According to Forbes, Microsoft reported $77.7 billion in revenue with 18% growth driven by AI Azure demand, Alphabet posted $102.3 billion revenue up 16% with increased capex, and Amazon highlighted AI-fueled AWS workloads with over $90 billion capital spending in the first three quarters. Meta reported Q3 capex at $19.4 billion and raised full-year spend to $70-72 billion while Apple’s June-quarter revenue hit a record $94 billion with growing AI investment. Meanwhile, Tencent showed 21% advertising growth powered by AI integration across its ecosystem without matching US-level infrastructure spending, proving the AI platform story extends beyond American tech giants.
The Capex Reality Check
Here’s the thing about these numbers – they’re absolutely staggering. We’re talking about companies spending like they’re building national infrastructure projects rather than tech platforms. Amazon expects about $125 billion in capex this year. Meta’s guiding toward $70-72 billion for 2025. These aren’t just big numbers – they’re “we might need to check if these companies are actually countries” numbers.
And the strategic question becomes brutally simple: who can actually afford to play this game? We’re seeing the emergence of what amounts to an “AI rails” economy where a handful of companies own the infrastructure everyone else has to rent. But at these spending levels, you have to wonder how many players can realistically stay in the wholesale infrastructure business versus becoming customers themselves.
Tencent’s Different Path
Now look at Tencent’s approach. They’re growing at double-digit rates too, with 21% advertising growth specifically credited to AI. But they’re doing it completely differently. Instead of building massive foundation models for external clients, they’re deploying their Hunyuan AI directly into their own ecosystem – WeChat, gaming, payments, you name it.
Basically, Tencent has over a billion daily users already inside their walled garden. They don’t need to spend tens of billions building infrastructure to sell to others when they can just make their existing services smarter and more profitable. Their AI assistant Yuanbao plugs into everything from QQ Music to Tencent Meeting, generating immediate commercial impact without the hyperscale capex. It’s a fundamentally different model that might actually be more sustainable.
Regulatory Headwinds
And let’s not forget the regulators are watching all this very carefully. In both the US and Europe, authorities are retooling antitrust rules for an AI era where a few platforms control compute, data, and distribution. Google’s already been found to violate antitrust law in search and adtech. Europe’s Digital Markets Act has triggered big fines for Apple and Meta.
So here’s my question: when you combine unprecedented capital spending with increasing regulatory scrutiny, how long can this concentration of power last? The political pressure is only going to increase as these companies get bigger and their infrastructure spending starts looking like essential public utility investment.
The Profitability Test
The real test for this AI super-cycle isn’t who can spend the most – it’s who can actually make money from all this investment. US giants are betting that renting out AI infrastructure will pay off long-term. But Tencent’s showing that immediate monetization through existing ecosystems might be the smarter play.
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Ultimately, we’re watching two different AI strategies unfold. The US approach is build it and they will come. Tencent’s is integrate it and monetize now. Both are working for now, but the sustainability question looms large. Can anyone actually afford to keep spending at this rate indefinitely?
