The emergence of China’s DeepSeek has sent a chilling message to US tech giants: you don’t need to spend billions to achieve the same performance as leading AI models.
But don’t tell that to Alphabet (NASDAQ: GOOGL), Amazon (NASDAQ: AMZN), Meta Platforms (NASDAQ: META), and Microsoft (NASDAQ: MSFT).
As far as they are concerned, the huge AI spending will continue.
Last month, Microsoft CEO Satya Nadella said the company would be committing US$80 billion in capex for its financial year ending 30 June 2025 (FY25).
Then, Meta forecasted a spend of between US$60 billion and US$65 billion for 2025.
Not to be outdone, Alphabet and Amazon have since projected their capex spend of US$75 billion and US$105 billion, respectively.
When you add it all up, the combined spending reaches a staggering US$325 billion.
Here’s the thing: there may be good reasons why the four tech giants are spending big.
Cloudy with a chance for real demand
During Microsoft’s FY25 first quarter (1Q’25) briefing, Nadella took time to point out that a big part of its capex spending is backed by actual demand (bolded for emphasis).
“One of the things that may not be as evident is that we are not actually selling raw GPUs for other people to train.
In fact, that’s a business we turn away because we have so much demand on inference …
We really are not even participating in most of that [“selling raw GPUs”], because we are literally going to the real demand, which is in the enterprise space, or our own products like GitHub Copilot or M365 Copilot.”
Here, Nadella distinguished AI usage between training and inference.
What is the difference?
To use an analogy, training is akin to teaching a student.
You provide the student (the AI model) with a lot of data (examples) and constantly check its answers.
Inference, on the other hand, is like getting the student to take a test.
Once trained, the AI model is presented with new data where the model will make predictions and classifications based on its training.
In simple terms, there is actual revenue backing this spend.
Similarly, Meta’s Chief AI scientist Yann LeCun said that billions in AI infrastructure spend will be used for inference and not training.
In other words, Meta is investing to support the actual usage of its AI solutions.
On this note, the social media firm said Meta AI (its AI assistant) is currently used by 700 million users per month and is aiming for one billion by the end of this year.
When demand exceeds supply
Speaking of demand, Alphabet CFO Anat Ashkenazi provided the reasoning behind the company’s increase in capex spending for 2025:
“We do see and have been seeing very strong demand for AI products in the fourth quarter in 2024.
We exited the year with more demand than we had available capacity.
So we are in a tight supply-demand situation, working very hard to bring more capacity online. As I mentioned, we’ve increased investment in CapEx in 2024, continue to increase in 2025, and will bring more capacity throughout the year.”
Similarly, Amazon CFO Brian Olsavsky also highlighted the need to support demand for its AI services as a key reason behind its high infrastructure spend:
“Similar to 2024, the majority of the spend will be to support the growing need for technology infrastructure.
This primarily relates to AWS, including support demand for our AI services, as well as tech infrastructure to support our North America and international segments.”
Based on our observations of the four tech giants above, the increased spending is consistently supported by actual usage.
Get Smart: 2025 is the year of applications
This is the year where AI usage may translate to revenue growth.
If the tech giants demonstrate topline and bottom-line growth driven by increased demand for their AI solutions and services, it will provide strong justification for their increased capital expenditure.
As a caveat, all four tech giants understand the importance of establishing an early lead in this potentially transformative technology.
They are unlikely to pull back anytime soon as the cost of missing this opportunity could be high.
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Disclosure: Chin Hui Leong owns all the stocks mentioned.
