The stock market crash was triggered by fears that artificial intelligence could replace the business models of many companies.
In recent days, the value of stocks, bonds, and loans in Silicon Valley has fallen by hundreds of billions of dollars, particularly affecting software development companies.
Among the reasons for the sell-off is the launch of a new legal services tool by the startup Anthropic PBC. "If today it's technology in law, tomorrow it could affect other areas like sales, marketing, or finance," noted analyst Jackson Ader from KeyBanc.
According to Bloomberg, fears of a potential crash have led to declines in the stocks of American and European tech giants. In recent days, a trillion dollars has vanished from the stock market. Even companies that were long considered the main beneficiaries of the AI boom have begun to show signs of fatigue and decline, as they have run out of ways to surprise investors, and debt repayment deadlines are approaching.
This week, the stock and credit markets will face an unprecedented downturn, the agency's report states.
Firstly, the decline in the AI market is characterized by its high speed and scope. In just two days, hundreds of billions of dollars were wiped off the value of stocks, bonds, and loans of various companies. Shares of software development companies were particularly hard hit, dropping nearly a trillion dollars over the past five days.
Secondly, this decline occurred not only due to fears of a bubble but also due to concerns that AI could soon displace the business models of many companies, a potential threat that has long been predicted.
The crisis has spread worldwide: from the USA to Europe, India, and China, even affecting sponsors of major tech companies on Wall Street. Creditors and private portfolio owners who previously actively invested in software companies are also under pressure. Over the past four weeks, loans to American tech companies totaling more than $17.7 billion, according to the Bloomberg index, have fallen to troubled levels.
This year will be interesting and alarming. We are at the early stages of a new distribution of roles in the market: who will be the winner and who will be the loser, noted Dec Mallarky, managing director of SLC Management.
There is now a possibility that debt repayment and obligations may occur faster than expected, leading to a significant market crash.
To understand why AI could become the trigger for the next market crash, it's worth looking at history.
In the late 1990s, the world experienced a boom related to the internet, with new companies emerging in the market almost daily.
Investors believed that a new economic era had begun, where traditional rules no longer applied.
Stock prices soared, profits were ignored, and valuations were based solely on promises of the future.
However, in 2000, reality returned, and the Nasdaq crashed by nearly 80 percent.
Most dot-coms disappeared, but the internet survived, continuing to transform the world. Investors who bought into the hype lost everything. We are now witnessing a similar situation, but under the banner of artificial intelligence.
AI is a reality. It has power and can change industries. However, expectations have once again outpaced actual profits.
A small group of companies, such as Apple, Microsoft, Amazon, Alphabet, Meta, Tesla, and NVIDIA, dominate the AI market, and their stocks account for a significant portion of the entire American market.
This level of concentration represents a historically dangerous situation. When the market relies on a limited number of companies that must deliver perfect results, even small disappointments can lead to severe declines.
The risk is heightened by the scale of investments.
AI companies are spending hundreds of billions of dollars on chips, data centers, cloud technologies, and energy resources.
Within a year, the spending on AI by major tech firms exceeds the GDP of many developed countries.
These investments keep the economy afloat. Without them, economic growth in the USA would appear significantly weaker.
The economy has become dependent on continuous investments in AI to maintain the appearance of stability.
If these expenditures slow down due to disappointing results, tightening credit, or loss of confidence from investors, markets may suddenly realize the fragility of the entire system.
A deeper problem lies in how money circulates within the AI ecosystem. Many companies in this sector finance each other through complex investment ties.
Large corporations invest billions in AI startups, which then spend that money on cloud services and data centers owned by the same corporations. Equipment suppliers sell chips to everyone while investing back in their clients.
This creates closed loops of capital flow, where revenue looks impressive, but much of the demand is generated within the system itself rather than through sustainable profits from end users.
This does not mean that fraud is occurring, but it indicates that valuations may be inflated, especially in an environment of cheap money and high optimism.
When funding becomes tighter, such structures typically collapse quickly.
The entire AI sector currently has valuations suggesting almost perfect scenarios: rapid technological progress, huge profits, and smooth scaling. Many companies have high multiples despite ongoing losses.
History shows that markets are ruthless when perfect results are not achieved.
Crashes typically begin not with stock sales, but with credit stress. Across the US economy, companies and consumers are heavily indebted. Many firms need to refinance large amounts of debt at much higher rates.
This compresses profits and increases the risk of defaults. When weak borrowers begin to fall, creditors retreat. Credit resources are depleted, investments slow down, layoffs increase, and demand decreases. Financial stress transitions from the markets to the real economy.
The current danger is that tightening credit may occur while AI valuations remain inflated and governments continue to be deeply in debt.
In previous crises, governments could actively intervene to stabilize markets. Currently, high levels of government debt and rising interest costs narrow this possibility.
Artificial intelligence will not destroy the economy by itself, just as the internet did not destroy the world in 2000. But finance has once again outpaced reality.
AI has become a catalyst for market optimism, a justification for high valuations, and a mask hiding deeper economic problems.
When expectations are revised, AI stocks could plummet sharply. Since these companies are now at the center of the market, their decline could drag down the entire system, acting not as the cause of the crisis, but as one of its most powerful triggers.
The reason this potential crash could be more dangerous than in 2000 or 2008 is that there is no clear path to retreat left.
Interest rates are already high relative to the level of debt. Central bank balances are already stretched, and governments face large deficits.
Conventional tools have been used repeatedly.
If confidence breaks now, policymakers may find that their measures lead to new problems instead of solutions.
This does not mean that the system will collapse instantly. It means prolonged instability, sharp fluctuations in the markets, uneven inflation, social tension, and geopolitical turbulence.
