The Numbers First
OpenAI is targeting a valuation in the range of $300 billion. Anthropic sits at $60 billion or more on recent private-market terms. xAI is above $50 billion. Add the European contenders and smaller players signalling intentions, and the total public equity these companies would add to the market approaches $400 billion , potentially concentrated into a window of months rather than years.
For context: the largest IPO wave in recent history was 2021. That year included Rivian at $11.9 billion, Coinbase's $65 billion direct listing, and an extraordinary volume of SPAC activity. Total capital raised across the full year hit approximately $300 billion. The current AI IPO wave would attempt to absorb a larger number in a much shorter window.
The compression is where the risk lives. Markets can absorb large capital raises. What they struggle with is large capital raises that arrive simultaneously, faster than institutions can rotate and price efficiently.
The Absorption Problem
Public markets absorb large IPOs through institutional rotation. A major new issue draws capital from existing positions , institutions sell some holdings to raise cash, then deploy that cash into the new offering. This is normal and happens continuously. The process works because the rotation is spread out, the demand generally matches the supply at the right price, and no single offering overwhelms the system's capacity to process it.
The crash scenario does not require any single IPO to be a failure. It requires the aggregate supply to exceed what institutions can absorb without forced selling. If institutions need to raise significant cash quickly to participate in multiple large AI offerings at once, they sell other tech holdings. Those sales push prices down. The declines make other institutional investors nervous about their own exposure. They sell. The correlation across the broader tech sector tightens, and what started as rational rotation starts to look like a sell-off.
None of this requires irrational behavior. It only requires the supply to arrive faster than the market's normal rotation mechanism can process it, which is exactly what a compressed multi-company IPO wave creates.
The Trigger Mechanism
The scenario has a specific starting point, and it is more precise than a general market downturn. One IPO , not necessarily the largest, just the first to show a crack , prices below its target valuation. Not catastrophically. A 10 to 15 percent miss is sufficient. That miss is a signal: demand at the expected price was not there. Institutional investors who had soft orders in for subsequent offerings in the queue begin to reconsider their exposure and what the miss implies about the category's actual market appetite.
Some pull their orders. Others reduce their allocations. The next company in the queue watches its order book thin and faces a binary choice: price lower and proceed, or pull the filing and wait for conditions to stabilize. If they price lower, the signal propagates , now two companies have priced below hope, and the conversation shifts from "is the demand there" to "where is the floor." If they wait, the other companies behind them face the same calculation at the same time, and the window starts to close for everyone simultaneously.
Market observers describe a 48-to-72-hour window as the relevant timeframe for sentiment to shift from FOMO to caution in a compressed IPO environment. That is short enough that companies cannot easily respond to each other's moves, and long enough for the narrative to reset entirely.
The Interest Rate Variable
The crash scenario becomes significantly more likely if interest rates are meaningfully elevated when the IPOs price. Higher rates compress the multiples that growth stocks can support. A company that justifies a 30x revenue multiple in a low-rate environment , where the alternative to equity is a low-yielding bond and the cost of capital is cheap , may only support a 15x multiple when rates are high and the risk-free return on cash is competitive.
OpenAI's financial projections, and the valuations of AI companies generally, depend on assumptions about continued rapid revenue growth that only make sense at aggressive multiples. If the rate environment compresses those multiples before the companies list, the valuation gap between what they hoped to raise and what the market will pay widens. The IPO math does not fall apart, but it gets harder to defend in institutional roadshows, and harder to defend means more pricing risk.
Rate timing is entirely outside any company's control. It is also potentially the single variable that matters most to whether this wave lands cleanly or creates turbulence , more than any individual company's fundamentals, more than the sequencing, more than the S1 disclosures. A favorable rate environment absorbs a lot of imperfection. An unfavorable one turns manageable imperfection into a problem.
The Circuit Breaker
The crash scenario has a real counterargument, and it deserves to be taken seriously rather than dismissed. Institutional investors have been underweight public AI for years. Most AI exposure in large diversified portfolios is private , illiquid, difficult to value with precision, and impossible to trade in response to new information. There is structural pent-up demand for public AI equity that has simply not existed in tradeable form until now.
When these companies list, large funds that have been unable to participate in the AI run through public markets finally have their entry point. That demand does not evaporate because one company prices slightly below target. It represents years of accumulated appetite for exposure the private markets could not provide at scale. The buying pressure from institutions that have been waiting for this moment is real and it is potentially substantial.
The question is whether that pent-up demand is large enough to cover the full supply of $400 billion in new equity, or whether it is large enough to soften the landing while still allowing some repricing. Those are different outcomes, and the difference between them is what separates a normal if bumpy IPO wave from one that leaves marks on the broader market.
The Realistic Base Case and the Confirming Signal
The realistic base case is not a crash. It is a repricing. Companies go public at lower valuations than their most optimistic private-round comparables implied. Post-IPO performance is mixed , some names hold their offering price, others drift below it over the following quarters. The narrative that every AI company is worth whatever its last private round suggested gets harder to sustain for companies still raising in the private markets. Seed and growth-stage valuations compress as public market data provides a reality check that private-only markets lacked.
That outcome would be significant even without any dramatic public failure. A $300 billion OpenAI that trades at $200 billion three months after listing tells every late-stage private AI company raising at an aggressive valuation that the public market disagrees with that number. Fundraising gets harder. The most speculative valuations in the private market get questioned more. That is not a crash , it is a correction of a specific kind of pricing optimism that had no real anchor.
The confirming signal for a more serious scenario is specific: if three or more major AI IPOs are trading below their listing price by the end of 2026, the repricing has become something more structural than a routine post-IPO cooling.
That outcome would not mean AI itself failed as a technology category. It would mean the financial infrastructure built around it , the valuations, the multiples, the assumptions baked into the S1 filings , was priced for a future that arrived more slowly than required.
The wave is coming. Whether it breaks cleanly or creates lasting turbulence depends on timing, rates, sequencing, and how much of the pent-up institutional demand proves real when the actual order books open.
Watch the first 90 days of post-IPO trading more carefully than the opening-day pop. First-day returns reflect allocation dynamics and short-term momentum. The 90-day performance reflects whether institutional investors who received allocations are holding or distributing. Distribution into a rising market is fine. Distribution into a softening one creates the pressure that tests whether the pent-up demand story holds or dissolves under real conditions.