Key Takeaways
- U.S. stock market loses $3.2 trillion in value
- Data centers and AI spending at the center of concern
- AX budgets should start with per-project costs
- To check this week: supplier contracts
On November 5, 2026 (local time), U.S. stocks lost more than $3.2 trillion in market capitalization in a single day, as doubts over AI investment profitability converged with the possibility of tighter data center construction regulations.
How far did indexes and companies fall?
- Nasdaq Composite: down 5.5%, roughly 12% below its October 6 all-time high
- Nasdaq 100: down 6.4%, losing $2.3 trillion in market cap
- S&P 500: down 4.4%, its steepest drop since April 2025
- Philadelphia Semiconductor Index: down 12%, the largest decline since March 2020
By company, semiconductor and data center-related firms took the hardest hits.
- Semiconductors: Nvidia fell 9.3% (losing more than $400 billion in market cap), AMD fell 17.3%, Micron fell about 17%
- Emerging cloud providers: CoreWeave fell 10%, Nebius fell 15%
- Data center operators: Applied Digital, Cipher Digital, and IREN each fell more than 14%
- Major cloud providers: Microsoft fell 3.6%, Amazon and Google each fell 2.2%
Why data centers became the focal point
A key driver behind the sell-off was concern that the Democratic Party's midterm election victory could dampen AI infrastructure investment. Worries emerged that permitting and regulation for new facilities could tighten, with power grid and water shortages as well as community opposition surfacing as variables for construction plans. Michael O'Rourke, chief market strategist at JonesTrading, said, "What stands out most about this election outcome is that a slowdown in data center buildout speed has become a core issue."
The decline among emerging cloud companies—which have raised large sums to fund AI infrastructure buildout—reflected concerns that delays in investment expansion could make it harder to bear debt and capital expenditure burdens. Ted Parkhill, CEO of Incline Investment Management, said, "The market is shifting its focus from the promise of AI to the cost of AI."
Implications for Korean Companies' AX
What companies should focus on is not stock prices but costs and supply terms. From an AX perspective, this episode is better understood as an issue of infrastructure investment pace, profitability, and regulatory risk rather than AI growth itself. AX budgets should be assessed by per-project costs and payback timing rather than by AI growth forecasts.
Permitting and power issues at U.S. data centers are variables that Korean companies cannot directly control. If a company's AX efforts depend on U.S. AI infrastructure, it makes sense to distinguish the following three points in order.
- Per-project cost and payback timing: Record the cost of each AX project separately, along with when it is expected to convert into revenue or profit.
- Scope of supplier dependency: Identify which projects are tied to which AI infrastructure suppliers.
- Contract termination terms: If the supplier is an emerging cloud company, review the terms for contract termination and data migration first.
This week, go through each ongoing AX project and write down a single line noting the AI infrastructure supplier and contract termination terms. If that table comes up empty, that is where the AX budget discussion should begin.