Google Looking To Spend Nearly $2 Trillion On AI Infrastructure Over A Decade: Report

• According to Chief Technologist Amin Vahdat, Google might spend up to $1.9 trillion on AI infrastructure over the next ten years.
• The firm is adding more data centers, in-house TPUs, and energy capacity. 
• At the same time, it is giving its proprietary chips to more and more outside customers via cloud services.

According to Amin Vahdat, Google's (GOOGL) Chief Technologist for AI infrastructure, the company's long-term bet on AI could lead to almost $2 trillion in infrastructure spending over the next ten years. 

Vahdat told Forbes that the tech giant's current investment rate, at $175 billion to $185 billion in capital expenditures this year, could persist for several years. 

He pointed out that, at current spending levels, comparable amounts could eventually amount to a "significant investment," even though he stressed that these numbers are not an official commitment. “If there’s a 10-year horizon… one could imagine, assuming it’s not going to go down, that this could extend to some big number,” Vahdat told Forbes on Sunday.

At the high end of that range, Google's yearly investment may reach $1.5 trillion over eight years and roughly $1.9 trillion over a decade.

TPUs, Data Centers And Energy

Google's investment plan includes data center growth, customized semiconductor development, and energy acquisition. The firm is continuing to expand its in-house Tensor Processing Units (TPUs), which are increasingly being made available to external clients via the cloud platform. 

Previously, Google CEO Sundar Pichai said, “We’re seeing our AI investments and infrastructure drive revenue and growth across the board,” while Alphabet expected to spend around $185 billion this year alone.

Alphabet Inc. Class A shares were up 0.5% in after-hours trading. On Stocktwits, retail sentiment around GOOGL remained in ‘Extremely Bearish’ territory, as chatter levels remained ‘low’ over the past day.

 

Vahdat also said that one of the company's top focuses is to reimagine how data centers are created, transitioning to more modular and repeatable designs that can be deployed internationally at scale. The change is intended to shorten building timeframes while meeting the rising demand for computing capability.

As AI leaders race to build infrastructure for next-generation models, investment pressure intensifies. Demand has also boosted chipmakers like Nvidia (NVDA), whose price has risen substantially with the AI growth.

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