Asian stock markets opened to a modest decline on October 8, 2025, reflecting a ripple of caution that has swept across global financial markets. The retreat mirrored Wall Street’s recent pullback from record highs, as investors and analysts alike voiced growing concerns about overheated valuations—particularly in the technology sector and the burgeoning field of artificial intelligence.
Technology shares led the slide in Asia, with a US-listed index of Chinese shares falling sharply. This tech-driven retreat came as the Japanese yen weakened for a fifth consecutive day, reaching its lowest level against the dollar since February. The currency’s slide was attributed in part to Sanae Takaichi’s unexpected victory as the new leader of Japan’s ruling Liberal Democratic Party, a development that caught markets off guard and contributed to the yen’s ongoing slump.
But beyond regional currency moves and the usual market jitters, the larger story is one of mounting anxiety about the sustainability of the AI investment boom. According to The Guardian and Economic Times, OpenAI’s recent multibillion-dollar deals with chip giants Nvidia and AMD have become a lightning rod for debate. Under the terms of the Nvidia deal, OpenAI will pay Nvidia in cash for the chips powering its artificial intelligence models, while Nvidia will invest in OpenAI in exchange for non-controlling shares. Some market watchers see echoes of the late 1990s dot-com bubble in these circular financial arrangements, with leading British tech investor James Anderson remarking, “It’s not quite like what many of the telecom suppliers were up to in 1999-2000, but it has certain rhymes to it. I don’t think it makes me feel entirely comfortable from that point of view.”
The AMD deal, meanwhile, further entwines OpenAI with another major chipmaker. OpenAI has agreed to use hundreds of thousands of AMD chips in its datacenters—the digital backbone of AI tools such as ChatGPT—and will have the opportunity to buy up to 10% of AMD. Both deals are driven by an insatiable appetite for computing power, as OpenAI and its competitors race to unlock ever greater performance and meet surging demand.
Neil Wilson, a UK investor strategist at Saxo, summed up the mood: transactions like those between Nvidia and OpenAI “look, smell and talk like a bubble.” The warning signs are piling up. OpenAI’s valuation has skyrocketed from $157 billion in October 2024 to a staggering $500 billion just a year later, according to The Guardian. Anthropic, another AI heavyweight, saw its value nearly triple from $60 billion in March to $170 billion in September 2025. Yet, despite these heady numbers, the financial reality is less reassuring: OpenAI reportedly posted $4.3 billion in revenue in the first half of 2025, but an operating loss of $7.8 billion.
Stock market swings have also raised eyebrows. AMD’s stock briefly surged by $80 billion in valuation after the OpenAI announcement, while Oracle—a major player in AI infrastructure—gained about $250 billion in a single day in September after reporting strong results. These dramatic moves have prompted seasoned market watchers to wonder if valuations are becoming dangerously disconnected from business fundamentals.
Chris Montagu of Citigroup captured the prevailing sense of caution: “Profit-taking risks have rapidly risen across markets, and are particularly elevated for Nasdaq, potentially hampering further upside.” The sense that a bubble may be forming around AI isn’t confined to the stock market. The big four AI “hyperscalers”—Meta, Alphabet, Microsoft, and Amazon—are expected to pour $325 billion into capital expenditure this year, a sum roughly equal to the GDP of Portugal.
Yet, in the midst of this investment frenzy, a sobering reality check emerged. In August 2025, the Massachusetts Institute of Technology published research showing that 95% of organizations are getting zero return from their investments in generative AI. The MIT study found that the issue wasn’t with the quality of the AI models, but rather with how they were being used. The so-called “genAI divide” is stark: while startups led by young entrepreneurs are seeing revenue jumps from deploying AI tools, most established organizations are not reaping significant benefits. The report’s release coincided with a sharp fall in AI infrastructure stocks, including Nvidia and Oracle.
Consulting firm McKinsey & Company echoed these findings, noting that while eight out of ten companies report using generative AI, the same proportion see no significant impact on their bottom line. The problem, McKinsey said, is that AI tools are often deployed for generic tasks like producing meeting minutes, rather than for transformative applications such as identifying risky suppliers or generating new ideas.
Despite these cautionary tales, there’s no denying the scale of AI’s adoption. OpenAI reported that ChatGPT now boasts 800 million weekly users, up from 500 million just seven months earlier. Sam Altman, OpenAI’s CEO, remains bullish, asserting that demand for paid AI access is set to “steeply increase.”
Meanwhile, financial officials in the US continue to weigh the risks and rewards of the current environment. Federal Reserve Governor Stephen Miran said his expectations for a limited tariff impact on inflation meant the Fed could continue easing policy. However, Minneapolis Fed President Neel Kashkari warned that any drastic rate cuts would risk stoking prices—underscoring the delicate balancing act facing policymakers as they navigate an economy supercharged by technology and speculation.
Adrian Cox, a thematic strategist at Deutsche Bank Research Institute, described the market’s mood as being at a crossroads: “We are at a crossroads where the lights are flashing different colours.” Cox pointed to red lights—like enormous capital expenditure and soaring private company valuations—amber signals in the more than doubling of tech stock prices, and green lights in the fact that much of the investment is coming from well-capitalized firms funding spending from their own free cashflow. “We are only scratching the surface in terms of the technology’s capabilities and there is much more road ahead in terms of companies adopting AI,” Cox added.
Elsewhere in Asia, there were signs of optimism. Vietnam was upgraded to emerging-market status by FTSE Russell, a move that could unlock billions of dollars in additional capital inflows. And in commodities, oil prices rose in early Asia trading after a report indicated a drop in stockpiles at a US delivery hub.
So, is the AI boom a bubble waiting to burst, or the dawn of a new era? For now, the answer depends on where you stand. But one thing is clear: investors, policymakers, and tech leaders are all watching closely as the next chapter unfolds.
