Key variables of "AI trading": the higher the exposure of the service industry, the greater the risk of AI disruption, "AI infrastructure" is most advantageous.

Morgan Stanley pointed out in its latest report that in the context of rapid evolution of AI technology, investors need to distinguish between "infrastructure providers benefiting from AI development" and "service providers that may be disrupted by AI". According to news from Wind Trading Platform on February 14, Morgan Stanley's latest quantitative research reveals that in AI-themed investments, the "exposure in the service industry" has become a decisive variable. Data shows that the performance of investments from the beginning of the year to now is significantly negatively correlated with the exposure in the service industry - the higher the exposure in the service industry of a theme, the greater the impact from concerns about disruption by AI. Among them, the theme of "AI Adopters" has a high exposure in the service industry at 53%, ranking at the bottom in performance. The report stated that the exposure in the service industry for "AI Infrastructure" is only 14%, not only showing the strongest performance from the beginning of the year, but also leading in all six major quantitative evaluation dimensions. Morgan Stanley believes that this implies in AI investment themes, priority should be given to allocating to the infrastructure sector with the least risk of direct AI disruption and benefiting from the growth in structural capital expenditures. Concerns about AI disruption have spread from software to a wide range of service industries Market concerns about AI disruption have expanded from the initial software industry to a wider range of service industries, including financial consulting and brokerage services. According to the report, as AI capabilities accelerate non-linearly, investors are reassessing the profitability sustainability of service-oriented business models. This concern is directly reflected in the stock performance of related industries, making the "exposure in the service industry" an important factor driving the performance of theme investments. Morgan Stanley's quantitative team classified 25 industry groups in the Global Industry Classification Standard (GICS) into "service industry" and "non-service industry" categories, and calculated the proportion of weightage in the service industry in AI and technology diffusion themes and their four sub-theme investment portfolios. The report stated that according to Morgan Stanley's research findings, although these themes fall under the category of AI investments, their performance from the beginning of the year to now shows a clear negative correlation with exposure in the service industry. "AI Adopters" high risk exposure: 53% service industry exposure dragging performance Among AI-related themes, the sub-theme of "AI Adopters" has the highest exposure in the service industry, reaching 53%, significantly higher than other themes. Morgan Stanley indicated that this theme focuses on companies that are adopting AI technology to improve operational models and efficiency. However, it is this high concentration in the service industry that makes it the worst performing AI sub-theme. According to the report, the core issue lies in uncertainty. As companies accelerate the adoption of AI, concerns arise about competitive dynamics and the sustainability of pricing - which is the core concern reflected in current market pricing. Stephen Byrd, Head of Theme Research at Morgan Stanley, recommends that in the area of AI adopters, more careful selection is needed, focusing on companies with pricing power. "AI Infrastructure" breaking through: 14% service industry exposure + leading in six dimensions It is worth noting that the report pointed out that in contrast, the exposure in the service industry for the theme of "AI Infrastructure" is only 14%, the lowest among all AI themes, while its investment performance from the beginning of the year to now is the strongest. This theme focuses more on areas such as computing power, semiconductors, and supportive hardware, with less direct exposure to risks of service industry disruption. More importantly, AI infrastructure benefits from continuous capital expenditures and structural demand for computing, semiconductors, and complementary hardware. This demand is not a short-term phenomenon, but a long-term trend accompanying the development of AI technology. Morgan Stanley uses six quantitative dimensions to evaluate the attractiveness of themes: (1) information ratio; (2) breadth of earnings expectations revision; (3) bottom-up Morgan Stanley earnings forecasts; (4) valuation levels; (5) mutual fund positions; and (6) factor exposure. Morgan Stanley stated that on this scorecard, AI Infrastructure has shown outstanding performance in AI themes: showing strong risk-adjusted performances in the short to medium term; strong earning expectations revisions in the past three months; favorable mutual fund positions, especially in high-performing mutual funds where holdings are more active. This article is reposted from "Wall Street News", author: Dong Jing; GMTEight editor: Chen Siyu. (Note: This is a general translation of the text provided, as accurate as possible but may not be perfect.)