NEW YORK / MANILA — November 3, 2026. Wall Street’s artificial intelligence boom is confronting one of its biggest tests of the year after the Nasdaq-100 officially entered correction territory, dragged lower by disappointing technology earnings, ballooning AI infrastructure spending and mounting doubts about whether enormous investments will deliver sufficient profits.
The technology-heavy index closed Monday, November 2, at 27,989.82, down approximately 1.4% for the session and 10.4% below its October 6 record closing high.
The decline marked the Nasdaq-100’s third technical correction of 2026, according to MarketWatch.
A technical correction generally occurs when an index falls at least 10% from a recent peak.
The selloff followed a brutal October in which shares of major technology companies, semiconductor manufacturers and AI infrastructure businesses suffered substantial losses.
Reuters reported on October 30 that the Nasdaq-100 was on course to erase more than $2 trillion in market value during the month.
Much of the pressure came from disappointing earnings and concerns about the vast capital required to build artificial intelligence infrastructure.
Investors are increasingly questioning whether companies such as Alphabet, Amazon, Microsoft and Meta can maintain their extraordinary spending while protecting profits and cash flow.
But the latest market decline presents a more complicated picture than a simple technology crash.
Despite the correction, the Nasdaq-100 remained approximately 10.9% higher for the year through November 2.
And while technology stocks struggled, many other sectors of the US stock market continued advancing.
The critical question is whether Wall Street is experiencing a healthy reassessment of expensive AI stocks — or the beginning of a deeper financial shock that could spread across global markets.
Nasdaq-100 Officially Enters Correction Territory
The Nasdaq-100’s latest decline follows weeks of pressure on major technology companies.
On October 30, the index fell approximately 3.5%, briefly trading more than 10% below its earlier peak.
However, it recovered sufficiently to finish that session outside correction territory on a closing-price basis.
That distinction changed on November 2.
The index declined another 1.4% and closed at 27,989.82, approximately 10.4% below its October 6 high.
The move confirmed the technical correction using closing prices.
MarketWatch reported that this was the index’s third correction of at least 10% in 2026, following earlier downturns in March and July.
But a correction does not automatically mean a prolonged bear market is underway.
A bear market is commonly defined as a decline of at least 20% from a recent peak.
The Nasdaq-100 had not reached that threshold.
Corrections can occur during broader market uptrends, and some are followed by substantial recoveries.
The latest decline nevertheless shows that investors have become less willing to pay extremely high valuations for future AI-related earnings.
S&P 500 Falls, but Dow Jones Holds Up
Technology weakness also influenced the broader US market on Monday.
The S&P 500 fell approximately 0.5%, closing at 7,541.40.
The Nasdaq Composite lost 1.1%, finishing at 25,164.32.
However, the Dow Jones Industrial Average gained approximately 0.4%, closing at 51,983.98.
The Russell 2000 small-cap index declined approximately 0.2%.
The mixed performance is important.
It suggests that investors were not abandoning every category of US stock simultaneously.
Instead, some were shifting capital away from expensive technology companies toward businesses in other sectors.
Reuters reported that nine of the S&P 500’s 11 sectors gained during October, even as technology stocks suffered heavy losses.
More than 70% of the index’s individual stocks advanced during the month.
This divergence suggests the market may be undergoing a rotation away from AI-heavy stocks rather than experiencing a uniform collapse across the economy.
However, if technology losses deepen sufficiently, they could eventually weigh on other sectors through reduced investment, weaker business confidence and broader financial-market volatility.
Big Tech Earnings Turn AI Optimism Into Investor Anxiety
A major catalyst for the correction was the market’s reaction to earnings reports from America’s largest technology companies.
Alphabet, Amazon, Meta and Intel faced sharp investor scrutiny after reporting results or forecasts that disappointed expectations.
The central concern was not simply declining sales.
In several cases, companies continued producing substantial revenue and profits.
Instead, investors became concerned about how much money businesses were committing to AI development relative to the cash they could generate.
Building data centers requires sophisticated processors, networking equipment, cooling systems, electricity infrastructure and specialized facilities.
Those investments often involve large upfront costs.
The resulting revenue may arrive gradually over several years.
That mismatch has become one of Wall Street’s biggest concerns.
WWC ONE MEDIA previously examined the issue in Big Tech’s $750-Billion AI Gamble Shakes Wall Street as Core Businesses Slow — But Will the Spending Ever Pay Off?.
The article explored estimates suggesting that major technology companies’ combined capital expenditure could approach three-quarters of a trillion dollars in 2026.
That figure is an estimate across several companies and types of investment.
It is not a confirmed amount devoted exclusively to AI.
Nevertheless, the scale illustrates why shareholders are demanding evidence of financial returns.
Alphabet, Amazon and Intel Become Warning Signs
Several earnings reports intensified investors’ concerns.
Alphabet suffered a sharp share-price decline as investors questioned the profitability of its AI infrastructure expansion and the potential effects of AI-powered search on its established advertising business.
