Finance
Microsoft data center leases slowing, analysts say, raising investor attention
Published by Global Banking & Finance Review®
Posted on February 24, 2025
3 min readLast updated: January 25, 2026
Global Banking & Finance Review®
Company
Published by Global Banking & Finance Review®
Posted on February 24, 2025
3 min readLast updated: January 25, 2026
Microsoft's slowdown in data center leases raises investor concerns about AI infrastructure investments, despite ongoing $80 billion plans.
By Aditya Soni
(Reuters) -An analyst note flagging a possible slowdown by Microsoft in leasing data center capacity grabbed the market's attention on Monday, lending credence to skepticism among investors worried that the AI-led stock-market boom might be running out of steam.
TD Cowen analysts in a note Friday said the tech giant had scrapped leases for sizeable data center capacity in the United States, suggesting potential oversupply as it builds out artificial intelligence infrastructure.
The brokerage, citing its supply chain checks, said Microsoft has canceled leases totaling "a couple of hundred megawatts" of capacity with at least two private data-center operators, the analysts led by Michael Elias said.
Microsoft's plan to invest over $80 billion in AI and cloud capacity this fiscal year remains on track, a company spokesperson said. "While we may strategically pace or adjust our infrastructure in some areas, we will continue to grow strongly in all regions," the spokesperson added.
While Microsoft shares were little affected - the stock lost 1% on Monday - related companies took a hit. Shares of German firm Siemens Energy and French company Schneider Electric fell 7% and 4%, respectively.
U.S. utility companies Constellation Energy and Vistra, which provide power for data centers, lost 5.9% and 5.1%, respectively. Tech bellwethers were lower as part of a broader Nasdaq selloff.
Investor skepticism over the billions that U.S. tech firms have channeled into AI infrastructure has grown due to slow payoffs and breakthroughs at Chinese startup DeepSeek, which showcased AI tech at a much lower cost than its Western rivals.
Microsoft had also paused converting statement of qualifications, or precursors to formal leases, TD Cowen analysts said, adding that other tech firms including Meta Platforms had previously made similar moves to lower capital spending.
"I don't construe it as any change up in the big macro picture. Their desire is to build out these data centers," said Dan Morgan, senior portfolio manager at Synovus Trust, which owns shares in Microsoft.
Any lease cancellations would mark a sharp shift for Microsoft, which has been spending billions of dollars on data centers to overcome supply bottlenecks that have limited its ability to meet AI demand.
The news could possibly indicate lower demand, Bernstein analyst Mark Moelder said, especially after lackluster quarterly results from major cloud companies, but it was also reflective of the capacity build-up at Microsoft in the past years.
"Microsoft needed to meet demand and had a great deal of difficulty finding capacity. Management may, therefore, have rented, even at a meaningful premium, data centers and GPU capacity and negotiated more deals for additional future capacity than they needed," Moelder added.
(Reporting by Aditya Soni in Bengaluru; Additional reporting by Juby Babu in Mexico City; Editing by Sriraj Kalluvila and Shounak Dasgupta)
Microsoft has reportedly scrapped leases for a significant amount of data center capacity in the United States, indicating a potential oversupply.
Microsoft's stock lost 1% on Monday, while related companies like Siemens Energy and Schneider Electric saw declines of 7% and 4%, respectively.
Analysts suggest that the cancellations could indicate lower demand for data center capacity, particularly following disappointing quarterly results from major cloud companies.
Despite the lease cancellations, Microsoft plans to invest over $80 billion in AI and cloud capacity this fiscal year, according to a company spokesperson.
Microsoft has struggled to find sufficient capacity to meet AI demand, leading to high costs for renting data centers and GPU capacity.
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