Goldman Sachs Analysts Identify Key Measure for Assessing Longevity of AI Trade
Goldman Sachs analysts have pinpointed a crucial metric for evaluating the sustainability of the AI trade: sales revisions. In a recent report released on Wednesday, they highlighted the significant growth of the AI sector, especially in its infrastructure phase, while also acknowledging lingering doubts about its long-term profitability.
The report delineates four distinct phases of the AI trade, with Phase 2 standing out as the most robust performer. This phase encompasses companies involved in AI infrastructure, such as semiconductor firms and cloud providers, which have shown exceptional performance. According to the analysts, stocks in this category have returned an impressive 26% year-to-date, propelled by substantial capital investments from hyperscalers.
Despite the success of Phase 2 companies, Goldman Sachs emphasizes that the AI trade is facing increasing scrutiny. Investors are becoming more apprehensive about the potential returns on the significant AI investment spending by hyperscalers. While expenditures on AI infrastructure persist, there has been a noticeable lag in revenue growth projections, raising concerns about the profitability of these investments.
The focus is now shifting towards companies in the later phases of AI adoption, particularly Phase 3, which are expected to monetize AI through software and IT services. However, these companies have experienced volatile performance, with stocks witnessing a 19% decline between February and May. This downward trend reflects investor uncertainty regarding the timing and extent of returns from AI investments.
The sustainability of the AI trade hinges on aligning sales and earnings growth with the substantial investments being made. Historical examples from the Tech Bubble era highlight the risks of excessive investment without corresponding revenue growth. The analysts stress that sales revisions will be a crucial indicator for investors to evaluate the durability of the AI trade.
As the second-quarter earnings season approaches, it will be a critical test for the optimism embedded in current valuations. Companies involved in AI must demonstrate that their investments are translating into tangible sales and earnings growth to justify their valuations. Failure to meet revenue expectations could result in a downgrade of these stocks.
Furthermore, Goldman Sachs points out that the AI capex cycle is still relatively modest compared to the Tech Bubble era. While TMT stocks during that time were spending over 100% of cash flows on capex and R&D, today's leading TMT companies have more controlled spending at 72% of cash flows.
Investors are advised to closely monitor upcoming earnings reports and sales projections to assess the long-term viability of AI-driven growth. It is crucial for hyperscalers to achieve the necessary earnings growth to maintain their recent ROI, especially in the face of a potential economic slowdown that could challenge their returns on investment.
In conclusion, the analysis underscores the importance of sales revisions in evaluating the sustainability of the AI trade and highlights the potential risks and rewards for investors in this evolving sector.