--- title: "Morgan Stanley's Xing Ziqiang: AI Investment Enters \"Halftime,\" a \"September 24\"-Style Reversal Unlikely in the Near Term" type: "News" locale: "en" url: "https://longbridge.com/en/news/294606250.md" description: "Xing Ziqiang, Chief Economist at Morgan Stanley, pointed out that AI investment is entering a \"halftime break,\" and a policy reversal similar to the \"September 24\" shift is unlikely to recur soon. He believes the recent volatility in global tech stocks results from the interplay of macroeconomic factors and micro-level return on investment narratives. Although major tech companies have not reduced their investment plans, the market has already priced in the positive news and entered a consolidation phase" datetime: "2026-08-02T12:08:57.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/294606250.md) - [en](https://longbridge.com/en/news/294606250.md) - [zh-HK](https://longbridge.com/zh-HK/news/294606250.md) --- # Morgan Stanley's Xing Ziqiang: AI Investment Enters "Halftime," a "September 24"-Style Reversal Unlikely in the Near Term Within the industry, Xing Ziqiang, Chief Economist at Morgan Stanley, is an analyst known for both his popularity and professional expertise. He accurately captured the window of China's macroeconomic policy shift in September 2024, alerting global institutions in advance to the intensification of policies aimed at stabilizing growth. He has also provided forward-looking and in-depth analysis of many characteristics of China's economy in recent years, predicting the pace of real estate adjustment, the relocation of industrial chains, the export boom of the "new three items," and changes in the AI computing power investment cycle, influencing the asset allocation of numerous institutions. On July 30, 2026, Xing Ziqiang spoke at a Morgan Stanley communication session in Shanghai, offering his latest judgments on policies for the second half of the year, the "K-shaped divergence" of the economy, AI competition, and the recent volatility in global tech stocks. What he said is certainly intriguing. ## **This Round of Tech Stock Adjustment Driven by Global Resonance** Regarding the recent severe fluctuations in global tech stocks, Xing Ziqiang believes the adjustment was triggered by the intertwining narratives of macroeconomic factors and micro-level return on investment. He considers the market turbulence seen in China's A-shares during this period to be a microcosm of the global AI tech resonance. In his view, this round of the AI investment cycle was initiated by US large tech companies announcing plans to build computing centers. However, the benefits of the industrial chain did not remain solely in the US but spread to related companies in South Korea and China. Among them, companies in South Korea and Taiwan participated more in chips, memory, and other segments, while mainland Chinese companies primarily engaged in global division of labor through optical modules, PCBs, and other links. However, since related companies in various regions are still within the same global investment cycle, they are simultaneously affected in the capital markets. ## **The AI Narrative Has Changed** Xing Ziqiang further clarified that changes in the AI narrative do not necessarily reflect fundamentals. The investment plans announced by these major AI companies for this year and next have not been cut; they have even been slightly increased, with planned investments of approximately $800 billion this year and about $1.2 trillion next year. Orders in the industrial chain have not shown significant problems, yet the capital market has still experienced a "rollercoaster-style" adjustment. In response, he believes that one must often respect the market, as it may have already priced in much of the good news for the next one to two years in advance. Historically, every major technological revolution has often been accompanied by overinvestment and excessive prosperity, followed by a "moment of reckoning" in financial markets where stock prices align with financial costs. However, Xing Ziqiang emphasized that this reckoning does not mean investments are completely "wasted," nor does it imply that they are unhelpful to productivity or the economy. He cited the internet investment boom of the late 1990s as an example. Infrastructure such as broadband routers and submarine cables ultimately enhanced global economic productivity, but some "shovel-selling" companies still experienced a "moment of reckoning" in stock prices and financial returns after the dot-com bubble burst. Believing that AI will change human productivity and represent progress—a massive technological revolution—is entirely consistent with the current market volatility. ## **Shifting from "Selling Shovels" to "Using Shovels"** Citing the views of Morgan Stanley's US, Asia-Pacific, and China strategy teams, Xing Ziqiang suggested that AI investment may be entering a "halftime break" stage, and the market's focus needs to shift from "selling shovels" to "using shovels." "We need to broaden our horizon. We should not look solely at AI semiconductor computing power but pay attention to the many companies that can benefit from applying AI." In the recent past, the market mainly focused on chips and memory, the so-called "shovel-selling" segments. In the next phase, the focus may gradually shift to which companies can truly use these "shovels" to enhance their own productivity and increase revenue. He summarized this change as an expansion from AI infrastructure providers to AI adopters—companies that can increase revenue, improve efficiency, and reduce costs through AI. ## **Unable to Answer Questions About Bottom-Fishing** Xing Ziqiang also explicitly stated that he could not answer questions such as whether now is the right time to buy the dip amid market volatility. However, from the broader global perspective of investing in the next stage of the industrial and technological revolution driven by AI, China has advantages. At the same time, the boundaries of the AI ecosystem may continue to expand. Some energy, resource, and strategic raw material companies, which are not superficially AI tech companies, may enter this system due to the growing demand for electricity, energy storage, and scarce resources driven by AI. Morgan Stanley's strategy team refers to some of these areas as having "HALO assets" characteristics. They are not easily replaced by AI and may become even scarcer as AI infrastructure expands. Therefore, the so-called "second half" of AI does not mean the end of AI investment, but rather that market attention may gradually expand from the narrow segments of semiconductors and computing power to applications, energy, and a broader industrial ecosystem. Within the broad AI ecosystem, China has significant advantages in energy transition and will provide better green energy technology products to the world. The rise of domestic large language models, with their low token costs, also presents clear advantages if the global AI industry can successfully commercialize. ## **More and More People Believe in AI** In Xing Ziqiang's view, the most worrisome change in AI trading is not that investors suddenly disbelieve in AI, but that more and more people believe in it. Six months ago, if someone suggested that a 25 basis point rise in US interest rates might impact AI investment, a considerable number of "junior fund managers" would have argued that such an interest rate change was insufficient to affect a technology revolution that "changes humanity." As the cognition of these "junior fund managers" influenced the "senior veterans," becoming a consensus among global capital, the market structure exhibited highly crowded trading phenomena." So-called crowding is first reflected in leveraged funds concentrating bets on AI computing infrastructure. Citing the South Korean market as an example, Xing Ziqiang noted that from the end of last year to the first half of this year, the market saw several leveraged ETFs with multiple times long exposure. Typically, a massive influx of such leveraged funds is often a characteristic of the latter stage of a speculative, investment, or sector-specific bull market. When regulatory policies tighten, or when expectations for liquidity and interest rates change, leveraged funds tend to amplify market volatility. The second pressure comes from the primary market and the bond market. The capital required for AI computing centers is enormous. Some leading tech companies can no longer cover all capital expenditures solely with their operating cash flows and need to continue financing through IPOs, secondary offerings, and bond issuances. "From the first half of this year to the first half of next year, in just one year, these companies need to raise $1 trillion in the public markets through debt and equity issuance, continuously absorbing or 'draining' liquidity." This means that while leveraged funds in the secondary market concentrate bets on AI, AI companies continue to absorb liquidity from the stock and bond markets. The market will become more sensitive to marginal changes in inflation, oil prices, interest rates, and central bank policies. These intertwined factors have triggered some changes in the AI narrative. ## **Another AI Industrial Path** Discussing AI competition, Xing Ziqiang believes that China is taking a different path. China relies more on system integration, power supply, engineer dividends, and algorithm optimization to reduce the cost of using AI. The most impactful data point is token cost. "The token cost of domestic large models is roughly only 1/10th of that in the US, which is indeed cheap." The value of low costs is gradually manifesting on the corporate side. Previously, some overseas companies encouraged employees to use the most advanced models extensively. However, as token bills continued to grow, companies began to tier AI tasks, assigning complex, long-term tasks to the most advanced models and simple, short-term tasks mostly to lower-cost open-source models. Xing Ziqiang therefore proposed whether China could replicate the experience of the 2G, 3G, and 4G eras by building AI computing power into a cheap, widely accessible digital infrastructure. During the mobile internet era, China lowered the barriers to entrepreneurship and application innovation through strong network infrastructure and relatively low fees. Similarly, if future support is provided through renting capacity from a national computing network, it could be China's version of a digital infrastructure solution. Regarding chip usage, Xing Ziqiang proposed a "dual-track computing system." On one hand, training the most frontier models still requires the world's most advanced chips. On the other hand, during the inference and application stages, the performance requirements for individual chips are relatively lower, allowing domestic chips to gain more application opportunities through state-led computing centers. After domestic chips gain more applications in the inference end, they can accumulate feedback through "learning by doing," continuously optimizing systems and efficiency. ## **"The 'September 24' Turning Point Has Not Yet Arrived"** Returning to China's macroeconomic policies, Xing Ziqiang directly stated in a report title that the "September 24"\-style turning point has not yet arrived. Xing Ziqiang stated that although some economic indicators weakened in the second quarter, recent policy documents and official statements show that policy focus remains concentrated on technology, energy, industrial autonomy and security, and resolving "chokehold" issues. "Even if the economy slowed in the second quarter, if we were to find a lever to support the bottom, it would likely still follow the path of grasping technology and energy transition. In other words, the possibility of starting from the investment side is greater than from the consumption side." Additionally, in Xing Ziqiang's view, the second half of this year is more likely to see the accelerated implementation of fiscal resources within the annual budget framework that have not yet been deployed, rather than a sudden expansion of the deficit or the issuance of new large-scale special sovereign bonds. He stated that there is over 2 trillion yuan of fiscal remaining capacity available for use in the second half of the year, found in the outstanding balances of central and local government debt, as well as in previously established new financial instruments. From a specific directional perspective, it will likely still be on the investment side, including power grids and energy storage in the energy sector, and AI and computing power in the technology sector. ## **"Divergence" Difficult to Resolve in the Short Term** Furthermore, Xing Ziqiang believes that the economic "divergence" situation will be difficult to resolve in the short term. The upward end includes AI and the "new three items" in energy; the downward end includes domestic demand, consumption, real estate, and employment. Addressing this structural issue, Xing Ziqiang proposed three recommendations. First, optimize the trade-in policy by shifting some trade-in resources from durable goods like cars and home appliances to service consumption such as dining, entertainment, and tourism. Second, consider whether hard-tech industries that are already in a global upcycle with high export growth rates still need to maintain strong export tax rebates and fiscal support. The saved resources could be considered for tax cuts in the domestic service and consumption sectors. Third, continue to improve the social security system to reduce residents' precautionary savings. Risk Warning and Disclaimer The market carries risks; investment requires caution. This article does not constitute personal investment advice, nor does it take into account the specific investment objectives, financial status, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article align with their specific circumstances. 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