A Wall Street Firm Modeled Out an AI Crash: S&P 500 Down 30%, $20 Trillion Gone. But Here's What Happens Next

TS Lombard models an AI-boom reversal that would cut U.S. stocks at least 30%—tech 40% and other sectors 20%—and erase about $20 trillion in market value, with $125 billion–$190 billion of losses on AI-related debt. The firm nevertheless expects only a mild U.S. recession, estimating a roughly 2-percentage-point reduction in the level of GDP, and says credit losses would not become systemic. It advises staying invested in diversified global stocks, avoiding an early bet against tech, and adding government bonds only when financial strain appears; its working assumption places a reversal in early 2028, though that timing could slip. TS Lombard also expects non-U.S. stocks to outperform over time and long-term interest rates to fall.

Analysis

The key transmission is not simply lower AI equity multiples: it is a feedback loop from concentrated end-customer funding to cloud-provider utilization, then to debt service and unfinished data-center capacity. If lab fundraising or customer monetization disappoints, contracted backlog may prove less bankable than lenders assumed; CoreWeave appears most exposed to that refinancing channel. Oracle is also named as a vulnerable provider, but the article supplies no company-specific debt or utilization evidence to rank its risk. Hyperscalers may absorb revenue downgrades better, yet capex deferrals would flow through to construction and equipment suppliers and weaken the jobs/income impulse in data-center regions.

Near term, the report is a scenario, not a timing signal: chasing an outright tech short after a sharp drawdown risks a squeeze if capex and funding hold. Over 1–3 months, monitor lab funding, cloud utilization/backlog conversion, AI-credit spreads, and capex guidance; these are more actionable than the projected 2028 turning point. Over 6–18 months, sustained non-U.S. relative outperformance is plausible if AI investment remains unusually U.S.-concentrated, but broad ex-U.S. indices still carry cyclical and currency risk.

Contrarian risk: the bear case may overstate fragility if AI usage converts into diversified, recurring enterprise revenue; conversely, a mild-recession assumption could understate local employment and supplier spillovers. The 30% equity drawdown is a stress case, not a base-case forecast.

Key Decisions for Investors

• Consider a beta-adjusted long VEA / short QQQ relative-value position rather than a net short in technology; scale in over weeks, with a defined loss limit. The thesis is geographic and concentration diversification, not a forecast that AI demand collapses. Reassess if non-U.S. relative performance reverses persistently or U.S. earnings breadth broadens.
• Keep CoreWeave on a financing-risk watchlist, not an automatic short after its sharp decline. Revisit only if refinancing costs, bond spreads, or utilization/backlog conversion deteriorate further; a funding round, improved cash generation, or durable customer demand would falsify the bearish setup. Verify current debt maturities and covenant terms before taking exposure.
• Do not add long-duration Treasuries solely on the modeled crash path. Use widening credit spreads, weakening labor data, or capex cuts as confirmation before adding duration; the trade can lose if investment persists and yields rise.
• Track Oracle and hyperscaler capex commentary alongside AI-lab funding and customer concentration. A reduction in committed spending would be a catalyst for supplier estimates to reset; stable utilization and evidence of end-customer revenue would argue against broadening the underweight.