By Vicky Sidler | Published 31 July 2025 at 12:00 GMT

In a recent update to his widely read analysis, Sequoia’s David Cahn re-ran the numbers—and the AI revenue hole has tripled. What was a $200B question in 2023 has ballooned into a $600B question.

Translation: Big Tech is pouring billions into AI data centers, but actual revenue? Still lagging. Badly.

And while that might sound like a Wall Street problem, it’s also a cautionary tale for small business owners.

TL;DR

• AI infrastructure investment is outpacing real revenue—by about $600B.

• GPU supply shortages are over, but demand is softening.

• OpenAI remains the main player with meaningful revenue.

• Speculative spending now exceeds early railroad hype.

• Commoditization means prices will drop—but not every investor wins.

• Small businesses should watch, learn, and market like builders—not bettors.

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The $600B Elephant in the Server Room:

Last year, Cahn flagged a worrying mismatch: tech giants were stockpiling GPUs like canned beans in a bunker, but actual end-user revenue wasn’t following suit.

Now, things are even more lopsided.

Here’s the math: Take Nvidia’s revenue. Double it to account for the full cost of data centers. Then double it again to reflect the margin AI companies need to stay profitable.

That leaves a gaping $600 billion gap between what’s being spent on AI and what’s coming back in.

Spoiler: That’s not great business.

Wait—So Is AI a Bubble?

Yes and no.

Yes—if you’re a hedge fund hoping your GPU-backed startup turns into the next Google.

No—if you’re a founder solving real problems and delivering value people will actually pay for.

Right now, the market’s flooded with AI tools most people don’t use or understand. Outside of ChatGPT, AI hasn’t yet cracked mainstream wallets. And when customers don’t see the value, they don’t click “Buy Now.”

That’s not an AI problem. It’s a marketing problem.

When Everyone Builds Tracks, But No One Boards the Train:

Some optimists say building AI infrastructure is like building railroads—you lay the tracks, and eventually, the passengers will come.

But there’s a twist: In the 1800s, railroads had pricing power. Only so many tracks could run from point A to B. If you owned them, you owned the traffic.

In contrast, GPU cloud computing is fast becoming a commodity. With new entrants flooding the market, prices are already being pushed toward cost. No moat. No margin. No miracle.

And just like in the railroad boom, lots of investors will burn cash while a few operators (think OpenAI) ride off with the profit.

What This Means for Small Business Owners:

This isn’t just a Silicon Valley drama. It’s a lesson in strategy:

1. Don’t Chase Hype—Solve Problems: AI’s real winners aren’t the loudest or flashiest. They’re the ones quietly fixing broken systems. As a small business, your edge is speed, not scale. Focus on specific, customer-visible wins.
   
   

2. Value Trumps Novelty: Consumers won’t pay for tech they don’t understand or trust. Whether you’re selling software, services, or sourdough, your job is to make the value obvious.
   
   

3. Clear Messaging Wins Markets: If AI startups with billions in backing are struggling to explain what they do, imagine how hard it is for your ideal customer to get your pitch in 10 seconds. That’s why we start every client with a crystal-clear one-liner using the StoryBrand framework.

Want AI to Work for You? Don’t Try to Be AI.

Use it. Integrate it. But don’t imitate the giants. The AI boom is full of confusing jargon, fuzzy promises, and tools that sound more impressive than they are.

Instead of joining the noise, get clear on:

• Who you help

• What problem you solve

• Why you’re the right choice

It’s not about having the latest tool. It’s about using the right words.

Builders Beat Bettors—Every Time:

The real winners of the AI wave won’t be the loudest hype machines. They’ll be the ones who take advantage of cheaper compute, clearer strategy, and a real connection with the people they serve.

Start with clarity. Start with trust.

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