
在2024年英國大選失利后,外界曾對里希·蘇納克有一種簡單的定論:這位斯坦福MBA畢業(yè)生、前高盛(Goldman Sachs)分析師會(huì)退出議會(huì),離開英國,迅速前往加州,在某家超大規(guī)模云服務(wù)商謀得高薪高位。盡管蘇納克一再否認(rèn),但幾乎沒人相信他。他經(jīng)常穿著典型硅谷風(fēng)格的白色運(yùn)動(dòng)鞋。
兩年后的今天,蘇納克讓懷疑者大跌眼鏡。他仍然是英格蘭北部一個(gè)鄉(xiāng)村選區(qū)的議員(他甚至將AI在奶牛養(yǎng)殖中的應(yīng)用作為自己的研究重點(diǎn)之一)。同時(shí),盡管他已成為高盛、微軟(Microsoft)和Anthropic的顧問,他的工作重心依然堅(jiān)定地扎根于英國。工黨政府也經(jīng)常與他保持溝通。
在英國第二大城市伯明翰(位于倫敦以北約100英里)舉行的高盛“1萬家小企業(yè)”項(xiàng)目會(huì)議上,蘇納克表示:“我與這兩家科技公司的合作,讓我更加確信,AI不僅將帶來巨大的改變,而且變革的速度也將超出想象。”
“這不僅僅關(guān)乎改善我們的經(jīng)濟(jì)狀況——盡管這本身至關(guān)重要。我認(rèn)為,AI將抬高整個(gè)人類社會(huì)的生存底線,因?yàn)樗鼘⒆屖澜绺鞯氐拿總€(gè)人,無論身處何地,都有機(jī)會(huì)獲得金錢能買到的最優(yōu)質(zhì)的醫(yī)療和教育。我認(rèn)為,這是一股非同尋常的民主化力量。”
他對在場的眾多首席執(zhí)行官表示,AI落地應(yīng)用的速度“至關(guān)重要”。如果你沒有為“應(yīng)用型AI”(即在業(yè)務(wù)中實(shí)際應(yīng)用AI)時(shí)代做好規(guī)劃,就面臨被時(shí)代拋棄的風(fēng)險(xiǎn),并最終滑落到“K型經(jīng)濟(jì)”中代表衰退的那一側(cè)。
蘇納克表示:“就像蒸汽動(dòng)力、電力一樣,人工智能是一種通用技術(shù),它能夠也必將改變我們經(jīng)濟(jì)和社會(huì)的方方面面。面對新技術(shù),我們都經(jīng)歷過類似的周期:市場充斥著炒作,人們也容易被情緒裹挾。但我真心認(rèn)為,如果說人工智能只用工業(yè)革命一半的時(shí)間就能產(chǎn)生兩倍的影響,這樣的判斷其實(shí)已經(jīng)是相對保守的了。”
與企業(yè)領(lǐng)袖們的問答環(huán)節(jié)也頗具啟發(fā)性。大多數(shù)首席執(zhí)行官表示,他們在做出決策時(shí)需要更多支持;也有人意識到,必須對員工進(jìn)行培訓(xùn),從而共同創(chuàng)造新的高效工作方式,而不是自上而下強(qiáng)行推行。還有不少人擔(dān)心失去工作,這種擔(dān)憂有時(shí)源于認(rèn)知盲區(qū),而非真實(shí)數(shù)據(jù)。有一位創(chuàng)始人還特別提到,對那些華而不實(shí)的AI工具產(chǎn)生“虛假自信”,這是一個(gè)值得關(guān)注的問題。
蘇納克表示:“很明顯,在AI這件事上,責(zé)任不能只落在IT部門。它必須從企業(yè)領(lǐng)導(dǎo)層開始。麥肯錫(McKinsey)的研究顯示,當(dāng)領(lǐng)導(dǎo)者展現(xiàn)出明確的責(zé)任意識和投入時(shí),企業(yè)內(nèi)部的AI落地會(huì)更加成功。這并不意味著你必須具備深厚的技術(shù)背景,你不需要一夜之間變成程序員,但關(guān)鍵在于認(rèn)知和思維方式。”
“我在各地與企業(yè)交流時(shí),看到的最大錯(cuò)誤是,人們先從技術(shù)入手,然后再去為其尋找應(yīng)用場景,這完全是本末倒置。”
“最好的做法是,先審視公司業(yè)務(wù)本身,找出痛點(diǎn)所在:哪些任務(wù)讓員工感到沮喪?哪些流程拖慢了效率?又有哪些瓶頸限制了增長?從這些地方入手,往往是識別AI初始應(yīng)用場景的最佳路徑。”
在高盛的此次會(huì)議上,有一個(gè)分論壇主題是“AI——是朋友還是敵人?”當(dāng)然,答案并不是非此即彼。關(guān)鍵在于,首席執(zhí)行官們是否清楚AI能夠在哪些方面推動(dòng)增長、創(chuàng)造收入機(jī)會(huì),同時(shí)又能保留那些對企業(yè)和各部門至關(guān)重要的人類領(lǐng)導(dǎo)力與判斷力。如果所有人都以同樣的方式使用相同的AI工具,那么最終大家提供的解決方案也會(huì)趨于同質(zhì)化。而一個(gè)充斥著“AI垃圾內(nèi)容”的世界,絕非任何人的向往之地。(財(cái)富中文網(wǎng))
譯者:劉進(jìn)龍
審校:汪皓
在2024年英國大選失利后,外界曾對里希·蘇納克有一種簡單的定論:這位斯坦福MBA畢業(yè)生、前高盛(Goldman Sachs)分析師會(huì)退出議會(huì),離開英國,迅速前往加州,在某家超大規(guī)模云服務(wù)商謀得高薪高位。盡管蘇納克一再否認(rèn),但幾乎沒人相信他。他經(jīng)常穿著典型硅谷風(fēng)格的白色運(yùn)動(dòng)鞋。
兩年后的今天,蘇納克讓懷疑者大跌眼鏡。他仍然是英格蘭北部一個(gè)鄉(xiāng)村選區(qū)的議員(他甚至將AI在奶牛養(yǎng)殖中的應(yīng)用作為自己的研究重點(diǎn)之一)。同時(shí),盡管他已成為高盛、微軟(Microsoft)和Anthropic的顧問,他的工作重心依然堅(jiān)定地扎根于英國。工黨政府也經(jīng)常與他保持溝通。
在英國第二大城市伯明翰(位于倫敦以北約100英里)舉行的高盛“1萬家小企業(yè)”項(xiàng)目會(huì)議上,蘇納克表示:“我與這兩家科技公司的合作,讓我更加確信,AI不僅將帶來巨大的改變,而且變革的速度也將超出想象。”
“這不僅僅關(guān)乎改善我們的經(jīng)濟(jì)狀況——盡管這本身至關(guān)重要。我認(rèn)為,AI將抬高整個(gè)人類社會(huì)的生存底線,因?yàn)樗鼘⒆屖澜绺鞯氐拿總€(gè)人,無論身處何地,都有機(jī)會(huì)獲得金錢能買到的最優(yōu)質(zhì)的醫(yī)療和教育。我認(rèn)為,這是一股非同尋常的民主化力量。”
