How To Invest Ahead of a Potential AI Bubble Burst, According to Financial Experts
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Jordan Rosenfeld
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Molly Sullivan
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Artificial intelligence (AI) has quickly moved from a future concept to a major area of corporate spending, and investors have followed close behind. As AI stocks swing and questions about valuations resurface, many investors worry they are facing a bubble that’s about to pop, taking portfolios down with it.
Experts discussed how to invest ahead of a possible bubble and offered some general tips to keep your portfolio safe.
Is AI Really a Bubble?
Before even answering how to invest before an AI bubble, it’s good to look at whether a bubble is really happening. According to Scott Chou, co-founder at ESO Fund, he’s not sure AI volatility is parallel to the dot-com bubble burst of the ’90s.
“There’s no question that AI spending has surged, and some of it is over-concentrated, which can look like bubble behavior. But calling it a bubble overlooks the structural shift that’s underway,” he said.
While some AI companies won’t survive, much like during the dot-com era, he believes that those that succeed “will be transformative enough to justify the capital being poured into the space.”
Why AI Stocks Can Fall Even When the Technology Keeps Advancing
If AI stock bounces feel like a sign that AI adoption is in trouble or that a bust is on its way, Chou suggested these are more likely temporary market corrections. These are more likely to happen in AI-sectors “where investment has been aggressive,” and public markets thus grow nervous.
“Some of this fluctuation is what John Belton, portfolio manager at Gabelli Funds, called “risk-off price action and de-risking into year-end.” In other words, instead of seeing strong results as good news, investors interpret them as a sign that too much money is being spent on AI, which makes them worry about a contraction.
Valuation Bubble vs. Earnings Bubble
Not all bubbles look the same. Belton explained that there are two types of stock market bubbles: “valuation bubbles” and “earnings bubbles.” He said, “Valuations seem to simply reflect strong fundamentals without obvious excess. Are we in an earnings bubble? Time will tell,” he said.
However, Jack Fu, CEO of Draco Evolution, added that some caution flags include: “When valuations expand faster than fundamentals for an extended period, when earnings guidance stops improving but prices keep rising, and when the narrative becomes ‘this time is different’ without clear numbers behind it.”
Where Risk and Reward Diverge
An AI bubble may take more than just expanding AI infrastructure quickly to pop, according to Paul Meeks, managing director at Freedom Capital Markets. “While I see an AI bubble, I don’t see it popping for the next two years, so I still support owning the infrastructure builders.”
Aggressive spending on AI may look risky but not only is much of it “generating attractive returns,” Belton said, but the funds are also going to a large AI supply chain, according to Fu.
“People focus on the obvious AI winners, but there is an entire supply chain behind it. Data centers, power and grid infrastructure, cooling, networking equipment, semiconductor tools and cybersecurity all matter,” Fu said.
The Overlooked Factor That Can Trigger a Correction
Beyond revenue and compute power, one expert said the biggest determinant of long-term AI winners may be something far less visible to markets in the short term.
The biggest gap that will determine whether today’s enthusiasm for AI drives substantial, durable revenue is trust, according to Gerald Kierce-Iturrioz, CEO and co-founder of Trustible.
“When trust is present, adoption accelerates and budgets move from pilots to enterprise-wide deployments,” he explained. “When it isn’t, adoption stalls, incident risk rises, regulatory exposure increases and valuations can correct quickly.”
How Retail Investors Can Reduce Risk Without Missing AI’s Upsides
Rather than trying to time the peak of AI stock values, experts said retail investors should focus on position sizing, diversification and planning for volatility before it arrives.
“Another common mistake is thinking ‘AI’ is a single trade, then ending up with multiple positions that are all exposed to the same drivers,” Fu said.
Like most good investing, Chou added that everyone needs to know what the right time horizon is for their investment. “AI is not a short-term trend, and the companies that survive the shakeout will define the next decade of innovation,” he said.
Most investors can’t predict exactly when sentiment might shift. The best bet is to build AI exposure that can withstand volatility long enough to benefit from the technology’s real, though uneven, long-term adoption.
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