Finance
Analysis-Investors on guard for risks that could derail the AI gravy train
Published by Global Banking and Finance Review
Posted on October 15, 2025
5 min readLast updated: January 21, 2026
Global Banking and Finance Review
Company
Published by Global Banking and Finance Review
Posted on October 15, 2025
5 min readLast updated: January 21, 2026
Investors are cautious about risks affecting AI market growth, focusing on capital expenditures and financial strategies of tech companies.
By Lewis Krauskopf
NEW YORK (Reuters) -Optimism over the profit potential of artificial intelligence has helped drive the U.S. 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 fueled enthusiasm about the technology's potential. Citigroup strategists estimate that nearly 50% of the S&P 500's overall roughly $57 trillion in market capitalization 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."
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 U.S. companies begin reporting quarterly results in the days ahead.
MASSIVE CAPEX SPENDING IN FOCUS
Given massive capital expenditures 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.
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 U.S. equity 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 toward 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.
EYEING RETURN ON INVESTMENTS
Barclays strategists are optimistic about the AI theme over the next 12 to 18 months, but they are also wary of signs the energy infrastructure may not be sufficient to support data centers 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 U.S. equity 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.
"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.
"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."
(Reporting by Lewis Krauskopf; Editing by Alden Bentley and Nick Zieminski)
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans.
Capital expenditure (CapEx) is the funds used by a company to acquire, upgrade, and maintain physical assets such as property, buildings, and technology.
Return on investment (ROI) is a financial metric used to evaluate the profitability of an investment, calculated as the net profit divided by the initial cost of the investment.
Tech stocks are shares in companies that operate in the technology sector, including software, hardware, and IT services.
Market capitalization is the total market value of a company's outstanding shares, calculated by multiplying the share price by the total number of shares.
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