他對在場的眾多首席執(zhí)行官表示,AI落地應(yīng)用的速度“至關(guān)重要”。如果你沒有為“應(yīng)用型AI”(即在業(yè)務(wù)中實(shí)際應(yīng)用AI)時(shí)代做好規(guī)劃,就面臨被時(shí)代拋棄的風(fēng)險(xiǎn),并最終滑落到“K型經(jīng)濟(jì)”中代表衰退的那一側(cè)。
蘇納克表示:“就像蒸汽動(dòng)力、電力一樣,人工智能是一種通用技術(shù),它能夠也必將改變我們經(jīng)濟(jì)和社會(huì)的方方面面。面對新技術(shù),我們都經(jīng)歷過類似的周期:市場充斥著炒作,人們也容易被情緒裹挾。但我真心認(rèn)為,如果說人工智能只用工業(yè)革命一半的時(shí)間就能產(chǎn)生兩倍的影響,這樣的判斷其實(shí)已經(jīng)是相對保守的了。”
與企業(yè)領(lǐng)袖們的問答環(huán)節(jié)也頗具啟發(fā)性。大多數(shù)首席執(zhí)行官表示,他們在做出決策時(shí)需要更多支持;也有人意識到,必須對員工進(jìn)行培訓(xùn),從而共同創(chuàng)造新的高效工作方式,而不是自上而下強(qiáng)行推行。還有不少人擔(dān)心失去工作,這種擔(dān)憂有時(shí)源于認(rèn)知盲區(qū),而非真實(shí)數(shù)據(jù)。有一位創(chuàng)始人還特別提到,對那些華而不實(shí)的AI工具產(chǎn)生“虛假自信”,這是一個(gè)值得關(guān)注的問題。
蘇納克表示:“很明顯,在AI這件事上,責(zé)任不能只落在IT部門。它必須從企業(yè)領(lǐng)導(dǎo)層開始。麥肯錫(McKinsey)的研究顯示,當(dāng)領(lǐng)導(dǎo)者展現(xiàn)出明確的責(zé)任意識和投入時(shí),企業(yè)內(nèi)部的AI落地會(huì)更加成功。這并不意味著你必須具備深厚的技術(shù)背景,你不需要一夜之間變成程序員,但關(guān)鍵在于認(rèn)知和思維方式。”
“我在各地與企業(yè)交流時(shí),看到的最大錯(cuò)誤是,人們先從技術(shù)入手,然后再去為其尋找應(yīng)用場景,這完全是本末倒置。”
“最好的做法是,先審視公司業(yè)務(wù)本身,找出痛點(diǎn)所在:哪些任務(wù)讓員工感到沮喪?哪些流程拖慢了效率?又有哪些瓶頸限制了增長?從這些地方入手,往往是識別AI初始應(yīng)用場景的最佳路徑。”
在高盛的此次會(huì)議上,有一個(gè)分論壇主題是“AI——是朋友還是敵人?”當(dāng)然,答案并不是非此即彼。關(guān)鍵在于,首席執(zhí)行官們是否清楚AI能夠在哪些方面推動(dòng)增長、創(chuàng)造收入機(jī)會(huì),同時(shí)又能保留那些對企業(yè)和各部門至關(guān)重要的人類領(lǐng)導(dǎo)力與判斷力。如果所有人都以同樣的方式使用相同的AI工具,那么最終大家提供的解決方案也會(huì)趨于同質(zhì)化。而一個(gè)充斥著“AI垃圾內(nèi)容”的世界,絕非任何人的向往之地。(財(cái)富中文網(wǎng))
譯者:劉進(jìn)龍
審校:汪皓
There was a simple narrative about Rishi Sunak when he was defeated in the U.K. general election of 2024. The Stanford MBA graduate and former Goldman Sachs analyst would quit Parliament, leave the U.K., and hotfoot it to California for lucrative roles toward the top of some hyperscaler or other. Sunak kept insisting it wasn’t true, despite the fact he often wore regulation Silicon Valley white trainers. Few people believed him.
Two years later, and Sunak has confounded the skeptics. He is still a Member of Parliament for a rural constituency in the north of England (AI use for dairy farmers is one of his specialties). And although he is now an advisor to Goldman Sachs, Microsoft, and Anthropic, his work is resolutely anchored in the U.K. The Labour government is regularly in touch.
“My work with the two technology companies has left me even more convinced, not just about how much AI is going to change, but how quickly it’s going to change things, too,” Sunak told a conference hosted by the Goldman Sachs 10,000 Small Businesses programme held in Birmingham, England’s second city 100 miles north of London.
“It’s not just about transforming our economy—as much as that is important. I believe that AI is going to lift the floor for humanity, and it’s going to do that because it’s going to make it possible for everyone, no matter where they are around the world, to have access to the best health care and education that money can buy. And I think that is an extraordinary democratizing force.”
