Goldman Sachs says this is ‘a key indicator for the durability of the AI trade’ By Investing.com

Goldman Sachs analysts have identified a key metric to gauge the longevity of AI trading: sales review. According to a report released Wednesday, while the AI ​​sector has seen significant growth, especially in the infrastructure phase, there are still doubts about its long-term profitability.

The report examines four phases of AI commerce, with the second phase, which includes companies operating in AI infrastructure such as semiconductor companies and cloud providers, showing the strongest performance.

Analysts noted that “the average return on stocks involved in building AI infrastructure (phase 2) has been 26% so far this year.” This phase has outperformed significantly, driven by large capital expenditures from the giant companies.

However, Goldman highlights that AI trading is under increasing scrutiny.

“Investors are increasingly concerned about the potential returns on AI spending by large computing companies,” they wrote. While spending on AI infrastructure continues, there has been a noticeable lag in revenue growth expectations for these investments.

The focus now shifts to reviewing the sales of companies involved in the later stages of AI adoption. Companies in the third stage, which are expected to generate profits from AI through software and IT services, have seen volatile performance.

Analysts noted that “potential revenue (Phase 3) stocks fell 19% between February and May,” a decline that reflects investor uncertainty about the timeline and size of returns from AI investments.

The durability of AI trading depends on the alignment of sales and profit growth with the large investments made. Historical precedents from the tech bubble era illustrate the risks of overinvesting without corresponding revenue growth.

Analysts stressed that “the sales review will be a key indicator for investors to assess the strength of the AI ​​trade.”

With the second-quarter earnings season approaching, it will be a crucial test of investor optimism based on current valuations. AI companies will need to prove that their investments translate into tangible sales and earnings growth to maintain their valuations. Early signs of failure to generate expected revenue could lead to a downgrade of these stocks, the report adds.

Moreover, Goldman Sachs notes that “the AI ​​capex cycle still pales in comparison to the tech bubble.” At the peak of the tech bubble, TMT stocks were spending more than 100% of their cash flow from operations on capex and R&D. By contrast, today’s leading TMT stocks, while seeing increased capex and R&D as a share of sales, have a more contained 72% of their cash flow.

Investors are advised to closely monitor upcoming earnings reports and sales forecasts to gauge the viability of AI-driven growth in the long term.

“The earnings growth needed for today’s mainframe companies to keep recent average ROI in line with current consensus earnings growth,” the analysts noted, adding that a broad-based economic slowdown could also challenge mainframe companies’ ROI.