Alphabet and Microsoft Signal Robust AI Demand Amid Escalating Infrastructure Investment

Alphabet and Microsoft posted quarterly results Wednesday that underscored accelerating demand for artificial intelligence services, even as both technology giants funneled billions into the infrastructure required to sustain that growth.

Google parent Alphabet projected capital expenditures of $195 billion to $205 billion for the current year, with spending expected to rise significantly in 2027. The company reported third-quarter revenue of $127.6 billion, a 25% increase year over year. Google Cloud revenue more than doubled to $30.7 billion, representing a 103% jump.

Google headquarters in Mountain View, California following Warren Buffett’s big investment. (Marlena Sloss/Bloomberg via Getty Images / Getty Images)

“Our AI infrastructure and solutions are the major drivers for Cloud growth, and our customers see us as the leading provider here, so there’s huge demand,” Alphabet CEO Sundar Pichai said on the earnings call. “We are working hard to bring more capacity online to meet this long-term demand.”

Alphabet spent approximately $51.4 billion on capital expenditures during the quarter, more than double the year-ago figure, with the bulk directed toward technical infrastructure supporting AI and cloud operations. Chief Financial Officer Anat Ashkenazi cautioned that Google Cloud could face near-term margin pressure as the company leans on third-party computing capacity to keep pace with demand.

Microsoft CEO Satya Nadella speaks at the Microsoft Build 2025, conference in Seattle, Washington on May 19, 2025. (Jason Redmond/AFP via Getty Images / Getty Images)

Microsoft similarly highlighted strong AI-driven momentum, with fiscal first-quarter revenue climbing 19% to $92.3 billion. Microsoft Cloud revenue rose 30% to $63.9 billion, while Azure cloud services grew 48%. The company’s commercial remaining performance obligation—a gauge of contracted future revenue not yet recognized—surged 73% to $677 billion.

The results illustrate the dual challenge confronting both firms: capturing surging AI demand while managing the immense costs of building the infrastructure to support it.

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