Christopher Wood of Jefferies highlights signs of AI trade fatigue, advocating for investments in India and China as value opportunities amid shifting market dynamics.
New Delhi, India Jul 10, 2026 ALN: Emerging bull Christopher Wood has raised concerns about the apparent fatigue in the AI trade, prompting Jefferies to adjust its investment strategy towards undervalued like India and China. Wood believes that the so-called "picks and shovels" companies involved in the AI capital expenditure (capex) boom will continue to outperform, especially as investors rotate away from crowded AI winners. This shift in focus comes at a time when the AI market, having experienced significant growth, may be facing a critical juncture.
In his newsletter, 'GREED & fear', Wood notes that the new quarter has begun with increasing discussions around "AI fatigue". This term refers to the growing sentiment among investors that the exuberance surrounding AI stocks may be waning, leading to a reassessment of investments in this sector. Investors are reportedly on the lookout for a peak in momentum, seeking cheaper value stocks that have not participated in the AI surge. He cites Tencent as a notable example of an Asian company positioned to benefit from this trend. Wood argues that the recent sharp pullbacks in South Korea’s AI leaders are both natural and healthy, as the Kospi index has fallen 22% from its June peak, with leveraged ETFs on major companies like SK Hynix and Samsung Electronics dropping around 30% from their highs.
Highlighting the extreme nature of the AI rally, Wood points out that since the beginning of 2023, a market-cap-weighted basket of Micron, SK Hynix, and Samsung Electronics has surged approximately 760%, compared to a 180% gain for a basket of tech giants like Alphabet, Amazon, Meta, and Microsoft. This stark contrast illustrates the varying degrees of success among different players in the tech sector, raising questions about sustainability and future growth. Wood emphasizes a preference for owning DRAM manufacturers, stating that demand for computing power will continue to grow even as the costs of AI tokens decline. However, he expresses uncertainty about which hyperscalers will successfully monetize their AI investments, a concern that reflects broader market apprehensions regarding the long-term viability of certain tech stocks.
Jefferies estimates that the four major US hyperscalers will spend around $700 billion on capex this year, with projections exceeding $800 billion next year and potentially surpassing $1 trillion by 2027. This figure represents roughly 3% of US GDP and about 22% of non-residential fixed investment, highlighting the significance of AI in the current landscape. Wood describes this phenomenon as "the mother of all cycles", indicating the unprecedented scale and impact of AI-related investments on the economy.
Despite the massive spending, Wood warns that the financing and accounting practices surrounding this capex arms race are becoming increasingly stretched. The hyperscalers have raised their projected capex to a staggering 92% of their projected operating cash flow, collectively issuing $169 billion in bonds this year and accumulating $662 billion in future data-center lease commitments that remain off balance sheet. Total undiscounted lease obligations are nearing $969 billion, a figure that underscores the potential risks associated with such high levels of debt and financial commitments. The implications of these financial strains could reverberate throughout the tech industry, affecting investment strategies and market dynamics.
In light of these developments, Jefferies is intentionally reallocating its Asia Pacific ex-Japan asset allocation towards less influenced by AI momentum. In its latest GREED & fear report, the firm recommends a 12% weight for India, compared to a 10.9% benchmark weight in the MSCI AC Asia Pacific ex-Japan index, resulting in a positive mismatch of 1.1 percentage points. This strategic shift reflects a growing recognition of India's potential as a market that offers value stocks with strong fundamentals, distinct from the high-flying AI sector.
Despite a correction in memory stocks, Jefferies remains underweight on Taiwan and neutral on Korea, having reduced Korea’s neutral weighting from 24.6% to 20.8% since late June. Wood emphasizes that like India, which hosts cheaper value stocks that have not been part of the AI trade, these are well-positioned to benefit from a sustained rotation away from momentum AI names. This repositioning could provide investors with opportunities to capitalize on undervalued assets that are less correlated with the volatile AI sector.
China is another focal point in Jefferies’ strategic rotation. Wood believes it is too late to sell MSCI China or Hong Kong stocks, asserting that these are poised to benefit from a mean reversion away from momentum AI names. The MSCI China index has sharply de-rated to just 10.6 12-month forward earnings, down from 13.9 in October 2025 and 18.5 in early 2021. While the CSI 300 has gained 11.9% in the first half of 2026, MSCI China has declined 14.9% in US dollar terms. This disparity indicates a potential opportunity for investors looking for value in a market that has been overlooked in favor of AI-centric stocks.
Wood acknowledges concerns regarding falling household loans and rising retail non-performing loans but maintains that consumption is stabilizing at a lower share of GDP. He believes that China will avoid a self-reinforcing negative equity cycle in the residential property market, with consumer and domestic-demand stocks already pricing in much of the macro strain. This perspective suggests a cautiously optimistic view of the Chinese economy, despite the challenges it faces, and highlights the potential for recovery in sectors that are not directly tied to the AI boom.
To contextualize the current AI cycle, Jefferies notes that US investment in information-processing equipment and software has reached 4.88% of nominal GDP in the first quarter of 2026, surpassing the 4.46% peak during the dot-com boom. Wood emphasizes that earnings from this capex boom are "front-end loaded" in favor of picks-and-shovels suppliers, as hyperscalers spent $130 billion on capex in the first quarter of 2026 but only booked $41.6 billion in depreciation and amortization, leading to potentially overstated profits. This phenomenon raises questions about the sustainability of growth in the AI sector and the long-term profitability of companies heavily invested in AI technologies.
With the Hyperscalers-4 index underperforming the S&P 500 by 11% since early May and AI leaders falling from their highs, Wood argues that investors can no longer overlook the risks associated with monetization, financing, and political resistance to data-center projects. The challenges faced by hyperscalers, including regulatory hurdles and public scrutiny, could impact their ability to execute on ambitious AI projects and maintain profitability in the face of rising costs and competition.
He concludes that as long as the AI capex arms race continues, the beneficiaries will remain the picks-and-shovels companies, which are the ones profiting from the capex, rather than the companies spending the money. This assertion underscores the importance of distinguishing between companies that provide the necessary infrastructure and those that are heavily reliant on AI for their business models.
In summary, Jefferies is repositioning its investments towards India, China, and other Asian that are likely to gain from a long-overdue rotation away from AI momentum. This strategic shift reflects a broader trend in the investment landscape, as market participants seek to navigate the complexities of the evolving tech sector and identify opportunities in undervalued regions. As the AI narrative continues to unfold, the implications for investors will be significant, requiring a careful analysis of both risks and opportunities in this dynamic environment.
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