ChatGPT Is Causing a Stock-Market Ruckus

The rise of artificial intelligence is taking the tech world by storm. The technology is also making waves on Wall Street.

It is early days for so-called generative AI, a form of artificial intelligence that can conjure original ideas in the form of text, video or other media. But the tool has caused a stir in companies, schools, governments and the general public for its ability to process massive amounts of information and generate sophisticated content in response to prompts from users.

Big technology companies are investing billions of dollars in the technology. Startups are raising cash and trying to develop business models using AI at a rapid pace.

Investors are gauging the extent to which AI’s arrival will upend companies, industries and contemporary business practices—and placing bets accordingly. That has sent stocks swinging wildly in both directions: Chip maker Nvidia’s shares are surging, while shares of study-materials company Chegg have plummeted.Enthusiasm for the potential of AI is one reason big tech companies are among this year’s strongest performers.

There is little doubt that generative AI chatbots are popular. ChatGPT reached 100 million users in two months, the fastest app on record, analysts at Goldman Sachs said in a research note. In comparison, TikTok took nine months to reach that milestone, while Instagram took 30.

“We view AI as huge, and we’ll continue weaving it in our products on a very thoughtful basis,” Apple Chief Executive Tim Cook said last week on a conference call with analysts.

Apple isn’t alone. There have been more than 300 mentions of “generative AI” on company conference calls worldwide so far this year, according to data from AlphaSense. The phrase barely garnered a mention before 2023.

Major health systems are experimenting with AI to see whether the technology can help boost the productivity of their medical staffs. Entrepreneurs and venture-capital investors hope generative AI will revolutionise businesses from media production to customer service to grocery delivery. Even Coca-Cola told investors it is experimenting with the technology.

Some investors wonder whether generative AI is the latest tech with the potential to disrupt entire industries. The dawn of online streaming spelled the end of home-video-rental companies such as Blockbuster, while cameras on phones helped render photo processing obsolete and helped spark Apple’s rise and Kodak’s decline.

Artificial intelligence is “almost certainly overhyped in its initial implementation,” said Michael Green, chief strategist at Simplify Asset Management. “But the longer-term ramifications are probably greater than we can imagine.”

Microsoft has added nearly $500 billion in market value since the tech giant announced a $10 billion investment in startup OpenAI, developer of ChatGPT, in January. Shares of Nvidia, which makes chips needed to power the chatbots, have risen 96% so far this year. Google parent Alphabet shed $100 billion in market value in a single day earlier this year after its chatbot Bard underwhelmed investors, though those losses quickly reversed.

Alphabet shares are up 22% this year.

Those moves might prove ephemeral as the technology’s power becomes clearer, said Daniel Morgan, senior portfolio manager at Synovus Trust. “The most difficult thing to ascertain is, what is going to be the impact of all that spending to these companies on revenues and profits?” His fund owns shares of Microsoft, Alphabet and Nvidia.

The flurry of investor interest has pushed valuations higher. Nvidia trades at 164 times its past 12 months of earnings, according to FactSet. Microsoft and Alphabet trade at 33 times and 24 times, respectively.

Portfolio managers said the race to understand the implications of AI’s emergence is essential, both to invest in the technology’s winners and to avoid its eventual losers. Shares of Chegg fell 48% last week after the study-materials company said that the rise of ChatGPT was harming its ability to attract new customers.

“You just don’t know all the knock-on effects,” said Will Graves, chief investment officer at Boardman Bay Capital Management. “If this really is an iPhone moment, nobody saw that Uber was coming out of the iPhone to hammer the taxi industry.”

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion