩姆·奧爾特曼(Sam Altman)的長期合作,以及微軟AI首席執(zhí)行官穆斯塔法·蘇萊曼(Mustafa Suleyman)的開創(chuàng)性工作,尤其是Copilot工具的研發(fā)。但納德拉鮮少提及2025年下半年大部分時間里持續(xù)困擾華爾街的擔(dān)憂:人工智能領(lǐng)域是否存在泡沫。
在瑞士達(dá)沃斯舉行的世界經(jīng)濟(jì)論壇年會上,納德拉與論壇臨時聯(lián)席主席、貝萊德(BlackRock)首席執(zhí)行官拉里·芬克(Larry Fink)展開對話。他解釋道,倘若人工智能的增長完全依賴資本投入,這可能就是泡沫的信號。“如果我們討論的焦點(diǎn)完全集中在科技企業(yè)上,那么這無疑是一個顯著信號,表明該領(lǐng)域存在泡沫。”納德拉表示。“若討論僅聚焦于技術(shù)層面的動態(tài),那就只是供給側(cè)的情況。”
不過納德拉針對生產(chǎn)力困境提出解決方案,呼吁企業(yè)領(lǐng)導(dǎo)者采用新知識工作模式,即通過調(diào)整工作流程,使之與人工智能的技術(shù)架構(gòu)相適配。“作為企業(yè)領(lǐng)導(dǎo)者,我們應(yīng)當(dāng)樹立這樣一種理念:要借助技術(shù)手段,推動工作本身——也就是工作流程——的變革。”
轉(zhuǎn)型陣痛
納德拉指出,這場變革并非全無先例。他將當(dāng)下的人工智能浪潮與上世紀(jì)80年代的計算機(jī)革命相類比:彼時,計算機(jī)技術(shù)重塑了職場格局,催生了新增長機(jī)遇與生產(chǎn)力提升空間,也催生了新型勞動者群體。“我們由此定義了‘知識型工作’這一全新的職業(yè)類別,人們真正開始借助計算機(jī)與軟件的力量,放大自身的工作成效,”他說道,“我認(rèn)為,在人工智能時代,類似的變革必將再次上演。”
納德拉認(rèn)為人工智能將徹底顛覆企業(yè)內(nèi)部的信息流通模式。相較于過去層級分明、效率低下的信息傳遞機(jī)制,人工智能會推動企業(yè)信息流通走向扁平化,這就要求企業(yè)領(lǐng)導(dǎo)者重新調(diào)整現(xiàn)有的組織架構(gòu)。納德拉表示:“現(xiàn)有組織設(shè)有部門與各類專業(yè)崗位,信息自下而上傳遞。但在人工智能時代,這種模式行不通了——信息流通會實(shí)現(xiàn)全面扁平化。一旦這種模式成型,我們就必須重新設(shè)計組織架構(gòu)。”
對部分《財富》美國500強(qiáng)企業(yè)而言,這種轉(zhuǎn)型或許會更為艱難,因?yàn)榻M織架構(gòu)的調(diào)整往往伴隨著轉(zhuǎn)型陣痛。納德拉指出,精簡型企業(yè)能夠更輕松地應(yīng)用人工智能技術(shù),原因在于其組織架構(gòu)更具新穎性與可塑性,而大型企業(yè)則可能需要較長時間才能使用新工作流程。
盡管人工智能已得到廣泛應(yīng)用,普華永道(PwC)第29期《全球CEO調(diào)研報告》顯示:僅有10%至12%的企業(yè)表示,該技術(shù)為公司帶來了營收增長或成本節(jié)約方面的實(shí)際效益,而56%的企業(yè)稱尚未從人工智能的應(yīng)用中獲得任何回報。這一數(shù)據(jù),與2025年8月一項(xiàng)聚焦人工智能投資回報的調(diào)查結(jié)論相呼應(yīng)——彼時的調(diào)查結(jié)果更為悲觀,有95%的生成式人工智能試點(diǎn)項(xiàng)目以失敗告終。
在達(dá)沃斯論壇期間,普華永道全球主席康慕德(Mohamed Kande)接受《財富》雜志戴安·布雷迪(Diane Brady)采訪時指出,在當(dāng)前的人工智能應(yīng)用周期中,眾多首席執(zhí)行官持謹(jǐn)慎態(tài)度且信心不足。“人工智能發(fā)展如此迅猛……以至于人們忘記技術(shù)應(yīng)用必須回歸基礎(chǔ)。”他解釋道。調(diào)查發(fā)現(xiàn),那些從人工智能應(yīng)用中獲益的企業(yè)都在“夯實(shí)基礎(chǔ)”。他強(qiáng)調(diào),這更多關(guān)乎執(zhí)行而非技術(shù)本身,未來高效的管理和卓越的領(lǐng)導(dǎo)力將至關(guān)重要。
納德拉對芬克表示:“大型企業(yè)面臨根本性挑戰(zhàn):除非其變革速度能跟上技術(shù)迭代的步伐,否則那些借助人工智能工具實(shí)現(xiàn)規(guī)模化發(fā)展的小型企業(yè),終將后來居上。”
新入局者擁有“從零開始”的優(yōu)勢,能圍繞人工智能能力搭建工作流程,而大型企業(yè)則需應(yīng)對人工智能對整個部門和專業(yè)分工模式帶來的扁平化影響。
誠然,納德拉承認(rèn),大型企業(yè)依然具備自身的優(yōu)勢,尤其是在客戶關(guān)系、數(shù)據(jù)資源與專業(yè)技術(shù)方面。但他強(qiáng)調(diào),企業(yè)必須掌握駕馭這些資源的能力,以此推動管理模式的變革,否則這些優(yōu)勢會成為重大阻礙。
“關(guān)鍵在于,倘若企業(yè)無法借助新生產(chǎn)函數(shù)將這些優(yōu)勢轉(zhuǎn)化為發(fā)展動能,那么終將陷入發(fā)展停滯的困局。”他說道。(財富中文網(wǎng))
譯者:中慧言-王芳
多年來,微軟首席執(zhí)行官薩提亞·納德拉始終引領(lǐng)人工智能的發(fā)展浪潮,這得益于他與OpenAI首席執(zhí)行官薩姆·奧爾特曼(Sam Altman)的長期合作,以及微軟AI首席執(zhí)行官穆斯塔法·蘇萊曼(Mustafa Suleyman)的開創(chuàng)性工作,尤其是Copilot工具的研發(fā)。但納德拉鮮少提及2025年下半年大部分時間里持續(xù)困擾華爾街的擔(dān)憂:人工智能領(lǐng)域是否存在泡沫。
在瑞士達(dá)沃斯舉行的世界經(jīng)濟(jì)論壇年會上,納德拉與論壇臨時聯(lián)席主席、貝萊德(BlackRock)首席執(zhí)行官拉里·芬克(Larry Fink)展開對話。他解釋道,倘若人工智能的增長完全依賴資本投入,這可能就是泡沫的信號。“如果我們討論的焦點(diǎn)完全集中在科技企業(yè)上,那么這無疑是一個顯著信號,表明該領(lǐng)域存在泡沫。”納德拉表示。“若討論僅聚焦于技術(shù)層面的動態(tài),那就只是供給側(cè)的情況。”
不過納德拉針對生產(chǎn)力困境提出解決方案,呼吁企業(yè)領(lǐng)導(dǎo)者采用新知識工作模式,即通過調(diào)整工作流程,使之與人工智能的技術(shù)架構(gòu)相適配。“作為企業(yè)領(lǐng)導(dǎo)者,我們應(yīng)當(dāng)樹立這樣一種理念:要借助技術(shù)手段,推動工作本身——也就是工作流程——的變革。”
轉(zhuǎn)型陣痛
納德拉指出,這場變革并非全無先例。他將當(dāng)下的人工智能浪潮與上世紀(jì)80年代的計算機(jī)革命相類比:彼時,計算機(jī)技術(shù)重塑了職場格局,催生了新增長機(jī)遇與生產(chǎn)力提升空間,也催生了新型勞動者群體。“我們由此定義了‘知識型工作’這一全新的職業(yè)類別,人們真正開始借助計算機(jī)與軟件的力量,放大自身的工作成效,”他說道,“我認(rèn)為,在人工智能時代,類似的變革必將再次上演。”
納德拉認(rèn)為人工智能將徹底顛覆企業(yè)內(nèi)部的信息流通模式。相較于過去層級分明、效率低下的信息傳遞機(jī)制,人工智能會推動企業(yè)信息流通走向扁平化,這就要求企業(yè)領(lǐng)導(dǎo)者重新調(diào)整現(xiàn)有的組織架構(gòu)。納德拉表示:“現(xiàn)有組織設(shè)有部門與各類專業(yè)崗位,信息自下而上傳遞。但在人工智能時代,這種模式行不通了——信息流通會實(shí)現(xiàn)全面扁平化。一旦這種模式成型,我們就必須重新設(shè)計組織架構(gòu)。”
對部分《財富》美國500強(qiáng)企業(yè)而言,這種轉(zhuǎn)型或許會更為艱難,因?yàn)榻M織架構(gòu)的調(diào)整往往伴隨著轉(zhuǎn)型陣痛。納德拉指出,精簡型企業(yè)能夠更輕松地應(yīng)用人工智能技術(shù),原因在于其組織架構(gòu)更具新穎性與可塑性,而大型企業(yè)則可能需要較長時間才能使用新工作流程。
盡管人工智能已得到廣泛應(yīng)用,普華永道(PwC)第29期《全球CEO調(diào)研報告》顯示:僅有10%至12%的企業(yè)表示,該技術(shù)為公司帶來了營收增長或成本節(jié)約方面的實(shí)際效益,而56%的企業(yè)稱尚未從人工智能的應(yīng)用中獲得任何回報。這一數(shù)據(jù),與2025年8月一項(xiàng)聚焦人工智能投資回報的調(diào)查結(jié)論相呼應(yīng)——彼時的調(diào)查結(jié)果更為悲觀,有95%的生成式人工智能試點(diǎn)項(xiàng)目以失敗告終。
在達(dá)沃斯論壇期間,普華永道全球主席康慕德(Mohamed Kande)接受《財富》雜志戴安·布雷迪(Diane Brady)采訪時指出,在當(dāng)前的人工智能應(yīng)用周期中,眾多首席執(zhí)行官持謹(jǐn)慎態(tài)度且信心不足。“人工智能發(fā)展如此迅猛……以至于人們忘記技術(shù)應(yīng)用必須回歸基礎(chǔ)。”他解釋道。調(diào)查發(fā)現(xiàn),那些從人工智能應(yīng)用中獲益的企業(yè)都在“夯實(shí)基礎(chǔ)”。他強(qiáng)調(diào),這更多關(guān)乎執(zhí)行而非技術(shù)本身,未來高效的管理和卓越的領(lǐng)導(dǎo)力將至關(guān)重要。
納德拉對芬克表示:“大型企業(yè)面臨根本性挑戰(zhàn):除非其變革速度能跟上技術(shù)迭代的步伐,否則那些借助人工智能工具實(shí)現(xiàn)規(guī)模化發(fā)展的小型企業(yè),終將后來居上。”
新入局者擁有“從零開始”的優(yōu)勢,能圍繞人工智能能力搭建工作流程,而大型企業(yè)則需應(yīng)對人工智能對整個部門和專業(yè)分工模式帶來的扁平化影響。
誠然,納德拉承認(rèn),大型企業(yè)依然具備自身的優(yōu)勢,尤其是在客戶關(guān)系、數(shù)據(jù)資源與專業(yè)技術(shù)方面。但他強(qiáng)調(diào),企業(yè)必須掌握駕馭這些資源的能力,以此推動管理模式的變革,否則這些優(yōu)勢會成為重大阻礙。
“關(guān)鍵在于,倘若企業(yè)無法借助新生產(chǎn)函數(shù)將這些優(yōu)勢轉(zhuǎn)化為發(fā)展動能,那么終將陷入發(fā)展停滯的困局。”他說道。(財富中文網(wǎng))
譯者:中慧言-王芳
Microsoft CEO Satya Nadella has been leading the charge on artificial intelligence for years, owing to his long alliance with OpenAI’s Sam Altman and the groundbreaking work from his own AI CEO, Mustafa Suleyman, particularly with the Copilot tool. But Nadella has not spoken often about the fears that rattled Wall Street for much of the back half of 2025: whether AI is a bubble.
At the World Economic Forum’s annual meeting in Davos, Switzerland, Nadella sat down for a conversation with the forum’s interim co-chair, BlackRock CEO Larry Fink, explaining that if AI growth spawns solely from investment, then that could be a sign of a bubble. “A telltale sign of if it’s a bubble would be if all we are talking about are the tech firms,” Nadella said. “If all we talk about is what’s happening to the technology side then it’s just purely supply side.”
However, Nadella offers a fix to that productivity dilemma, calling on business leaders to adopt a new approach to knowledge work by shifting workflows to match the structural design of AI. “The mindset we as leaders should have is, we need to think about changing the work—the workflow—with the technology.”
Growing pains
This change is not wholly unprecedented, as Nadella pointed out, comparing the current moment to that of the 1980s, when computing revolutionized the workplace and opened up new opportunities for growth and productivity and created a new class of workers. “We invented this entire class of thing called knowledge work, where people started really using computers to amplify what we were trying to achieve using software,” he said. “I think in the context of AI, that same thing is going to happen.”
Nadella argues that AI creates a “complete inversion” of how information moves through a business, replacing slow, hierarchical processes with a view that forces leaders to rethink their organizational structures. “We have an organization, we have departments, we have these specializations, and the information trickles up,” Nadella said. “No, no, it’s actually—it flattens the entire information flow. So once you start having that, you have to redesign structurally.”
That shift may be harder for some Fortune 500 companies as structural changes could be accompanied by uncomfortable growing pains. Nadella says that leaner companies will be able to more easily adopt AI because their organizational structures are fresher and more malleable. On the other hand, large companies could take time to adopt new workflows.
Despite widespread adoption of AI, the 29th edition of PwC’s Global CEO Survey found that only 10% to 12% of companies reported seeing benefits from the technology on the revenue or cost side, while 56% reported getting nothing out of it. It follows up on an even more pessimistic finding about AI returns from August 2025: that 95% of generative AI pilots were failing.
PwC global chairman Mohamed Kande spoke to Fortune’s Diane Brady at Davos about the finding that many CEOs are cautious and lack confidence at this stage of the AI adoption cycle. “Somehow AI moves so fast … that people forgot that the adoption of technology, you have to go to the basics,” he explained, with the survey finding that the companies seeing benefits from AI are “putting the foundations in place.” It’s about execution more than it is about technology, he argued, and good management and leadership are really going to matter going forward.
“For large organizations,” Nadella told Fink, “there’s a fundamental challenge: Unless and until your rate of change keeps up with what is possible, you’re going to get schooled by someone small being able to achieve scale because of these tools.”
New entrants have the advantage of “starting fresh” and constructing workflows around AI capabilities, while larger firms will have to contend with the flattening effect AI has on entire departments and specializations.
To be sure, Nadella says that large organizations have kept an upper hand, especially when it comes to relationships, data, and know-how. However, he maintains that firms must understand how to use those resources to their advantage to change management style, which could otherwise pose a major roadblock.
“The bottom line is, if you don’t translate that with a new production function, then you really will be stuck,” he said.