He told the room full of chief executives that speed of adoption is “everything.” If you are not planning for the era of applied AI (in use in your business), then the risk is being left behind, sitting on the wrong side of a “K-shaped economy.”
“Like steam power, like electricity, artificial intelligence is a general-purpose technology which can and will change every aspect of our economy, of our society,” Sunak said. “With new technologies, we’ve all been through these cycles. There’s lots of hype out there, and people get carried away, but I genuinely believe that it is a conservative estimate to say that artificial intelligence will have twice the impact of the Industrial Revolution in just half the time.”
The question-and-answer session with the business leaders is revealing. Most feel they need support in making decisions as CEOs. Others know they need to train their staff so that new ways of being productive can be cocreated, not ordered from above. Many fear losing their jobs, sometimes through ignorance rather than data. One founder flagged “false confidence” with splashy AI tools as worthy of note.
“It’s clear that when it comes to AI, the responsibility for it can’t sit in the IT department,” Sunak said. “It has to start with the leaders. Research from McKinsey shows that when leaders demonstrate ownership and commitment, they find that AI deployment in their organizations is far more successful. That doesn’t mean that you have to have deep technical expertise. You don’t need to become a coder overnight, but it’s about awareness, [and] it’s about mindset.
“When I go around the country talking to businesses, the single biggest mistake I see is that people start with the technology first and then try and find a use case for it, which is completely the wrong way around.
“The best thing to do is to look at your business first and figure out where the pain points are. Where are those tasks that employees are really frustrated with? Where are the processes that slow things down? Or where are the bottlenecks that are limiting your growth? That is probably the best way to identify a set of initial AI use cases.”
One of the sessions at the Goldman Sachs conference is titled “AI—friend or foe?” It’s neither, of course. The key will be a CEO’s awareness of where AI can drive growth and revenue opportunities whilst retaining the very essential human leadership and guidance that makes each business and division unique. If everyone uses the same AI tools in the same way, then everyone risks offering the same AI-led solutions. And a world of AI-slop is not where anyone wants to be.