Optimism over the profit potential of artificial intelligence has helped drive the US stock market to record highs, but investors are looking for weak spots that could emerge in the AI trade and have identified some risks to watch for.
AI has been the dominant theme on Wall Street since the launch of ChatGPT in November 2022, which fuelled enthusiasm about the technology’s potential. Citigroup strategists estimate that nearly 50% of the S&P 500’s overall roughly US$57-trillion in market capitalisation has “high” or “medium” exposure to AI.
The benchmark index is up about 13% year-to-date, while the tech-heavy Nasdaq Composite has climbed 17%.
“So much of what is holding up the markets is either directly or indirectly related to that trade,” said Yung-Yu Ma, chief investment strategist at PNC Financial Services Group.
Technology and AI-linked stocks have stumbled several times this year. The emergence of a Chinese low-cost AI model called Deepseek at the start of the year sent shockwaves through tech stocks as it raised questions about massive capital spending. Similar questions also arose in August, briefly hitting tech stocks once again. The AI trade recovered from those setbacks and has thrived.
“There is a huge opportunity here, but it really just comes down to what’s priced in and what’s not,” said Steve Lowe, chief investment strategist at Thrivent Financial. “There is a lot of growth priced in, and that is one of the concerns, because there are still a number of risks that could trip up people’s expectations.”
Warning signs
While some of the market participants who point to risks remain bullish as the benchmark S&P 500 starts the fourth year of its bull run, investors have identified potential warning signs to watch for as tech and other major US companies begin reporting quarterly results in the days ahead.
Given massive capital expenditure required to build out infrastructure tied to AI applications, investors said they will watch the rate of spending and return on investments, and the potential for outlays to erode profitability.
Capex from major cloud computing and AI platform companies known as “hyperscalers” including Microsoft, Amazon, Alphabet, Meta Platforms and Oracle, is expected to roughly double from 2024 to 2027 to $500-billion annually, according to Barclays strategists.
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While these companies generate massive amounts of cash, it is important to watch whether they are “spending faster than their growth rates and eating into their free cash flow margins”, said Michael Arone, chief investment strategist for State Street Investment Management.
Investors are also wary of any surprise softening in the spending, given the importance of tech outlays to support the AI expansion.
“The bigger risk is not investing too much; it is not investing enough right now,” said Garrett Melson, portfolio strategist at Natixis Investment Managers Solutions.
There could be ramifications from potential “circular” deals involving AI companies with overlapping interests, such as Nvidia’s recent announcement it will invest up to $100-billion in OpenAI.
While the interdependent relationships within the AI ecosystem “do not appear sinister … there is significant systemic risk in such close financial and operational ties”, Irene Tunkel, chief US equities strategist at BCA Research, said in a note this week.
Tech companies have large cash resources to support AI spending and deal making. But a switch towards more leverage might raise eyebrows. “When you see these big announcements, you want to see it funded through cash flow, not debt or equity raises,” said Anastacio Teodoro, senior portfolio manager at Federated Hermes.
Barclays strategists are optimistic about the AI theme over the next 12-18 months, but they are also wary of signs the energy infrastructure may not be sufficient to support data centres and the AI-related build-out.
“The power issue is probably one of the most important gating factors you should be looking out for,” Venu Krishna, head of US equities strategy at Barclays, said on a recent call with journalists. Investors are also on guard for signals that demand is tailing off or that the massive investments are not paying off as anticipated.
Potential trigger
“One potential trigger is that suddenly the needs just look like they are going to be less than was originally anticipated,” PNC’s Ma said.
Patrick Ryan, chief investment strategist at Madison Investments, said there have yet to be many tangible signs of significant revenue and productivity gains stemming from AI.
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“If you get to the point where it becomes questionable that all of this investment was really going to pay off … that is going to be something that would be very at risk,” Ryan said. “How that happens, I can’t necessarily put my finger on it.” — Lewis Krauskopf, (c) 2025 Reuters
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