"Key variables of 'AI trading': The higher the exposure to the service sector, the greater the risk of AI disruption; 'AI infrastructure' is the most advantageous."

"Key variables of 'AI trading': The higher the exposure to the service sector, the greater the risk of AI disruption; 'AI infrastructure' is the most advantageous."

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Morgan Stanley recently pointed out that against the backdrop of rapid advancement in AI technology, investors need to distinguish between "infrastructure providers benefiting from AI development" and "service providers that may be disrupted by AI".

On February 14th, according to Wind Trading Desk, Morgan Stanley's latest quantitative research reveals that in AI-themed investing, "service sector exposure" has become a decisive variable. Data shows a significant negative correlation between service sector exposure and investment performance year-to-date—the higher the exposure, the greater the impact from concerns over AI disruption. Among them, the "AI Adopters" theme has a service sector exposure as high as 53% and ranks at the bottom in performance.

The report states that "AI Infrastructure" has only 14% service sector exposure, not only showing the strongest year-to-date performance, but also comprehensively leading in six major quantitative evaluation dimensions. Morgan Stanley believes this means that within the spectrum of AI investment themes, priority should be given to infrastructure sectors with minimal direct risk of AI disruption that benefit from structurally increased capital expenditure.

Concerns over AI disruption spread from software to broader service industries

Market concerns about AI disruption have spread from the initial software industry to broader service sectors, including financial consulting and brokerage services.

According to the report, as AI capabilities accelerate non-linearly, investors are reassessing the sustainability of profits from service-oriented business models. These worries are directly reflected in stock price performance of related industries, making "service sector exposure" an important driver for thematic investment performance.

Morgan Stanley's quantitative team classified the 25 industry groups under the Global Industry Classification Standard (GICS) into "service industries" and "non-service industries", and calculated the proportion of service sector weighting in the AI and tech diffusion theme and its four sub-theme portfolios.

The report states that, according to Morgan Stanley research, although these themes all fall under AI investment, their performance year-to-date shows a clear negative correlation with service sector exposure.

High risk exposure for "AI Adopters": 53% service sector exposure drags performance

Among AI-related themes, the "AI Adopters" sub-theme has the highest service sector exposure, reaching 53%, which is significantly higher than other themes.

Morgan Stanley notes that this theme focuses on companies adopting AI technology to improve operations and efficiency. However, it is precisely this high concentration in the service sector that makes it the weakest performing AI sub-theme.

According to the report, the core issue lies in uncertainty. As businesses accelerate AI adoption, concerns about the competitive landscape and pricing sustainability arise—these are the main worries reflected in current market pricing.

Stephen Byrd, Morgan Stanley’s Head of Thematic Research, suggests that a more selective approach is needed within the AI Adopters field, with emphasis on companies with pricing power.

"AI Infrastructure" breaks out: 14% service sector exposure + leads in six dimensions

Notably, the report points out a sharp contrast: the "AI Infrastructure" theme has only 14% service sector exposure—the lowest among all AI themes—and its year-to-date investment performance is the strongest.

This theme focuses more on computing power, semiconductors, and supporting hardware, and is less exposed directly to the risks of service sector disruption.

More importantly, AI infrastructure benefits from sustained capital expenditure and the structural demand for computing, semiconductors, and ancillary 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 thematic attractiveness: (1) Information Ratio; (2) Breadth of Earnings Estimate Revisions; (3) Bottom-up Morgan Stanley Earnings Forecast; (4) Valuation Level; (5) Mutual Fund Positioning; (6) Factor Exposure.

Morgan Stanley states that on this scorecard, AI Infrastructure stands out among AI themes: it shows robust risk-adjusted performance in both medium and short term; earnings estimate revisions have been strong in the past three months; mutual fund positioning is favorable, especially among outperforming funds.

 

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The above content is from Wind Trading Desk.

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