Is the AI bubble finally bursting? Wall Street loses $2.3 trillion in its worst crash since 2020
· OpIndia
Wall Street witnessed its worst stock market rout since the Covid-19 pandemic in March 2020 on Thursday, November 5, as investors rushed to dump technology stocks amid growing concerns about the sustainability of the artificial intelligence (AI) investment boom. The massive sell-off wiped out approximately $2.3 trillion in market value from the Nasdaq 100 alone, while semiconductor stocks suffered their steepest single-day decline in more than six years.
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The technology-heavy Nasdaq 100 plunged more than 6%, marking its worst single-day performance since March 2020. The benchmark S&P 500 declined 4.4%, while the Philadelphia Semiconductor Index, which tracks major chipmakers, crashed 12% in its worst session since the early days of the Covid-19 pandemic.
Nvidia, the world’s most valuable company, plunged more than 9%, recording its steepest single-day fall since January 2025 and wiping out its gains for the year. All 30 companies comprising the Dow Jones Industrial Average ended the session in negative territory, underlining the extent of the selling pressure.
The sell-off came amid growing uncertainty over the future of AI investments, which have been among the biggest drivers of Wall Street’s rally in recent years. Investors are increasingly questioning whether technology companies can sustain their enormous spending on AI infrastructure and whether the eventual returns will justify the hundreds of billions of dollars being committed to the sector.
However, concerns surrounding AI spending were not the only factor behind Thursday’s market rout. The outcome of the US midterm elections, fears of tighter regulatory scrutiny, the unwinding of crowded hedge-fund positions and a sudden lack of buyers combined to amplify the selling pressure.
Why did Wall Street crash?
Artificial intelligence has emerged as one of the biggest investment themes in global financial markets. Companies such as Microsoft, Alphabet, Amazon and Meta have committed enormous sums to building data centres and expanding their computing infrastructure to support the development and deployment of AI models.
This investment cycle has created unprecedented demand for specialised processors, memory chips, servers, networking equipment and other infrastructure. Nvidia, in particular, has emerged as one of its biggest beneficiaries because its graphics processing units (GPUs) are widely used to train and operate advanced AI models.
However, investors are beginning to question whether the pace of investment can be sustained indefinitely.
Building AI infrastructure requires billions of dollars in capital expenditure. Companies must acquire expensive processors, construct data centres, secure electricity supplies and maintain sophisticated cooling and networking systems. These investments also involve substantial depreciation and operating expenses.
For these investments to generate attractive returns, the revenue generated by AI products and services must eventually justify the costs.
The concern is that the industry could be spending money faster than it is generating meaningful commercial returns. Although AI adoption continues to expand, investors are questioning whether the revenue generated by AI applications will be sufficient to justify the enormous infrastructure investments.
Consequently, companies that had benefited from expectations of an uninterrupted AI investment boom are facing renewed scrutiny.
The Nasdaq 100 has now erased approximately $2.3 trillion in market value and fallen nearly 15% from its October 6 record, reflecting the extent of the reassessment.
How did the US midterm elections contribute to the crash?
The Democrats’ sweeping victory in the US congressional elections introduced another layer of uncertainty for investors.
The initial market reaction to the election results was positive. Investors expected Democratic control of Congress to act as a political check on President Donald Trump, potentially limiting his ability to push through controversial policies. There was also optimism that the changing political balance could improve the prospects of easing tensions surrounding the Iran conflict.
However, investor sentiment soon changed as attention shifted towards the potential consequences for the AI industry.
Democratic lawmakers have raised concerns about the rapid expansion of AI data centres, particularly their enormous electricity requirements, environmental impact and pressure on local infrastructure.
With Democrats gaining control of Congress, investors are concerned that the industry could face greater regulatory scrutiny. Delays in approvals, restrictions on new data-centre projects or additional compliance requirements could affect the pace of infrastructure expansion.
This is significant because the earnings expectations of several semiconductor manufacturers and technology infrastructure companies depend on continued growth in data-centre investments.
If political or regulatory developments slow that expansion, companies supplying the equipment required to build AI infrastructure could face weaker demand expectations.
Michael O’Rourke, Chief Market Strategist at JonesTrading Institutional Services, told Bloomberg that investors may have been too quick to assume the political shift would have little impact on the AI investment cycle.
He also cautioned that earnings forecasts for the coming year could become less reliable if policy changes alter expectations surrounding data-centre construction.
The election results did not directly cause the underlying concerns about AI profitability. Rather, they added another potential risk to an investment theme that was already facing questions about valuations and returns.
Hedge funds forced to sell as market panic intensifies
Another important factor behind Thursday’s crash was the unwinding of crowded investment positions.
AI-related stocks had become some of the most popular investments on Wall Street. Hedge funds, institutional investors and momentum-driven traders had built substantial positions in companies expected to benefit from the AI revolution.
When these stocks began falling sharply, some investors were forced to unwind their positions to limit losses and manage risk exposure.
This triggered a vicious cycle. Falling prices prompted additional selling, which pushed valuations lower and forced more investors to exit their positions.
