Google Is Spending Even More on AI Than Investors Expected

Google Is Spending Even More on AI Than Investors Expected

Google Is Spending Even More on AI Than Investors Expected

Image: Pexels / Shantanu Kumar

Google raised its 2026 capital expenditure forecast to as much as $205 billion as AI demand drives more investment in cloud infrastructure and data centers.

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David Curry
David Curry
Jul 24, 2026

Google has raised its estimated capital expenditures to between $195 billion and $205 billion this year, as it ramps up investment in AI and data centers.

The revised forecast increases the company’s expected 2026 capital spending by up to $15 billion compared with the guidance it issued in April. While this covers all of its planned expenditure, the majority is going toward building more data centers and purchasing compute capacity from hyperscalers, neoclouds, and other suppliers.

Alphabet chief financial officer Anat Ashkenazi also said in the earnings call that expenditures will be “significantly” higher next year, as the company continues to acquire more capacity.

Even though Google runs its own cloud computing company, it still does not have enough capacity for all of its customers and internal projects. That has led it to strike deals with several third-party suppliers, including a $920 million-a-month agreement with SpaceX for access to its data centers.

Google Cloud gaining momentum through AI

Investors can be partly reassured by the huge demand for Google’s data center capacity and AI products. In the same financial call, Google said its cloud division had a backlog of $514 billion in contracted work, up from $460 billion in the previous period.

The division has gone from a solid third-place cloud computing provider in the US to the one with the strongest momentum for AI workloads. Its Tensor Processing Units (TPUs) have become increasingly attractive for inference workloads because they offer strong performance and lower operating costs for certain AI deployments.

Even so, the revelation of increased spending this year and even more next year has spooked some investors, with its stock price falling by 3.9% since the financial call. Investors across the AI sector have increasingly questioned whether hyperscalers can generate sufficient returns on their unprecedented infrastructure spending.

Google’s overall revenue reached $119.8 billion in the second quarter of 2026, up 24% year-on-year. Google Cloud recorded an especially sharp increase, with revenue of $24.7 billion, up 82% from the same period last year.

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Cloud growth surging, but AI deployment delayed

While Google Cloud growth is surging, the search giant has fallen slightly behind Anthropic and OpenAI in releasing frontier AI models. Anthropic’s Fable and Mythos have been at the center of the AI conversation for more than a month, while OpenAI’s Codex is gaining more enterprise customers every week.

At the same time, Google has delayed its Gemini 3.5 Pro model, which was meant to be its major push into coding and enterprise workflows, because it did not meet internal benchmarks. It has also been forced to keep its cyber AI model in preview for select partners.

Its consumer Gemini app continues to grow, reaching 950 million monthly active users, a similar figure to ChatGPT. How much of this usage comes through AI Overviews and other search-related systems, rather than the Gemini app itself, is open to debate, with third-party app intelligence platforms suggesting that ChatGPT is used considerably more actively than Gemini.

Google’s rising capital expenditure underscores a broader reality across the AI industry: demand for computing infrastructure continues to outpace supply. For enterprise customers, that means more AI capacity is becoming available, but significant investments—and competition for compute—are likely to persist well into next year.

Other News: Reddit is reportedly reconsidering its partnership with Google as AI-generated search answers reduce referral traffic.

David Curry

David Curry is a tech journalist and analyst with more than a decade of experience covering the technology sector for established media outlets and research-driven publications. He has reported on the industry since the early 2010s, with a focus on B2B technology, data journalism, mobile apps and app markets, artificial intelligence, digital platforms, and emerging technologies. His work combines journalism, analysis, and industry research to help readers understand how technology trends develop, how digital markets evolve, and how businesses and consumers are affected by new platforms, products, and innovations. David’s coverage often explores the intersection of technology, business strategy, market data, and user behavior. David holds a BA from the University of Lincoln and a master’s degree in International Journalism from the University of Leeds. His academic background and years of reporting experience inform his clear, analytical approach to explaining complex technology topics for professional and general audiences.