Shares of Japanese NAND flash maker Kioxia slid 12% on Friday after a report that OpenAI was considering delaying its IPO sparked a selloff in AI-related shares
Sam Nussey /Reuters:
Context & Ripple Effects
Kioxia’s market narrative has shifted sharply since its Tokyo listing: earlier coverage tied a major run-up to AI-driven memory demand, constrained NAND supply, and stronger pricing power. That optimism also supported plans to offer US depositary shares in 2027.
The company’s shares have previously been vulnerable to valuation shocks, including a discounted share sale and concerns that its AI exposure lagged some rivals. The latest move shows that investors are still treating Kioxia as a high-beta expression of the broader AI trade.
First-order effects
- Kioxia shareholders face an immediate repricing as a reported delay to OpenAI’s IPO weakens sentiment toward AI-linked equities, despite no reported change in Kioxia’s operations or NAND-demand outlook.
- The decline puts pressure on the valuation narrative that had elevated Kioxia alongside AI-related memory suppliers.
Second-order effects
- Investors may scrutinize whether memory-chip valuations are supported by near-term storage demand and pricing rather than by expectations around AI-company funding and public-market liquidity.
- A weaker share-price backdrop could make Kioxia’s planned US depositary-share offering a more valuation-sensitive proposition if AI-stock sentiment remains fragile.
Third-order effects
- If such reactions persist, the memory sector’s AI exposure will increasingly be priced as a capital-markets cycle as well as a hardware-demand cycle, amplifying volatility around major AI companies’ financing decisions.
- The pattern could reward chipmakers that can demonstrate durable supply constraints and customer demand independently of headline AI valuation signals; that distinction remains unproven by this selloff alone.
The trend: AI enthusiasm is extending across the semiconductor supply chain, but increasingly linking memory-chip valuations to confidence in the financing and commercialization timeline of leading AI platforms.