2026 was supposed to mark the year Wall Street’s trillion‑dollar artificial‑intelligence bet began delivering returns. Instead, the year has turned into a high‑stakes test of investor confidence.
In the first half, many AI‑related stocks surged to record highs as major hyperscalers such as Google’s Alphabet, Meta and Microsoft posted robust earnings.
Two of the industry’s biggest players, Anthropic and OpenAI, announced plans to go public, following SpaceX’s high‑profile IPO in June that briefly propelled Elon Musk to the world’s first trillionaire status. Meanwhile, AI models made notable strides on notoriously difficult tasks as the race to outperform human capabilities intensified.
Post-midterm AI sell-off rattles global markets amid Big Tech jitters
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AI doubts trigger market turbulence
The second half has brought far more volatility. While chipmaker Nvidia’s shares climbed higher last month, many hyperscalers and memory‑chip firms saw their stock prices swing wildly. A dramatic tech‑stock sell‑off followed the Democrats’ midterm victory, with the “Magnificent Seven”—including Meta, Apple, Amazon and Tesla—losing more than $1 trillion in a single trading day.
The AI sector suffered another blow when Nvidia’s stock plunged nearly 10 % over two days after its board and the FBI opened an investigation into CEO Jensen Huang’s alleged ties to a woman suspected of being a Chinese spy. On Thursday, Huang resigned after a second alleged marital affair surfaced, sending Nvidia’s shares even lower.
Wall Street is growing cautious about the sheer scale of AI spending, with warnings that future earnings may not justify the billions being poured into data centers. New pressure from U.S. lawmakers to curb AI‑data‑center expansion has added to the uncertainty.
In September, Goldman Sachs estimated that hyperscalers need roughly $300 billion in annual AI revenue to break even on their outlays, leaving a gap of about $230 billion.
“We’re not in Kansas anymore,” said Dennis Dick, chief market strategist at the Canada‑based Stock Trader Network, echoing a sentiment that investors now demand concrete results: “show me the money.”
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AI stocks needed a ‘healthy correction’
Other analysts argue that it is too early to call a bubble burst. Kit Rees, an investment strategist at London‑based wealth manager Quilter, described last week’s rout as a “healthy correction.”
“We’re still in the very early innings of the AI build‑out,” Rees told DW. “There’s still a lot of excitement around this technology and investors will want a slice of the pie.”
According to Goldman Sachs, roughly $800 billion has already been committed to capital expenditures this year, with plans for an additional $1.2 trillion in 2027 and $1.4 trillion in 2028.
Questions over timing of Anthropic IPO
While OpenAI has postponed its public offering until next year, the Claude‑maker Anthropic still intends to list later this month. On Tuesday the company said it would sell 825 million shares at a price range of $70–$78.
Dick expressed surprise at Anthropic’s decision to proceed amid the market’s recent turmoil. “Is this the best timing?” he asked.
Anthropic’s target valuation has slipped from an original goal of over $2 trillion to an estimated $1.2–$1.3 trillion. Its future worth hinges on whether it can achieve a Goldman Sachs forecast of more than $600 billion in revenue by 2030.
“If you get to a company with $600 billion in revenue, a $1.3 trillion valuation doesn’t sound that bad,” Dick noted. “But when you’re talking about a firm currently generating $52 billion in revenue, it feels over‑valued.”
Still, some observers remain bullish. Vivek Seth, CEO of Shaires Holdings, called Anthropic “a once‑in‑a‑generation company” with rapid growth and strong institutional backing. “Its IPO will establish a market‑clearing valuation as conditions stabilize,” he told Bloomberg.
Signs to watch, not reasons to flee
Rees believes many of the current market jitters may not signal an imminent crash. Instead, she suggests investors should monitor emerging indicators that the AI trade is maturing. Those could include a slowdown in AI‑related revenues, reduced demand for financing, or weaker appetite for debt and equity offerings.
Early data already point to a tightening of credit for AI‑focused infrastructure firms. Borrowing costs for companies like CoreWeave and Oracle have surged, and the cost of insuring Nvidia’s debt against default has risen 76 % in a single month, according to CNBC.
“They’ve been spending, some people say, like drunken sailors,” Dick observed, noting that Oracle’s balance sheet has been strained to the point where its stock is down 65 % from recent highs. “That has not stopped Oracle, along with Meta, Microsoft and Alphabet, from continuing to issue new AI bonds. Since the end of last month, the four AI giants have announced deals worth $67 billion.
Rees also highlighted regulatory developments as a potential braking factor. This summer, New York and Texas temporarily paused new data‑center approvals, and Texas Governor‑elect Gina Hinojosa has vowed to curb the heavy power and water usage that drives up household utility bills.
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Not ‘different this time’
Economist Gary Smith, in his forthcoming book “AI Mania: Blather, Bluster, and the Bubble of All Bubbles,” draws parallels between today’s AI frenzy and earlier speculative booms surrounding railroads, automobiles, television and the internet. He warns of a “frightful crash” when the bubble finally bursts.
Historical precedents show that even after dramatic corrections—such as the dot‑com collapse of 2000, when the Nasdaq lost roughly 80 % of its value—bubbles often outlive expectations, making timing difficult to pinpoint.
Joachim Klement, head of market strategy at UK‑based investment bank Panmure Liberum, believes a reckoning could arrive as early as next year. “My core conviction is that the AI bubble will either burst in 2027 or in 2028, so sometime in the next two years,” he told Bloomberg last month.