The cloud over cloud companies - FT中文网
登录×
电子邮件/用户名
密码
记住我
请输入邮箱和密码进行绑定操作:
请输入手机号码,通过短信验证(目前仅支持中国大陆地区的手机号):
请您阅读我们的用户注册协议隐私权保护政策,点击下方按钮即视为您接受。
FT商学院

The cloud over cloud companies

The sector has been left behind in the euphoria over artificial intelligence sweeping through the stock market

There is one notable corner of the tech world that has not been touched by the artificial intelligence euphoria sweeping through the stock market.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

richard.waters@ft.com

版权声明:本文版权归FT中文网所有,未经允许任何单位或个人不得转载,复制或以任何其他方式使用本文全部或部分,侵权必究。

风向逆转:生活成本负担能力问题让特朗普陷入困境

美国总统将生活成本负担能力问题斥为“骗局”,遭遇民众的强烈反弹。

低增长已成为欧洲最大的金融稳定风险

欧洲最大的金融稳定风险已不再是银行,而是低增长本身。只有实现更强劲的增长,欧洲才能保持安全、繁荣与战略自主。

好莱坞导演罗伯•莱纳夫妇遇害,儿子尼克被捕

洛杉矶警方正在调查《摇滚万万岁》导演罗伯•莱纳遇害一案。莱纳生前除影坛成就外,也因长期投身民权事业而备受政界与娱乐圈人士称赞。
14小时前

“稳定币超级周期”为什么可能重塑银行业?

一些技术专家认为,未来五年内,稳定币支付系统的数量将激增至十万种以上。

一周展望:英国央行会在圣诞节前降息吗?

与此同时,投资者一致认为,欧洲央行本周将把基准利率维持在2%。而推迟发布的美国就业数据将揭示美国劳动力市场处于何种状态。

“布鲁塞尔效应”如何适得其反

曾被视为全球典范的欧盟立法机器,如今却在自身抱负的重压下步履蹒跚。
设置字号×
最小
较小
默认
较大
最大
分享×