Source: Wall Street See

In the global capital markets, AI is undoubtedly a rising star in recent years. However, as AI technology develops and enters different stages, the market volatility becomes more and more evident.

In the latest research report released on the 10th, Goldman Sachs divides AI-related investments into four main stages, representing different levels from infrastructure construction to productivity improvement.

Goldman Sachs pointed out that AI trading has entered the second stage, gradually transitioning from simply relying on valuation growth to being driven by corporate profitability to boost market performance.

First and second stages: Infrastructure companies take over from hardware providers

Goldman Sachs believes that the first stage of AI trading is dominated by hardware providers, with Nvidia leading the way in this stage.

As the market matures, investors continue to have high confidence in AI development. Infrastructure companies start to take over, reaching the second stage.

Goldman Sachs points out that the focus of the second stage is on the construction of AI infrastructure, including semiconductor companies, cloud service providers, datacenters, equipment manufacturers, and utility companies.

These companies have benefited from the increase in AI capital expenditure, with some infrastructure stocks already up over 27% year-to-date in 2024. Goldman Sachs emphasizes that with the widespread application of AI technology, the stock prices of these companies could continue to rise, and the company's profitability will gradually become the main driver of the stock price increase, rather than relying solely on valuation expansion.

In addition, the valuation of phase two stocks is higher than the average level, reflecting the market's optimism.

Compared to the equally weighted s&p 500 stocks of the past 10 years, the trading prices of phase two stocks are 0.4 standard deviations higher. In contrast, phase three and four stocks are cheaper by 0.2 and 0.4 standard deviations respectively.

Goldman Sachs also points out that the surprise factor of the second phase AI spending is diminishing, indicating that the returns on these stocks may be more moderate. Nevertheless, the increase in demand may lead super large-scale technology companies to exceed expectations in AI-related capital expenditures.

In early 2023, the demand for nvidia chips far exceeded analyst expectations, and super large-scale capital spending became increasingly positive in the first half of 2024.

However, the magnitude of nvidia's sales surprise and super large enterprise capital expenditure surprises has been decreasing. The upcoming third quarter earnings season will provide another litmus test for AI demand and spending.

Phase Three: Uncertainty remains in the monetization of AI applications.

Goldman Sachs points out that phase three focuses on companies trying to generate additional revenue through AI technology, mainly software and IT service enterprises.

Although these companies have lower valuations, goldman sachs believes that the commercialization progress of AI applications is not as ideal as expected. Despite investors' high expectations for the future of AI applications, the actual application development and profitability still face challenges.

Goldman Sachs found through IT spending surveys that although there has been an increase in enterprise investment in AI technology in 2024, it is expected that only 3% of the IT budget next year will be used for the development and application of generative AI technology.

This means that AI-driven revenue growth is difficult to achieve in the short term, and investors still need to patiently wait for further development of AI technology.

However, the report also mentioned that platform stocks may stand out in the third stage. These platform companies, including microsoft, mongodb, datadog, etc., provide the best utilization of AI infrastructure and lay the foundation for building the next generation of applications.

Phase 4: Potential winners of productivity improvement

The fourth stage involves companies that are expected to achieve productivity improvements through AI. Goldman Sachs believes that these companies may achieve the greatest profit increase in the future due to the widespread use of AI, but currently, the comprehensive popularization of AI will still take several years.

According to Goldman Sachs' survey, only 6% of companies are already using generative AI in the production process, and the differences between industries are quite significant. For example, AI applications in manufacturing and technology industries are relatively widespread, while the acceptance in traditional industries is lower.

Goldman Sachs believes that only when the commercial use of third-stage AI applications is achieved on a large scale, will fourth-stage companies truly enter investors' view. This means that although fourth-stage companies have huge potential for growth, it is still difficult to see a significant performance improvement in the short term.

Editor / jayden