Amazon also faced scrutiny over major capital expenditures and the financial relationship between cloud growth and infrastructure spending.
Intel became another focus of the selloff after its outlook disappointed analysts.
MarketWatch reported that Intel shares plunged approximately 29% on October 30, one of the company’s steepest single-session declines in decades.
The stock then fell another 8.8% on November 2.
These reactions illustrate how dramatically market expectations can change.
A company’s share price reflects anticipated future earnings, not merely the financial results it has already reported.
When investors reduce their growth assumptions, stock valuations can decline rapidly.
That can happen even when businesses remain profitable.
However, steep stock losses should not automatically be interpreted as evidence that the underlying companies are insolvent or that their products have failed commercially.
Semiconductor Stocks Suffer as AI Spending Fears Spread
Semiconductor companies have been among the biggest beneficiaries of the AI investment boom.
Advanced processors and memory chips are essential for training and operating large artificial intelligence models.
But chipmakers are also exposed to changes in customers’ spending plans.
On October 30, the Philadelphia Semiconductor Index plunged approximately 7.2%.
It fell another 3.4% on November 2, according to market reporting.
The consecutive declines reflected investors’ concern that some AI infrastructure spending forecasts could eventually be reduced.
WWC ONE MEDIA covered the regional consequences in Asian Chip Stocks Plunge as Amazon’s AI Spending Sparks Funding Fears — But Could the $2.1-Trillion Data Center Boom Be at Risk?.
The report examined how the US technology selloff affected Asian semiconductor companies, including suppliers in South Korea and Japan.
However, falling semiconductor share prices do not establish that AI chip demand has collapsed.
Some suppliers continue reporting strong orders for advanced computing products.
Investors are reassessing whether future growth will be sufficiently large to justify existing valuations.
That is a financial-market concern, not necessarily evidence of an immediate collapse in customer demand.
Wall Street’s Fear Gauge Reveals Rising Demand for Protection
The technology selloff has also increased demand for protection against market volatility.
On October 30, the Cboe Volatility Index, commonly known as the VIX, climbed as high as 22.31 during trading before closing at approximately 19.42.
The VIX measures expected near-term volatility inferred from S&P 500 options prices.
It does not directly predict whether stocks will rise or fall.
But a higher reading generally indicates that options markets are pricing greater potential market fluctuations.
WWC ONE MEDIA explored the development in Wall Street’s Fear Gauge Surges as AI Stock Selloff Sparks Rush for Protection — But Could a Bigger Market Crash Be Coming?.
The article described how investors purchased protective options as technology losses spread.
The increase in hedging activity suggests rising concern about further volatility.
However, a VIX reading near 20 is not equivalent to the extreme conditions experienced during the 2008 global financial crisis or the early stages of the COVID-19 market shock.
A market correction can create significant financial losses without necessarily becoming a systemic crisis.
Why Microsoft’s $25-Billion Bond Offering Is Raising Questions
Another concern involves the way technology companies are financing their infrastructure expansion.
Microsoft recently priced a $25-billion bond offering, its largest US-dollar debt transaction in years.
The offering attracted substantial institutional demand.
But it also highlighted the enormous financing requirements associated with modern AI infrastructure.
WWC ONE MEDIA examined the transaction in Microsoft Raises $25 Billion in Massive Bond Sale as AI Spending Explodes — But Is Big Tech’s Debt Gamble Getting Dangerous?.
Microsoft remains a highly profitable company with substantial operating cash flow and strong credit ratings.
Issuing debt is not evidence that the company is in financial distress.
The bond proceeds also have broad corporate purposes and are not designated exclusively for AI projects.
Nevertheless, the offering illustrates how capital-intensive the technology industry has become.
Companies must finance expensive facilities while determining whether future customer demand will justify their construction.
For investors, the relationship between capital expenditure, cash generation and long-term profitability is becoming increasingly important.
Oracle’s Data-Center Financing Highlights Another Risk
Some AI infrastructure projects depend more heavily on external financing than the largest technology companies do.
Those projects can be exposed to changes in interest rates, construction schedules, energy availability and customer demand.
WWC ONE MEDIA previously investigated one such issue in Oracle’s $18 Billion AI Data Center Debt Comes Under Pressure — And New Mexico’s Permitting Fight Is Getting Bigger.
The report examined loans associated with a large data-center development and uncertainty surrounding its financing and permitting.
The situation illustrates a broader challenge.
A project can have significant potential commercial demand but still encounter difficulties if financing costs increase or construction is delayed.
However, loans trading below face value do not automatically establish a default.
Similarly, investor concern over data-center financing does not mean every AI infrastructure project is economically unviable.
The central question is whether the expected revenue will be sufficient to cover construction, operating and financing costs.
Why the AI Boom Can Continue Even if Tech Stocks Fall
One of the most important distinctions is the difference between technological adoption and stock-market valuation.
Artificial intelligence can become increasingly useful while the shares of companies associated with it decline.
The internet provides a historical example.
During the late 1990s, investors assigned extraordinary valuations to companies connected with online technology.
Many stocks later suffered enormous losses.
Yet the internet continued transforming commerce, communication and business operations.
A similar distinction could apply to AI.
Companies may successfully develop applications that improve productivity, research, manufacturing and customer services.
But investors who pay excessive prices for anticipated growth may still experience disappointing returns.
The long-term success of artificial intelligence therefore does not guarantee that every AI-related stock is a good investment at every valuation.
Wall Street’s Market Rotation Could Prevent a Broader Crash
Despite the severity of the recent technology selloff, some analysts believe the broader market may remain resilient.
Reuters reported that investors had been shifting toward sectors outside technology rather than withdrawing completely from equities.
Consumer staples, industrial companies and selected financial businesses attracted interest during October.
This rotation helped limit the S&P 500’s monthly decline.
The broader index lost less than 1% during October, even as its technology sector fell approximately 6.8%.
That divergence may reduce the risk of a simultaneous marketwide selloff.
However, the largest technology companies represent substantial weightings in major US stock indexes.
A sustained decline in those shares can therefore affect index performance even when many smaller companies are rising.
If falling technology valuations also lead companies to reduce hiring, capital spending or expansion plans, the effects could eventually become more widespread.
The resilience of other sectors will be an important indicator of whether the correction remains concentrated in technology.
US Midterm Elections Add Another Layer of Uncertainty
The Nasdaq-100 correction occurred immediately before the November 3 US midterm elections.
Political uncertainty can influence short-term financial-market sentiment.
Investors may reassess expectations concerning taxation, regulation, federal spending and economic policy.
However, it would be misleading to conclude that the midterms caused the technology correction.
The selling pressure developed before Election Day and was primarily associated with earnings, AI spending and stock valuations.
Federal Reserve policy is another important factor.
Higher borrowing costs can reduce the present value of expected future profits and make financing more expensive.
Technology stocks with elevated valuations can be especially sensitive to such changes.
Upcoming economic reports, including employment and inflation data, may influence expectations for monetary policy.
But no single election result or economic report can guarantee a market recovery.
What the Nasdaq Correction Means for Philippine Investors
The US technology selloff may also affect investors in the Philippines.
Global equity funds, exchange-traded funds and investment products can have significant exposure to large American technology companies.
When those shares decline, the value of investments linked to them may also fall.
Changes in international risk appetite can influence capital flows into emerging markets.
However, the Nasdaq-100 and the Philippine Stock Exchange Index represent different companies, sectors and economic conditions.
A 10% decline in the Nasdaq-100 does not mean Philippine stocks must fall by the same amount.
For investors, the episode highlights the importance of understanding portfolio concentration.
A fund marketed as diversified may still have substantial exposure to a relatively small group of major technology companies.
Investment risks depend on holdings, valuations, currency movements and financial objectives.
Short-term market movements should not be treated as reliable predictions of future returns.
What Investors Should Watch Next
The next stage of the market’s adjustment will depend on several developments.
Technology companies will need to demonstrate that their AI investments can generate sustainable revenue and profits.
Investors will pay close attention to capital expenditure, free cash flow and cloud-computing growth.
Semiconductor companies will be evaluated according to actual customer orders rather than market expectations alone.
Corporate borrowing costs and access to financing will also matter.
If investors become concerned about financial returns, some companies may reduce or delay infrastructure projects.
On the other hand, evidence of stronger AI revenue, improved utilization of data centers and better cash generation could support a recovery in technology valuations.
The broader stock market’s performance will provide another important signal.
If nontechnology sectors remain resilient, the correction could remain relatively concentrated.
If selling spreads across most sectors, concerns about a deeper downturn would become more serious.
The Bigger Question: Is the AI Bubble Finally Bursting?
The Nasdaq-100’s November 2 correction represents a significant change in Wall Street’s attitude toward artificial intelligence.
For much of the AI boom, investors rewarded companies that announced larger spending commitments, new data centers and increasingly advanced computing systems.
Now they are demanding stronger evidence of returns.
The Nasdaq-100 has fallen more than 10% from its October peak.
Some leading technology stocks have suffered dramatic declines.
And disappointing earnings have raised questions about the financial sustainability of the AI infrastructure race.
Yet the broader market remains more resilient than the technology sector alone.
The Nasdaq-100 is still higher for the year, and several nontechnology industries continue attracting investment.
These facts suggest that a major repricing of AI-related shares is underway, but they do not prove that an economy-wide crash is inevitable.
The decisive factor may be whether technology companies can convert enormous infrastructure investments into durable profits.
As the Nasdaq-100 officially enters correction territory and investors question hundreds of billions of dollars in AI spending, is Wall Street simply correcting excessive technology valuations — or could the next round of megacap earnings expose a much deeper weakness in the artificial intelligence investment boom?
