AI spending boom accelerates: Big tech to invest an aggregate of $400 billion in 2025; much more in 2026!

The biggest U.S. mega-cap tech companies are on track to invest an aggregate of $400 billion into artificial intelligence (AI) initiatives this year, a commitment they collectively indicate “is nowhere near enough.”  Meta, Alphabet, Microsoft, and Amazon all have announced further AI spending increases in 2026. The investment community reacted favorably to the plans presented by Google and Amazon late this past week, though some apprehension was noted regarding the strategies outlined by Meta and Microsoft.
  • Meta Platforms says it continues to experience capacity constraints as it simultaneously trains new AI models and supports existing product infrastructure.  Meta CEO Mark Zuckerberg described an unsatiated appetite for more computing resources that Meta must work to fulfill to ensure it’s a leader in a fast-moving AI race. “We want to make sure we’re not underinvesting,” he said on an earnings call with analysts Wednesday after posting third-quarter results. Meta signaled in the earnings report that capital expenditures would be “notably larger” next year than in 2025, during which it expects to spend as much as $72 billion. He indicated that the company’s existing advertising business and platforms are operating in a “compute-starved state.” This condition persists because Meta is allocating more resources toward AI research and development efforts rather than bolstering existing operations.
  • Microsoft reported substantial customer demand for its data-center-driven services, prompting plans to double its data center footprint over the next two years. Concurrently, Amazon is working aggressively to deploy additional cloud capacity to meet demand.  Amy Hood, Microsoft’s chief financial officer, said: “We’ve been short [on computing power] now for many quarters. I thought we were going to catch up. We are not. Demand is increasing.” She further elaborated, “When you see these kinds of demand signals and we know we’re behind, we do need to spend.”
  • Alphabet (Google’s parent company) reported that capital expenditures will jump from $85 billion to between $91 billion and $93 billion. Google CFO Anat Ashkenazi said the investments are already yielding returns: “We already are generating billions of dollars from AI in the quarter. But then across the board, we have a rigorous framework and approach by which we evaluate these long-term investments.” 
  • Amazon has not provided a specific total dollar figure for its planned AI investment in 2026. However, the company has announced it expects its total capital expenditures (capex) in 2026 to be even higher than its 2025 projection of $125 billion, with the vast majority of this spending dedicated to AI and related infrastructure for Amazon Web Services (AWS).
  • Apple: Announced it is also increasing its AI investments, though its overall spending remains smaller in comparison to the other tech giants.

As big as the spending projections were this week, they look pedestrian compared with OpenAI, which has announced roughly $1 trillion worth of AI infrastructure deals of late with partners including Nvidia , Oracle and Broadcom.

Despite the big capex tax write-offs (due to the 2025 GOP tax act) there is a large degree of uncertainty regarding the eventual outcomes of this substantial AI infrastructure spending. The companies themselves, along with numerous AI proponents, assert that these investments are essential for machine-learning systems to achieve artificial general intelligence (AGI), a state where they surpass human intelligence.

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Youssef Squali, lead internet analyst at Truist Securities, states: “Whoever gets to AGI first will have an incredible competitor advantage over everybody else, and it’s that fear of missing out that all these players are suffering from. It’s the right strategy. The greater risk is to underspend and to be left with a competitive disadvantage.”
Yet skeptics question whether investing billions in large-language models (LLMs), the most prevalent AI system, will ultimately achieve that objective. They also highlight the limited number of paying users for existing technology and the prolonged training period required before a global workforce can effectively utilize it.
During investor calls following the earnings announcements, analysts directed incisive questions at company executives. On Microsoft’s call, one analyst voiced a central market concern, asking: “Are we in a bubble?” Similarly, on the call for Google’s parent company, Alphabet, another analyst questioned: “What early signs are you seeing that gives you confidence that the spending is really driving better returns longer term?”
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Big Tech AI Investment Comments and Quotes:

Google, which projected a rise in its full-year capital expenditures from $85 billion to a range of $91 billion to $93 billion, indicated that these investments were already proving profitable.  Google’s Ashkenazi stated: “We already are generating billions of dollars from AI in the quarter. But then across the board, we have a rigorous framework and approach by which we evaluate these long-term investments.”

Microsoft reported that it expects to face capacity shortages that will affect its ability to power both its current businesses and AI research needs until at least the first half of the next year. The company noted that its cloud computing division, Azure, is absorbing “most of the revenue impact.”

Amazon informed investors of its expedited efforts to bring new capacity online, citing its ability to immediately monetize these investments.
“You’re going to see us continue to be very aggressive in investing capacity because we see the demand,” said Amazon Chief Executive Andy Jassy. “As fast as we’re adding capacity right now, we’re monetizing it.”
Meta did not provide new details on AI model release or product timelines, nor did it specify when investors might see a broader return on their investments, which unsettled some investors. CEO Zuckerberg told analysts that the company would simply pivot if its spending on achieving AGI is proven incorrect. “I think it’s the right strategy to aggressively front load building capacity. That way, we’re prepared for the most optimistic case. In the worst case, we would just slow building new infrastructure for some period while we grow into what we build.”
Meta’s chief financial officer, Susan Li, stated that the company’s capital expenditures—which have already nearly doubled from last year to $72 billion this year—will grow “notably larger” in 2026, though specific figures were not provided.
Apple confirmed during its earnings call it is also increasing investments in AI . However, its total spending levels remain significantly lower compared to the outlays planned by the other major technology firms.
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Skepticism and Risk: 

While proponents argue the investments are necessary for AGI and offer a competitive advantage, skeptics question if huge spending (capex) on AI infrastructure and large-language models will achieve this goal and point to limited paying users for current AI technology.  Meta CEO Zuckerberg addressed this by telling investors the company would “simply pivot” if its AGI spending strategy proves incorrect.

The mad scramble by mega tech companies and Open AI to build AI data centers is largely relying on debt markets, with a slew of public and private mega deals since September. Hyperscalers would have to spend 94% of operating cash flow to pay for their AI buildout themselves and are turning to debt investors to help defray some of that cost, according to Bank of America. Deals so far this year have raised almost as much money as all debt financings done between 2020 and 2024, the BofA research said.

In bubbles, everyone gets caught up in the idea that spending on the hot theme will deliver vast profits — eventually. When the bubble is big enough, it shifts the focus of the market as a whole from disliking capital expenditure, and hating speculative capital spending in particular, to loving it.  That certainly seems the case today with surging AI spending.  For much more, please check-out the References below.

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