Cloud giants are preparing a record $700 billion for AI by 2026: a new supercycle in semiconductors
The investment race in artificial intelligence infrastructure is gaining momentum. Based on my calculations using MacroMicro analytics, the combined capital expenditures of the four largest cloud service providers (CSPs) will exceed $700 billion by 2026. This is not just a new record—it is a clear signal of the start of a supercycle in the semiconductor industry, which directly impacts the cryptocurrency and high-tech markets.
The latest earnings season only confirmed this trend. Companies from the "Magnificent Seven" once again showed strong results, but the main focus of investors was on upward revisions of capital expenditure forecasts. Instead of an expected peak, the data indicates that hyperscalers see more and more opportunities for investments in data centers, proprietary chips, and computing infrastructure.
Who is spending how much: the balance of power
The leader of the race remains Amazon (AWS) with projected capital expenditures of around $200 billion. The funds will go toward expanding data centers and developing its own Trainium and Inferentia chips. Microsoft (Azure) has raised the bar to approximately $190 billion, deepening its partnership with OpenAI and expanding infrastructure for Copilot. Alphabet (Google Cloud) is targeting $180–190 billion, focusing spending on the TPU network and the development of Gemini models.
Meta has significantly raised the bar to $125–145 billion. The funds will mainly go toward training open-source Llama models and improving recommendation algorithms. Notably, Tesla has also joined the race, raising its 2026 target to over $25 billion—for deploying AI servers and expanding the Dojo supercomputer.
Apple and NVIDIA are pursuing different strategies. Apple is betting on research and integrating AI into its own chips and devices. NVIDIA, meanwhile, is focused on developing next-generation chips and investing in AI providers such as CoreWeave.
How this affects the supply chain
Behind the sharp rise in semiconductor sales lies the entire value chain in AI computing. At its core are AI servers, whose "brains" are the chips. The top level includes advanced chip manufacturing (TSMC), CoWoS packaging, and high-bandwidth memory (HBM) from SK Hynix. The middle level consists of the cloud providers themselves, linking equipment suppliers with AI developers. The bottom level includes large language models (OpenAI, Anthropic) and a growing number of AI applications.
Noticing the acceleration in demand, providers are expanding capacity—which in turn spurs orders across the entire semiconductor industry. Sustained demand from cloud providers has already resulted in stable orders for GPUs from NVIDIA and AMD, as well as custom ASIC chips.
Global semiconductor sales show a strong positive correlation with the capital expenditures of major tech companies, and both indicators are hitting new records. A key indicator to track for a reversal is the AI monetization coverage ratio, which compares potential AI revenue with capital expenditures.
My analysis: The ratios for Meta (1.8), Microsoft (1.5), Google (1.1), and Amazon (0.7) currently confirm that these companies' investments are justified. This means the semiconductor supercycle continues, and markets, including the cryptocurrency market, will receive support from this powerful long-term trend. For investors, this is a signal to maintain focus on assets related to computing power and AI infrastructure.