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There’s one notable corner of the tech world that hasn’t been touched by the AI ​​euphoria sweeping the stock market.
If generative AI is indeed the next big sales opportunity for the tech industry, then software companies should be among the biggest winners. After all, most AI is likely to manifest itself as enhanced features in the enterprise software that companies rely on for their day-to-day operations.
But the Nasdaq GDP index of cloud software companies is down nearly 10 percent this year, while the Nasdaq Composite is up more than 20 percent. It has also halved since its pandemic-era peak. The slump points to an industry at a crossroads. The long, secular phase of growth fueled by the rise of the cloud looks like it has entered a new and more mature state, while the next (the spread of generative AI in business) has barely begun.
At times like these, Wall Street faces difficult questions. If the cloud business is truly maturing, investors’ attention must shift more quickly from growth to value. Tech companies that have recently reported disappointing results, such as Salesforce, MongoDB and Workday, have tried to lay low due to prolonged economic weakness. But the longer it goes on, the harder it is to maintain that argument. Salesforce’s revenue has doubled to $36 billion over the past four years: by this scale, the slower 10 percent growth it predicts for next year is starting to look more like the norm.
At the same time, investors have to handicap which companies will capture the next wave of growth and which companies will fail to adapt and fall into the dust.
According to the companies themselves, the lack of impact on their sales from AI is just a matter of timing. Salesforce CEO Marc Benioff, for example, points to the challenge of training large armies of salespeople to handle what he calls “harder, more complex selling.” Customers are grappling with a wide range of questions as they try to understand how new AI models work and how their workers should interact with them. They must also consider how to redesign their work processes to make the most of technology, as well as deal with new threats to the security of their data.
Although sales are still negligible, software companies are reporting huge customer interest in piloting their new AI services. This may mean that the AI ​​dividend has just been delayed.
Still, disruptive threats from AI suggest things won’t be so straightforward. One of them is the upheaval of the business model of cloud companies. Most rely on subscription fees per seat, meaning their revenue grows in line with the number of workers using their services. If generative AI works as promised and makes workers much more productive, customers should be able to do more with fewer employees.
The result has been a turn towards consumption-based pricing, or charging based on how much new services are actually used. Tying fees to usage has the added benefit of offsetting some of the higher costs of providing generative AI. However, if this does not lead to real and demonstrable business benefits, software companies may face a backlash as customers see their bills rise.
Software groups also have a technical history to contend with. In the past, new technological eras—such as the rise of client-server computing in the 1990s and cloud computing in the following decade—brought new waves of software startups. New companies, their products and business models designed from the ground up to fit the new computing paradigm, are off to a great start.
The first wave of these “native” software companies often looked like little more than “wrappers” around big language models that only added a veneer of industry-specific expertise as they offered businesses ways to adopt generative AI. However, they are all working hard to gain a foothold from where they can start building more impressive services.
According to Salesforce’s Benioff, it will be difficult to unseat incumbents. Companies like his have become the repository of their customers’ most important data, he says, giving them a big advantage when it comes to training AI models that businesses will find truly useful.
This will only be true if today’s cloud companies can adapt their own products and processes to the new technology quickly enough. Wall Street is withholding judgment for now.
richard.waters@ft.com