Premium: What If…We’re In An AI Bubble? (Part 2)

Source: Where’s Your Ed At Date: 2026-05-22 URL: https://www.wheresyoured.at/premium-what-if-were-in-an-ai-bubble-part-2/

Summary

Zitron’s Part 2 of the AI bubble case argues the sector is sustained by mutual dependency rather than genuine demand: AI labs absorb most available compute inventory, creating an illusion of market demand that obscures the absence of other large-scale buyers. He cites $178.5B in US data center debt from 2025, VC underperformance (0.8–1.2x TVPI since 2018), and the claim that OpenAI and Anthropic would need to collectively generate or raise over $1.25T across four years to cover existing compute commitments — a figure he frames as structurally impossible without a demand-side step-change.

Implications

• AI economics / bubble. The core structural claim — that hyperscalers are building against each other’s stated demand, not against proven third-party customer demand — is the most falsifiable version of the bubble thesis. The tell will be whether non-lab enterprise GPU utilization rates rise meaningfully in 2026. If data center occupancy outside the top 3–4 labs stays low while construction continues, Zitron’s framing strengthens.
• Governance / policy. $178.5B in data center debt is a number that will appear in credit markets, not just tech analysis. If construction slows — which Zitron identifies as the cascade trigger — the debt exposure becomes a systemic finance question, not just a tech-sector one. Regulatory interest in AI investment concentration becomes more likely if institutional capital starts flagging the mismatch.
• Enterprise deployment. Enterprise buyers who’ve been deferring large AI commitments may find the delay rational: if the infrastructure economics force price corrections, waiting is a defensible position. Procurement teams reading this framing will slow-walk multi-year vendor lock-in.