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Google CEO Sundar Pichai Bets $75B on AI Data Centers—Is This the Next Big Tech Gold Rush?

Google CEO Sundar Pichai Bets $75B on AI Data Centers—Is This the Next Big Tech Gold Rush?

Published:
2025-07-09 14:30:14
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Google’s Pichai committed $75 billion in AI data centres

Google just dropped a $75 billion bomb on the AI arms race—and Wall Street's already placing bets on who blinks first.


The AI Infrastructure Play

Pichai's all-in move into data centers isn't just about computing power—it's a land grab for the next decade of machine learning dominance. With this cash injection, Google's effectively building the railroads of the AI economy.


Follow the Money

That $75B could buy you three Ethereum networks at current prices—or one very expensive poker chip in Big Tech's high-stakes game. Meanwhile, crypto VCs are suddenly very interested in 'AI-adjacent' blockchain projects.


The Bottom Line

When tech giants throw around numbers that dwarf national GDPs, either we're witnessing genius—or the dot-com bubble wearing AI drag. Either way, the cloud just got a lot more expensive.

Google’s Pichai committed $75 billion in AI data centres

Despite uncertainties surrounding US tariffs, Google said in April it would allocate $75 billion this year to scale up its data center capacity. Ideally, the company hoped it could calm investor concerns and show that its AI plans were accruing solid returns.

At the Google Cloud Next 25 in Las Vegas, Alphabet CEO Sundar Pichai also affirmed that this investment WOULD bolster enterprise customers’ expanding AI demands and strengthen Google’s core services. He added that the company will work on building infrastructure that moves at Google speed, with near-zero latency, to support services like search, Gmail, and Photos for billions of users worldwide.

Although Google is not backing down from AI, its competitors have lessened their AI investments. Microsoft, which had previously pledged to spend over $80 billion on AI infrastructure in 2025, has since pulled the plug on certain data center developments in the US and Europe.

Abhivyakti Sengar, practice director at Everest Group, commented on the matter, saying he noticed a shift in the hyperscale strategy. He argued that although Google maintains its AI-first focus, Microsoft is now signaling a more regionally targeted and cautious strategy, which could influence other enterprises’ decisions.

Meanwhile, OpenAI recently revealed it will build its data center capacity to cut down on its dependence on other cloud providers and augment its computing capabilities.

Google started its roll-out of AI Mode in India

On Tuesday, Pichai revealed that the company began its launch of its ‘AI Mode’ for users in India. The feature generates AI responses into a similar Google Search interface, offering AI-generated answers within the familiar Google Search layout. AI Mode is set to provide detailed and informative responses rather than just links, though so far, it’s only available in English. Besides, it allows users to ask single, multi-part questions instead of running multiple searches.

Initially, the feature was available on search labs in June during its testing phase. After receiving positive input, Google has now expanded access, with no sign-up required. 

Analyst warns companies could go wrong by spending too much on AI

Google is not the only company still fixated on AI; other startups and corporations still want to be a part of the incoming revolution. Chris V. Nicholson, an investor with the venture capital firm Page One Ventures, explained that most companies diving into AI technologies are just afraid of being left behind.

Some AI experts have cited the massive risks of investing in AI, especially given how costly it can be to build its infrastructure without knowing if it will live up to expectations. However, some believe the bigger risk lies with not maintaining a competitive edge with your rivals, seeing that you could lose your standing.

Jordan Jacobs, a partner with venture capital firm Radical Ventures, cautions that companies could go wrong by spending too much on AI and not just with the case of too little.

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