Just yesterday, AI-linked stocks fell sharply across Asia after executives at leading U.S. AI companies called for a slower pace of development. Anthropic CEO Dario Amodei warned that increasingly capable AI agents could cause hundreds of billions of dollars in damage within six to 12 months, while OpenAI CEO Sam Altman and xAI chief Elon Musk backed calls for greater caution. Altman also said OpenAI would not pursue an IPO this year because of safety concerns.
Today, investors are showing nervousness over the stock market’s AI-led rally. Still, the concern has moved from the warnings themselves to whether they could eventually affect the spending driving the surge. Tech giants are expected to spend nearly $800 billion on AI infrastructure in 2026, benefiting chipmakers and data-centre operators.
Investors are now watching cancelled chip orders, delayed data centres or abandoned construction projects. “I need to see something concrete,” said Chuck Carlson, CEO of Horizon Investment Services.
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Are investors becoming too dependent on a few tech giants?
The AI boom has made the U.S. stock market unusually dependent on a small number of companies. The five largest companies in the S&P 500 now account for roughly 30% of the index, compared with about 11% two decades ago. That concentration means movements in a handful of technology stocks can have an outsized effect on the market as a whole.
Also, about $15 trillion is now benchmarked to the S&P 500, meaning money flowing into index funds is automatically directed toward the companies with the largest weights. Investors do not have to make a specific bet on AI for their portfolios to become exposed to it.
If enthusiasm for the biggest technology companies weakens, the resulting decline can affect the entire index’s performance, even if banks, healthcare companies, manufacturers, and other parts of the economy remain healthy. The AI trade has therefore become partly a concentration problem for the stock market, not simply a technology story.
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Why electricity consumption could become the next AI bottleneck
AI companies are running into a new limit of not having enough electricity and grid capacity to power the data centres they want to build. The International Energy Agency estimates that data centres consumed about 485 TWh of electricity in 2025, or 1.5% of global electricity demand. By 2030, that could rise to roughly 950 TWh, with AI-focused facilities accounting for much of the increase.
The pressure is already showing up in the U.S. In Texas, regulators recently halted new data-centre grid connections and launched an audit after power requests exceeded 700 gigawatts, more than 10 times the estimated electricity use of all U.S. data centres today. The issue is not just how much power AI needs, but whether local grids can deliver it fast enough as companies race to add computing capacity.
Google’s investment plans in Finland show how companies are responding. The company announced €13 billion ($15.1 billion) for AI infrastructure, including three data centres and a 22-year agreement to purchase up to 50% of the electricity from one Finnish nuclear plant. It is also working with Finnish utility Fortum on nuclear and renewable energy projects.
This makes electricity infrastructure an increasingly important part of the AI buildout. More chips and servers only increase computing capacity if there is enough power behind them. In regions where new grid connections, transformers and transmission lines take years to build, electricity availability could determine how quickly new AI capacity actually comes online.
Meanwhile, China has pushed back against Amodei’s call to slow the development of advanced AI, calling it “fearmongering”. China’s Foreign Ministry spokesman Guo Jiakun said at a regular briefing in Beijing on Monday that “fearmongering, confrontation and vicious competition will only disrupt the process of global AI governance and serve the interests of no one.”
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