At the same time, potential buyers appeared reluctant to enter the market during the sharp decline.
Michael Monaghan, Partner and Portfolio Manager at Founder ETFs, described the situation as a combination of hedge funds being forced to sell and a lack of buyers willing to absorb the selling pressure.
The resulting panic was not restricted to technology companies. Even stocks traditionally considered defensive, including Walmart, came under pressure as investors reduced their exposure to equities more broadly.
The Philadelphia Semiconductor Index plunged 12%, placing it in bear-market territory after declining more than 38% from its June 22 peak.
The Cboe Volatility Index (VIX), popularly known as Wall Street’s ‘fear index’, surged 11.57 points to 28.18, its highest level since March. A rising VIX indicates that investors are anticipating greater volatility and are increasingly concerned about further market declines.
Meanwhile, investors moved towards the relative safety of US government bonds. Treasury prices rose, pushing yields lower across maturities by as much as 12 basis points to their lowest levels since early September.
This flight towards safer assets indicated that the sell-off had evolved into a broader reassessment of risk across financial markets.
Comparisons with the dot-com crash and 2008 financial crisis
The scale and concentration of Thursday’s losses have drawn comparisons with previous episodes of market turmoil.
Greg Taylor, Chief Investment Officer at PenderFund Capital Management, told Bloomberg that the concentration of investor interest in AI was giving him flashbacks to the financial crisis of 2008 and the dot-com crash of 2001.
His comparison highlights a growing concern that investors may have become excessively dependent on a single investment theme.
The comparison does not necessarily mean that the current market is heading towards another financial crisis. However, it raises questions about whether valuations have become disconnected from the underlying earnings potential of companies.
During the dot-com bubble, investors poured money into internet companies on expectations of enormous future growth, often without sufficient consideration of profitability. When those expectations collapsed, technology stocks suffered a prolonged correction.
The current AI investment cycle is different in several respects. Many of the companies driving the boom are established businesses with substantial revenues and profits. Nevertheless, even financially strong companies can experience sharp corrections when their valuations assume growth that becomes difficult to deliver.
The immediate question is whether AI-related companies can generate sufficient revenue and profits to justify their capital expenditure and market valuations.
How could the Wall Street crash affect India?
The turmoil on Wall Street could have implications for emerging markets, including India, although the impact may differ from that on technology-heavy economies such as South Korea and Taiwan.
One of the biggest risks for Indian equities is a reversal in foreign institutional investment flows. When global investors become nervous, they often reduce exposure to emerging markets and shift capital towards safer assets such as US government bonds.
Such withdrawals could put pressure on the Sensex and Nifty, particularly large-cap companies with substantial foreign institutional ownership.
However, India could also benefit from a rotation of global capital away from expensive US technology stocks and towards other markets.
Indian equities have relatively limited direct exposure to advanced semiconductor manufacturing and AI data-centre infrastructure compared with South Korea and Taiwan. This could provide some insulation from a correction concentrated in the AI supply chain.
Another important factor is the Indian IT sector. Companies such as TCS, Infosys, Wipro and HCLTech derive a significant portion of their revenue from American clients. If US companies become cautious about technology spending, they could postpone discretionary IT projects, delay digital transformation contracts and reduce consulting expenditure.
This could affect the revenue growth of Indian IT companies.
Currency movements are another concern. A flight towards the US dollar could put pressure on the Indian rupee, making imports more expensive and potentially increasing inflationary pressures.
Crude oil prices will also remain important. India imports substantial quantities of crude oil, and a prolonged global economic slowdown could reduce energy demand and push oil prices lower. This would benefit India by reducing its import bill and easing inflationary pressures.
Nevertheless, a sustained global market correction could affect India through weaker foreign investment, reduced export demand and slower global economic growth.
Is this the beginning of a prolonged market correction?
Thursday’s crash has raised an important question for investors: Is Wall Street witnessing a temporary reassessment of AI valuations, or is the market entering a prolonged period of uncertainty?
The answer will depend on whether technology companies can deliver the earnings growth needed to justify their enormous investments.
AI remains a transformative technology with potentially significant commercial applications. The current sell-off does not necessarily indicate that the AI revolution is coming to an end. Instead, investors appear to be questioning the valuations assigned to companies benefiting from it and whether the expected returns will materialise quickly enough.
The political environment in Washington has added uncertainty, while hedge-fund selling and a lack of buyers have magnified the decline.
For India, the immediate impact could be relatively contained, particularly if global investors continue reallocating capital towards emerging markets. However, the country will not remain insulated if the correction spreads into a broader global economic slowdown.
The bigger takeaway from Thursday’s historic crash is that Wall Street’s AI-driven rally is entering a more demanding phase. Investors are no longer satisfied with announcements of massive capital expenditure and promises of future technological breakthroughs. They increasingly want evidence of sustainable revenues, profitability and returns on investment.
Whether this turns into a temporary correction or a much deeper market downturn will depend on how convincingly the technology industry can deliver on those expectations.