Gartner: AI spending >$2 trillion in 2026 driven by hyperscalers data center investments
According to Gartner, global AI spending will reach close to US$1.5 trillion this year and will top $2 trillion in 2026 as ongoing demand fuel IT infrastructure investment. This significant growth is driven by hyperscalers’ ongoing investments in AI-optimized data centers and hardware, such as GPUs, along with increased enterprise adoption and the integration of AI into consumer devices like smartphones and PCs.
| Market | 2024 | 2025 | 2026 |
| AI Services | 259,477 | 282,556 | 324,669 |
| AI Application Software | 83,679 | 172,029 | 269,703 |
| AI Infrastructure Software | 56,904 | 126,177 | 229,825 |
| GenAI Models | 5,719 | 14,200 | 25,766 |
| AI-optimized Servers (GPU and Non-GPU AI Accelerators) | 140,107 | 267,534 | 329,528 |
| AI-optimized IaaS | 7,447 | 18,325 | 37,507 |
| AI Processing Semiconductors | 138,813 | 209,192 | 267,934 |
| AI PCs by ARM and x86 | 51,023 | 90,432 | 144,413 |
| GenAI Smartphones | 244,735 | 298,189 | 393,297 |
| Total AI Spending | 987,904 | 1,478,634 | 2,022,642 |
Source: Gartner (September 2025)
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Hyperscaler Investments:
Cloud service providers are heavily investing in data centers and AI-optimized hardware to expand their services at scale. Amazon, Google and Microsoft are all ploughing massive sums into their cloud infrastructure, while reaping the benefits of AI-driven market growth, as Canalys’s latest data showed last week.
Businesses are increasingly investing in AI infrastructure and services, though there’s a shift towards using commercial off-the-shelf solutions with embedded GenAI features rather than solely developing custom solutions.
A growing number of consumer products, including smartphones and PCs, are incorporating AI capabilities by default, contributing to the overall spending growth. IDC forecasts GenAI smartphones* to reach 54% of the market by 2028, while Gartner projects nearly 100% of premium models to feature GenAI by 2029, driving significant increases in both shipments and end-user spending.
* A GenAI smartphone is a a mobile device featuring a system-on-a-chip (SoC) with a powerful Neural Processing Unit (NPU) capable of running advanced Generative Artificial Intelligence (GenAI) models directly on the device. It enables features like content creation, personalized assistants, and real-time task processing without needing constant cloud connectivity. These phones are designed to execute complex AI tasks faster, more efficiently, and with enhanced privacy compared to standard smartphones that rely heavily on the internet for such functions.
AI hardware, particularly GPUs and other AI accelerators, accounts for a substantial portion of the growth, with hyperscaler spending on these components nearly doubling, according to a story at CIO Drive.
About Gartner AI Use Case Insights:
Gartner AI Use Case Insights is an interactive tool that helps technology and business leaders efficiently discover, evaluate, and prioritize AI use cases to potentially pursue. Clients can search over 500 use cases (applications of AI in specific industries) and over 380 case studies (real world examples) based on industry, business function, and Gartner’s assessment of potential business value.
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3 thoughts on “Gartner: AI spending >$2 trillion in 2026 driven by hyperscalers data center investments”
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Like other large tech companies, Google is pouring tens of billions of dollars into AI development. It lifted its estimates for capital expenditures this year to a range of $91 billion to $93 billion, up from $52.5 billion in 2024.
The company said it expects a substantial increase in capital expenditures next year. Much of the money will be used to build data centers to develop and run AI models.
Google’s cloud division, which sells computing power to data centers, has grown as a result of the race to develop AI. The cloud unit had $15.2 billion in quarterly revenue, up 34% from the same quarter last year.
