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Hyperscaler AI capital expenditure versus slower and uncertain monetization timelines

 

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What we may be witnessing right now feels uncomfortably familiar.


Not in the technology itself… but in the economics behind it.


We are seeing hyperscalers committing extraordinary levels of capital, with projected AI-driven capex in 2026 approaching $650–700 billion annually, up from roughly $380–410 billion in 2025. In just one year, that is a 60–70%+ increase, with an estimated ~75% of that spend directly tied to AI infrastructure.


Individually, the scale is even more striking:


- Amazon alone is projected around $200B

- Alphabet around $175–185B

- Meta between $115–135B

- Microsoft exceeding $100B+ run rate

- Oracle adding another ~$50B


This is no longer incremental investment.

This is a structural capital shift at global scale.


And this is where the parallel with the dot-com era becomes difficult to ignore.


Back then, the belief was that the internet would transform everything. It did.

But the timing of value creation and the scale of investment were completely misaligned.


Today, AI will also transform everything.

But transformation does not guarantee proportional or immediate returns.


Some facts and figures that should make us pause:


- Data center costs are reaching extreme levels, with ~$80B for a single 1GW facility

- Hyperscalers are increasingly tapping debt markets, moving away from purely cash-funded growth

- AI infrastructure demand is described as “supply-constrained”, yet power availability is becoming the real bottleneck

- Despite strong demand signals, clear, large-scale monetization models are still evolving

- Stock volatility is already appearing after earnings when ROI timelines are questioned


This creates a structural tension:


When capital deployment scales faster than monetization maturity, financial risk accumulates beneath technological optimism.


And that is how bubbles form.


Not because the technology is wrong, but because capital allocation runs ahead of real economic absorption.


The real question is not whether AI will generate value. It will.


The question is whether:


- The value will arrive fast enough

- The value will be captured by those making the largest investments

- The market has correctly priced the timeline and distribution of that value


If the answer to any of these is “no”, then we are not looking at a technological failure…

we are looking at a financial misalignment.


And that is exactly what triggered the dot-com correction.


This is not a prediction of collapse.

But it is a reminder that innovation cycles and financial cycles do not always move at the same speed.


And when they diverge too much, markets tend to correct that gap.


Possibly abruptly.

- Manuel

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