Chris Wood Warns of Massive Capital Destruction in US as China Challenges AI Boom

Christopher Wood, global head of equity strategy at Jefferies Hong Kong, has spent three decades building a reputation for spotting speculative bubbles before they burst — flagging the dot-com boom, Japan's credit bubble, and the U.S. housing bubble ahead of most of his peers. Now he's warning that China's rapidly advancing, cheaper approach to AI could trigger significant capital destruction for U.S. investors who have poured money into the American AI infrastructure buildout.

The Core of Wood's Thesis

Wood argues the "AI capex arms race" began in 2023 when Microsoft invested in OpenAI, and that investors are missing a crucial dynamic: nearly all the money made so far from the AI boom has flowed not to the companies building AI products, but to those selling the infrastructure underneath them. "You want to own what I call the picks and shovels of AI," Wood said, pointing to companies like Nvidia and other semiconductor and data-center builders as the real profit-takers of the boom so far. His central concern: "It's completely unclear to me who's going to monetize and make money out of all this capex," setting up what he views as an almost-inevitable overinvestment bust.

Why China Changes the Calculus

Wood believes large language model providers will ultimately behave like utilities — capital-intensive, commoditized, and unlikely to earn sustainable returns. He argues China's AI advantage is likely to show up not in building the most powerful frontier models, but in cheap applications made possible by open-source models and inexpensive power, saying flatly that "China basically has unlimited access to cheap energy, whereas the U.S. has this massive energy bottleneck." That view has already translated into portfolio action at Jefferies: global macro strategist Mohit Kumar told Fortune the firm has "actually reduced our exposure to U.S. tech," arguing China may be the "big winner" in the AI race given valuation, wider adoption, and its power-generation advantage.

What's Driving the Chinese Approach

Other panelists have echoed Wood's framing of the strategic divergence between the two countries: Chan Yip Pang, executive director at Vertex Ventures SEA and India, put it as "China is focused a bit more on diffusion, while the U.S. focuses more on perfection." Wood has pointed to fear as much as opportunity in explaining why U.S. tech giants keep spending so aggressively, saying bluntly that companies are "terrified of being disrupted" and that "massive FOMO" is what's driving the arms race.

Not the Only Voice Raising the Alarm

Wood isn't alone in flagging this risk. At the Bloomberg Forum for Investment Management in Sydney, John Pearce, Chief Investment Officer at Australia's A$158 billion UniSuper pension fund, warned that continued Chinese progress in AI could trigger a sudden sell-off among U.S. tech giants, saying that if Chinese firms can develop comparable large language models "much, much cheaper" with the same output, "that's going to put a big question mark on your business model." Pearce described the risk of further "DeepSeek moments" — sudden demonstrations that cheaper Chinese models can match Western performance — as an immediate threat to U.S. tech valuations.

A Slightly Different Take on the Actual Trigger

In more recent comments, Wood has refined his framing of exactly what would end the AI boom, arguing it's unlikely to be a chip glut or oversupply issue. Instead, he believes the trade unwinds when investors realize hyperscalers simply cannot generate adequate returns on their massive AI investments — a concern rooted in capital misallocation rather than physical supply constraints, which he warns could trigger a prolonged pause in the broader AI trade rather than a sudden crash.

How Wood Has Repositioned

Consistent with his public warnings, Wood has already begun adjusting his own portfolio positioning in response to these concerns, favoring the "picks and shovels" infrastructure names he views as having genuine, demonstrated profitability over the broader universe of AI application companies whose long-term monetization path remains, in his view, unproven.

Why It Matters

Wood's warning carries particular weight given his track record of identifying prior speculative bubbles well ahead of consensus. If his thesis proves correct — that Chinese firms can deliver comparable AI capability at a fraction of the cost through open-source models and cheaper energy — the resulting pressure on U.S. AI infrastructure valuations could be severe, given how concentrated recent market gains have been in a relatively small number of AI-linked mega-cap names.

What's Next

With Jefferies already trimming its U.S. tech exposure and other prominent investors like UniSuper's Pearce voicing similar concerns, the debate over whether China's cheaper, open-source AI approach represents a genuine existential threat to U.S. AI valuations — or simply a competitive pressure that gets absorbed without triggering broader capital destruction — is likely to remain one of the defining questions for global markets through the rest of 2026.