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There is one notable corner of the tech world that has not been touched by the artificial intelligence euphoria sweeping through the stock market.
科技界有一個值得注意的角落，尚未被席捲股市的人工智慧熱潮所觸及。
If generative AI really does represent the next great sales opportunity for the tech industry, then software companies ought to be among the biggest winners. After all, most AI is likely to show up as enhanced features in the business software that companies rely on in their daily operations.
如果生成式人工智慧真的代表了科技行業下一個巨大的銷售機會，那麼軟體公司應該是最大的贏家之一。畢竟，大多數人工智慧都可能以增強功能的形式出現在企業日常運營所依賴的商業軟體中。
However, the BVP Nasdaq index of cloud software companies is down nearly 10 per cent this year, while the Nasdaq Composite is up more than 20 per cent. It has also halved from its pandemic-era peak. The slump points to an industry at a crossroads. A long, secular growth phase driven by the rise of the cloud looks like it is entering a new and more mature state, while the next (the spread of generative AI in business) has barely begun.
然而，BVP那斯達克(Nasdaq)雲軟體公司指數今年下跌近10%，而那斯達克綜合指數上漲超過20%。它也從疫情時期的峯值下降了一半。這種下滑表明該行業正處於十字路口。由雲端計算崛起驅動的長期成長階段似乎正在進入一個新的、更成熟的狀態，而下一個（商業中生成式人工智慧的傳播）幾乎剛剛開始。
At times like this, Wall Street faces complex questions. If the cloud business really is maturing, the focus of investors needs to shift more quickly from growth to value. Tech companies that recently reported disappointing results, such as Salesforce, MongoDB and Workday, have tried to pass the lull off as the result of extended economic weakness. But the longer it goes on, the harder this argument is to sustain. Salesforce’s revenues doubled in the past four years to $36bn: at that scale, the slower 10 per cent growth it has projected for next year begins to look more like the norm.
在這種時候，華爾街面臨著複雜的問題。如果雲端業務真的成熟了，投資者的關注重點就需要更快地從成長轉向價值。最近發佈令人失望的業績的科技公司，如Salesforce、MongoDB和Workday，試圖將低迷歸咎於經濟疲軟的延續。但是，隨著時間的推移，這個論點越來越難以維持。Salesforce的收入在過去四年翻了一番，達到了360億美元：在這個規模下，預計明年成長10%的速度開始看起來更像是正常水準。
At the same time, investors have to handicap which companies will catch the next wave of growth and which will fail to adapt and be left in the dust.
同時，投資者必須評估哪些公司將抓住下一波成長機遇，哪些公司將無法適應並被拋在後頭。
According to the companies themselves, the lack of an impact on their sales from AI is just a timing issue. Salesforce chief executive Marc Benioff, for instance, points to the challenge of training large armies of salespeople to handle what he calls “a harder, more complex sell”. Customers are grappling with a wide set of questions, seeking to understand how the new AI models work and how their workers should interact with them. They also need to consider how to redesign their work processes to make best use of the technology, as well as deal with new threats to the security of their data.
根據這些公司自己的說法，人工智慧對他們的銷售沒有產生影響只是一個時間問題。例如，Salesforce首席執行長馬克•貝尼奧夫(Marc Benioff)指出，培訓大批銷售人員來處理他所稱的「更加困難、更加複雜的銷售」是一個挑戰。客戶們正在努力解決一系列問題，試圖理解新的人工智慧模型如何工作以及他們的員工應該如何與之互動。他們還需要考慮如何重新設計工作流程以充分利用這項技術，並應對對數據安全的新威脅。
Even if sales are still negligible, the software companies report huge interest from customers in piloting their new AI services. This may mean the AI dividend has just been delayed.
即使銷售額仍然微不足道，軟體公司報告稱客戶對試點其新的人工智慧服務表現出了巨大的興趣。這可能意味著人工智慧紅利只是被推遲了。
Yet the disruptive threats from AI suggest things will not be so straightforward. One is the upheaval to the cloud companies’ business model. Most rely on charging per-seat subscriptions, meaning their revenue goes up in line with the number of workers using their services. If generative AI works as promised and makes workers far more productive, customers should be able to do more with fewer staff.
然而，人工智慧帶來的顛覆性威脅表明事情不會那麼簡單。其中一個是對雲端計算公司商業模式的顛覆。大多數公司依賴按用戶訂閱收費，這意味著他們的收入與使用他們服務的員工數量成正比。如果生成式人工智慧如所承諾的那樣提高工人的生產力，客戶應該能夠用更少的員工做更多的事情。
The result has been a pivot towards consumption-based pricing, or charging based on how much the new services are actually used. Tying fees to usage has the added advantage of offsetting some of the higher cost of delivering generative AI. But unless this leads to real and demonstrable business benefits, the software companies could face a backlash when customers see their bills soar.
結果是轉向基於消費的定價，即根據新服務的實際使用情況收費。將費用與使用量掛鉤的額外優勢是抵消了提供生成式人工智慧的更高成本。但是，除非這導致了真實可證明的商業利益，否則軟體公司可能會面臨客戶看到賬單飆升時的強烈反對。
The software groups also have tech history to contend with. In the past, new tech eras — such as the rise of client-server computing in the 1990s and cloud computing the following decade — have brought new waves of start-up software companies to the fore. New companies, their products and business models designed from the ground up to fit a new computing paradigm start with a big advantage.
軟體團隊還需要應對技術歷史。過去，新的技術時代，比如上世紀90年代的客戶端-伺服器計算和接下來的雲端計算，都帶來了新一波的新創軟體公司。新公司、他們的產品和商業模式從頭開始設計，以適應新的計算範式，從一開始就具有巨大的優勢。
The first wave of these “AI native” software companies has often looked like little more than “wrappers” around the large language models, adding only a veneer of industry-specific expertise as they offer businesses ways to adopt generative AI. But they are all working hard to gain a foothold from where they can start to build out more compelling services.
這些「AI原生」軟體公司的第一波往往看起來只是大型語言模型的「包裝」，只是在提供企業採用生成式人工智慧的方式時新增了一層行業特定的專業知識的外觀。但他們都在努力爭取一個立足點，從那裏開始構建更具吸引力的服務。
According to Salesforce’s Benioff, the incumbents will be hard to unseat. Companies such as his have become the repositories of their customers’ most important data, he says, giving them a big advantage when it comes to training the AI models that businesses will find truly useful.
根據Salesforce的貝尼奧夫所說，現有的公司將很難被取代。他說，像Salesforce這樣的公司已經成爲客戶最重要數據的存儲庫，這使得他們在培訓企業真正有用的AI模型時具有很大優勢。
That will only count if today’s cloud companies can adapt their own products and processes to the new technology fast enough. For now, Wall Street is suspending judgment.
但前提是，今天的雲端計算公司必須儘快讓自己的產品和流程適應新技術。目前，華爾街暫不做出判斷。