The recent surge in cloud spending at Microsoft Azure, Amazon Web Services (AWS) and Google Cloud has caught the attention of Timothy Prickett Morgan of The next platformwhich prompted him to ask an intriguing question. How much of this seemingly impressive growth, he wonders, is actually being driven by investments in AI startups like OpenAI and Anthropic, funded by these tech giants?
Recently, Microsoft invested $13 billion in OpenAI, Amazon committed $4 billion to Anthropic, and Google also contributed $2.55 billion to Anthropic.
These substantial investments may not only spur innovation, but also increase cloud revenues, the technology expert warns, as the money flows back into cloud spending for the infrastructure these companies provide.
“Sugar daddy” investments
This situation, with nearly $20 billion invested in OpenAI and Anthropic, much of which was likely used for cloud capacity to train and test generative AI models, creates a feedback loop. The investment in these AI startups is coming back as cloud spending, potentially making cloud providers’ revenue growth appear more substantial than it actually is.
As cloud providers continue to see increased demand for GPU-accelerated systems, driven by the rise of AI, their operating revenues have soared. AWS, for example, saw its operating revenues increase 74 percent to $9.33 billion in the same quarter. But the sustainability of this growth remains uncertain, especially if a significant portion is fueled by these investment-driven loops.
The additional $7.93 billion in core revenue for AWS, Microsoft and Google may be closely tied to their AI investments. The real test will be whether these growth rates can be sustained without relying on such “sugar daddy” investments to boost cloud spending.
Timothy Prickett Morgan asks, “How much of that? [$7.93 billion] came from the nearly $20 billion these companies invested in OpenAI and Anthropic? How much came from the unknown number of AI startups that these companies may also have stakes in, and who got such stakes only because the companies knew they would have to spend most of that money on cloud capacity to train their models?” It’s a great question, and one we’d love to know the answer to.
