Hyperscale vendors' 2026 Capex totaled approximately $730 billion, up 78% year-over-year, led by Amazon at $220 billion.

The five largest US cloud and AI infrastructure providers – Microsoft, Alphabet, Amazon, Meta, and Oracle – have collectively committed to spending between $660 billion and $690 billion on capital expenditure in 2026, nearly doubling 2025 levels. At the same time, pure-play AI vendors led by OpenAI and Anthropic are posting rapid revenue growth, though their combined revenues remain a fraction of the infrastructure investment being deployed on their behalf.

The first weeks of 2026 brought a cascade of earnings reports from major technology companies, all highlighting accelerating AI-related capital expenditure. Amazon projects $200 billion in capex for 2026, with most directed to data centers. Alphabet plans $175–185 billion; Meta, $115–135 billion; Microsoft, $120 billion or more; and Oracle, $50 billion. Combined, these five companies alone plan roughly $660–690 billion in infrastructure spending for 2026, the vast majority directed at AI compute, data centers, and networking. All report supply-constrained markets rather than demand-constrained ones.

Simultaneously, pure-play AI model vendors are reporting strong revenue growth. OpenAI ended 2025 with approximately $20 billion in annual recurring revenue, a threefold increase from the prior year. Anthropic's revenue run rate surpassed $9 billion in January 2026, up from roughly $1 billion at the end of 2024. Smaller vendors, including Cohere, Mistral, and Perplexity, are also scaling, though from considerably lower bases.

**The $690 Billion Infrastructure Sprint**

The scale of spending is substantial. In roughly 18 months, the aggregate annual AI infrastructure commitment from the five largest US cloud and technology companies has increased from approximately $380 billion in 2025 to a projected $660–690 billion in 2026. This represents a near-doubling of spending in a single year, driven by conviction that AI workloads will consume every available unit of compute capacity. Whether revenue and demand trajectories can justify this spending remains the central question facing the industry.

Amazon leads with a $200 billion capex plan for 2026, mostly data centers, a figure that surprised even bullish projections expecting closer to $147 billion. CEO Andy Jassy defended the plan, noting that AI capacity is monetized as quickly as it is installed. AWS reached a $142 billion annualized revenue run rate with growth accelerating to 24% year-over-year, a three-year high. Still, Amazon's stock dropped roughly 8–10% on the announcement, reflecting investor concern about payback periods.

Alphabet's planned $175–185 billion is notable partly because it has already been revised upward three times from an initial $71–73 billion range for 2025. CEO Sundar Pichai acknowledged the scale is significant enough to cause internal concern, but pointed to a cloud backlog that surged 55% sequentially to over $240 billion. Alphabet also reported reducing Gemini serving costs by 78% over 2025 through model optimization, signaling that efficiency gains are occurring alongside spending increases.

Microsoft is tracking toward $120 billion or more in fiscal 2026, having already spent $37.5 billion in its most recent quarter alone. The company disclosed an $80 billion backlog of Azure orders that cannot be fulfilled due to power constraints, suggesting demand outpaces even its aggressive build-out pace. Meta plans capex in the $115–135 billion range, including a 1 GW data center in Ohio and a Louisiana facility that could eventually scale to 5 GW. Oracle's projected $50 billion represents a 136% increase over 2025, supported by $523 billion in remaining performance obligations.

**The Stargate Factor**

Layered atop individual company plans is the Stargate project, a joint venture between OpenAI, SoftBank, Oracle, and MGX announced in January 2025 and backed by the Trump administration. The project targets $500 billion in AI infrastructure investment by 2029, with an initial $100 billion deployment. As of September 2025, roughly 7 GW of capacity had been planned across five sites in Texas, New Mexico, and Ohio, with more than $400 billion in commitments within the first three years.

**The Revenue Gap**

The scale of investment raises an obvious question about returns. Pure-play AI vendors – the primary consumers of this infrastructure – are growing rapidly but from modest bases relative to the capital being deployed. OpenAI's $20 billion ARR is impressive for a company that barely had consumer products three years ago, but it represents roughly 3% of the projected 2026 hyperscaler capex total. Anthropic's $9 billion run rate, while showing 9× year-over-year growth, occupies a similar position. The entire cohort of pure-play AI vendors – including Cohere ($150 million ARR), Mistral (~$400 million), Perplexity ($148 million annualized), and others – likely accounts for less than $35 billion in projected combined 2026 revenue.

This does not suggest the investment is misplaced. The hyperscalers are building not exclusively for third-party AI vendors but for their own AI services, enterprise customers running AI workloads on their clouds, and anticipated growth in AI inference demand as adoption matures. AWS alone reached $142 billion in annualized revenue, with an increasing share driven by AI. Microsoft reports its AI business is already larger than some established franchises. Revenue is coming – but the infrastructure is being built well ahead of it, which introduces execution risk.

**The US-China Infrastructure Race**

While US companies dominate raw spending figures, China's AI infrastructure investment is accelerating on a different model. Alibaba has committed RMB 380 billion (~$53 billion) over three years for AI and cloud, with CEO Wu indicating a larger plan is forthcoming. ByteDance is targeting RMB 160 billion (~$23 billion) in 2026 capex, with roughly $13 billion earmarked for AI processors. Tencent has been more measured, with quarterly capex actually declining in late 2025 as it prioritizes profitability alongside AI buildout.

China's total AI investment reached an estimated $125 billion in 2025, a substantial figure that remains well below the US hyperscaler total. However, Chinese AI model makers point to DeepSeek's R1 release in January 2025, which demonstrated that Chinese companies can achieve competitive model performance, though some of the low-cost claims were misleading.

US chip export controls continue to shape the landscape, though their impact is evolving. As of January 2026, the Trump administration allowed conditional sales of NVIDIA's H20 and H200 chips to approved Chinese customers with revenue-sharing arrangements, providing relief to Chinese firms while maintaining restrictions on the most advanced hardware. Huawei's domestic chip production remains limited – congressional testimony cited only 200,000 AI chips produced in 2025 – and the H200 is roughly 60% more powerful in real-world training than Huawei's Ascend 910C, suggesting Chinese companies still face meaningful constraints on scaling domestic compute.

**Regional Investment: Middle East, Europe, and Asia-Pacific**

The AI infrastructure buildout extends beyond the US-China axis. Saudi Arabia announced more than $15 billion in new AI investments at LEAP 2025 in Riyadh, including a $10 billion partnership between PIF and Google Cloud and plans to deploy 500 MW each of AMD and NVIDIA chips through its HUMAIN initiative. The UAE is developing what it describes as the largest AI campus outside the US – a 26-facility complex spanning 55 square kilometers.