Wall Street went into panic mode about two weeks ago after the Chinese start-up DeepSeek released an artificial intelligence system that appeared to be radically more efficient than what its American competitors had built.
Tech companies need more data centers than they have.
Many of the companies say they’re constrained by the supply of chips, land, and power needed to build data centers, and are racing to get more of them open. Microsoft, Alphabet, and Amazon all said they could have had higher cloud computing sales if they had the capacity. Cloud services are the typical way A.I. is delivered to customers.
Alphabet saw “demand that exceeds our available capacity,” Anat Ashkenazi, Alphabet’s finance chief, told investors. “So we’ll be working hard to address that and make sure we bring more capacity online.”
Microsoft has been saying it has been constrained for a while, and previously told investors that the pressure would ease early this year. But last week, when it reported its latest earnings, executives told investors that it might take until summer to get enough capacity up and running to meet the full demand. Its stock fell about 5 percent in after-hours trading after the report.
They say greater efficiency will expand the use and demand for A.I.
While many people think about data centers as the enormously expensive, power-hungry places where advanced A.I. systems are developed, they are also where A.I. is deployed. Those are two different steps: training a model that underpins ChatGPT, versus asking ChatGPT for a recipe suggestion.
Deploying A.I. is known as “inferencing” in the industry; it is where, the tech companies increasingly say, their businesses will boom.
As costs come down, “A.I. will be much more ubiquitous,” Satya Nadella, Microsoft’s chief executive, told investors last week.
Andy Jassy, Amazon’s chief executive, told investors on Thursday that while a world where every app was infused with A.I. could be hard to fathom, “this is the world we’re thinking about all the time.” That vision, he said, has inferencing at its core.
He argued that lowering the costs of inferencing would follow the pattern of previous technological trends: As the systems become less expensive to deploy, Mr. Jassy said, customers will “get excited about what else they could build that they always thought was cost-prohibitive before, and they usually end up spending a lot more in total.”
The companies say they have to think about the long haul.
Cloud providers are used to giving customers the illusion of endless supply, which means they must juggle having just enough data centers online to stream the video you want or answer your chatbot query. But they also can’t build too far in advance, locking up billions of dollars that could be deployed elsewhere. Balancing those two — particularly when securing land, chips, and power for data centers can take years — is one of the enormous challenges the companies face.
Executives have argued that they can adapt how they use the investments, between building and deploying A.I. models, and between serving their own core business and those of customers. Mr. Nadella said Microsoft’s infrastructure was “pretty fungible.” Ms. Ashkenazi said Google was also flexible. It could, for example, “repurpose capacity” to serve Google Search instead of cloud customers.
Mr. Zuckerberg said that Meta was studying DeepSeek and the ways it created efficiencies, but that investing heavily in data centers would be a strategic advantage against a small and nimble competitor.
“We serve a billion-plus people — that’s just a lot of people, so more and more of the fleet is going toward running inference,” he told employees.
Conclusion
Tech companies are committed to investing in data centers and A.I. infrastructure, despite the concerns over efficiency and profitability. They believe that the future of A.I. lies in deploying it at scale, and that the ability to do so will be a key differentiator for their companies.
In the short term, this means that investors should expect to see significant investments in data centers, as well as potential fluctuations in stock prices due to the volatility of the industry.
In the long term, the rewards could be substantial, as the companies that dominate the A.I. landscape may be those that can deploy A.I. most efficiently and at scale.
FAQs
Q: Why are tech companies investing so heavily in data centers?
A: Tech companies are investing in data centers to enable the deployment of A.I. at scale. They believe that the ability to deploy A.I. efficiently will be a key differentiator for their companies, and will enable them to grow their businesses in the long term.
Q: Is this investment necessary for the tech industry?
A: Yes, investment in data centers and A.I. infrastructure is necessary for the tech industry. The companies that can deploy A.I. efficiently and at scale will be well-positioned to dominate the market in the future.
Q: How will this impact investors?
A: Investors should expect to see significant investments in data centers, as well as potential fluctuations in stock prices due to the volatility of the industry. In the long term, the rewards could be substantial, as the companies that dominate the A.I. landscape may be those that can deploy A.I. most efficiently and at scale.
