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. 

“The forecast assumes continued investment in AI infrastructure expansion, as major hyperscalers continue to increase investments in data centers with AI-optimized hardware and GPUs to scale their services,” said John-David Lovelock, Distinguished VP Analyst at Gartner. “The AI investment landscape is also expanding beyond traditional U.S. tech giants, including Chinese companies and new AI cloud providers (like Oracle). Furthermore, venture capital investment in AI providers is providing additional tailwinds for AI spending.”Looking towards 2026, overall global AI spending is forecast to top $2 trillion, led in large part by AI being integrated into products such as smartphones and PCs, as well as infrastructure (see Table 1).
Table 1: AI Spending in IT Markets, Worldwide, 2024-2026 (Millions of U.S. Dollars)

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.

Enterprise Adoption:

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. 

Consumer Device Integration:

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. 

Hardware Dominance:

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. 

Infrastructure Expansion:
Continued investment is anticipated for the expansion of AI infrastructure (cloud resident data centers with AI optimized compute servers and ultra-fast interconnects), supporting the increasing demand for AI services and capabilities.
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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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Postscript: November 23, 2025:

In this new AI era, consumers and workers are not what drives the economy anymore. Instead, it’s spending on all things AI, mostly with borrowed money or circular financing deals.

BofA Research noted that Meta and Oracle issued $75 billion in bonds and loans in September and October 2025 alone to fund AI data center build outs, an amount more than double the annual average over the past decade. They warned that “The AI boom is hitting a money wall” as capital expenditures consume a large portion of free cash flow. Separately, a recent Bank of America Global Fund Manager Survey found that 53% of participating fund managers felt that AI stocks had reached bubble proportions. This marked a slight decrease from a record 54% in the prior month’s survey, but the concern has grown over time, with the “AI bubble” cited as the top “tail risk” by 45% of respondents in the November 2025 poll.

JP Morgan Chase estimates up to $7 trillion of AI spending will be with borrowed money. “The question is not ‘which market will finance the AI-boom?’ Rather, the question is ‘how will financings be structured to access every capital market?’ according to strategists at the bank led by Tarek Hamid.

As an example of AI debt financing, Meta did a $27 billion bond offering. It wasn’t on their balance sheet. They paid 100 basis points over what it would cost to put it on their balance sheet. Special purpose vehicles happen at the tail end of the cycle, not the early part of the cycle, notes Rajiv Jain of GQG Partners.

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