“The gen AI paradox”:
In a June 2025 study by consulting firm McKinsey, almost 80% of companies reported using generative A.I., but about the same number reported that the tools had not significantly affected their earnings. At the heart of this paradox is an imbalance between “horizontal” (enterprise-wide) copilots and chatbots—which have scaled quickly but deliver diffuse, hard-to-measure gains—and more transformative “vertical” (function-specific) use cases—about 90% of which remain stuck in pilot mode.
https://www.mckinsey.com/capabilities/quantumblack/our-insights/seizing-the-agentic-ai-advantage
It’s unlikely that big established companies will be able to substitute A.I. for large numbers of workers over the next year or two. One reason is that big companies are by their nature plodding and bureaucratic when reimagining their work processes. The McKinsey report observed that many companies’ flirtation with A.I. had involved “a proliferation of disconnected micro-initiatives” that suffered from “limited coordination.” A study released this summer by researchers at M.I.T. reached a similar conclusion, finding that industries other than technology and media showed “little structural change” as a result of A.I.
https://www.nytimes.com/2025/11/07/business/layoffs-ai-replacement.html
From Nov 8, 2025 NY Times:
According to an investor offering sheet obtained by DealBook, Blackstone is on the cusp of closing a $3.46 billion commercial-mortgage-backed securities (C.M.B.S.) offering to refinance debt held by QTS, the biggest player in the artificial intelligence infrastructure market. It would be the largest deal of its type this year in a fast-accelerating market. (Blackstone declined to comment.)
The bonds would be backed by 10 data centers in six markets (including Atlanta, Dallas and Norfolk, Va.) that together consume enough energy to power Burlington, Vt., for half a decade.
Blackstone’s offering is part of the latest push in the A.I. infrastructure financing blitz. According to McKinsey, $7 trillion in data center investment will be required by 2030 to keep up with projected demand. Google, Meta, Microsoft and Amazon have together spent $112 billion on capital expenditures in the past three months alone.
The sheer scale of spending is spooking investors: Meta’s stock tumbled 11 percent after the company revealed its aggressive capital expenditure plans last week, and tech stocks have sold off this week on overvaluation fears.
Now, the tech giants are turning to financing maneuvers that may add to the risk. To obtain the capital they need, hyperscalers have leveraged a growing list of complex debt-financing options, including corporate debt, securitization markets, private financing and off-balance-sheet vehicles. That shift is fueling speculation that A.I. investments are turning into a game of musical chairs whose financial instruments are reminiscent of the 2008 financial crisis.
Big tech companies are looking for new sources of financing. While Meta, Microsoft, Amazon and Google previously relied on their own cash flow to invest in data centers, more recently they’ve turned to loans. To diversify their debt, they’re repackaging much of it as asset-backed securities (A.B.S.). About $13.3 billion in A.B.S. backed by data centers has been issued across 27 transactions this year, a 55 percent increase over 2024.
If investors want to buy data center A.B.S., they have two options, according to Sarah McDonald, a senior vice president in the capital solutions group at Goldman Sachs: They can invest in a data center that has one tenant, like a hyperscaler, or in a co-location data center, which has thousands of smaller tenants. The former is an investment-grade tenant with a long-term lease, but the risk is highly concentrated; the latter is most likely renting out to noninvestment-grade tenants with short-term leases, but the investment is extremely diversified.
Digital infrastructure “is something that investors have a huge appetite for,” McDonald said.
Despite the increase in popularity, data center securities are just a small slice of the A.B.S. market, which is dominated by credit card, auto, consumer and student loans.
Blackstone’s $3.46 billion C.M.B.S. offering may seem like small potatoes compared with some other debt-fueled deals, such as Meta’s $30 billion corporate offering to finance its data center in Louisiana. But it’s unprecedented for the C.M.B.S. market, where issuance for data-center-backed deals was just $3 billion for all of 2024.
“They realize how much cash they’re going to need, so they’re getting the C.M.B.S. market comfortable with this type of asset,” said Dan McNamara, the founder and chief investment officer of Polpo Capital, a hedge fund that focuses on C.M.B.S. He added that while most traders in the market were well versed in assets like office space or industrial buildings, with data centers, “it’s not traditional ‘bricks and sticks’ commercial real estate.”
To complicate matters further, the share of single-asset-single-borrower securities (S.A.S.B.) — for example, the assets inside the bond being sold are all from the same company or a single data center — is rising, with 13 percent of all S.A.S.B. deals coming from data centers, according to Goldman Sachs.
“It’s one company, and these assets are quite similar. If there’s a problem with A.I. data centers, like if their current chips are obsolete in five years, you could have big losses in these deals,” McNamara said. “That’s the knock on S.A.S.B.: When things go bad, they go really bad.”
https://www.nytimes.com/2025/11/08/business/dealbook/debt-has-entered-the-ai-boom.html