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THE FIRST COMPANIES TO ACTUALLY USE AI AT SCALE ARE NOT ABLE TO AFFORD IT.
Big Tech created a manufactured demand bubble by giving billions to AI startups under strict contracts that force them to hand that exact cash right back to buy cloud servers.
Because this money simply travels in a circle, these startups never had to face the real, staggering expense of running giant AI models.
This round trip loop created a protected environment where companies could burn through infinite data because they were essentially playing with house money. But the exact moment this technology leaves the safe loop and hits a normal company with a hard budget constraint, the unit economics break completely.
Real enterprise customers do not get their cash recycled back to their own balance sheets. Every token bill is a final cash outflow.
This is why Uber gave AI coding tools to 5,000 engineers and exhausted its entire annual AI budget by April, with power users burning up to $2,000 a month each.
The invoices are so high that even Microsoft just ordered 100,000 of its own engineers to stop using Claude Code by June because the uncapped token billing became completely untenable. Microsoft has a multi-billion dollar partnership with Anthropic, yet had to cancel internal usage because the tool costs too much to run.
Nvidia's VP of applied deep learning admitted that the cost of compute for his team is now far higher than the actual salaries of his human workers. Wall Street thinks that falling chip prices will automatically fix this, but the math behind agentic AI makes that assumption impossible.
Gartner confirms that even if per-token prices drop 90% by 2030, total corporate bills will keep rising because active AI agents run continuously and resend massive conversation histories, multiplying token consumption up to 30 times per task.
The circular loop successfully fabricated a massive growth story to pump up a $2 trillion cloud backlog, but it hid a product that is structurally too expensive for the real economy to actually deploy.
The massive gap between optimistic earnings call statements and the actual invoices landing on corporate desks is the most mispriced risk in global finance today