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Goldman has an ‘AI hype vs reality AI warning’ for Microsoft, Google & Facebook – ET CISO
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Goldman Sachs has raised concerns about the massive spending on artificial intelligence (AI) by the US tech giants, according to a report by Bloomberg. The report cites strategists at Goldman Sachs, who analyzed spending by “hyperscalers” like Amazon, Meta, Microsoft, and Alphabet. These companies have collectively spent a whopping $357 billion on capital expenditure (capex) and research and development (R&D) in the past year.
A “significant portion” of this spending, according to the strategists, is directed towards AI, representing nearly a quarter of the S&P 500’s total capex and R&D expenditure.
Goldman Sachs’ lead strategist, Ryan Hammond, warns in a note that “today’s hyperscalers will eventually be required to prove that revenues and earnings will be generated from their investments.” He emphasizes that a lack of early signs of return could lead to a decrease in the valuations of these companies.
Spending on the Rise
Data compiled by Bloomberg shows that tech giants are ramping up their spending. Amazon’s capex is expected to reach $63 billion this year, up from $53 billion in 2023. Meta and Alphabet (Google’s parent company) are also projected to spend record amounts in 2024.
AI Hype vs Reality
While the excitement surrounding AI has driven US stocks to record highs this year, with Nvidia Corp. being a prime beneficiary, some investors are looking beyond the hype. They believe sectors like infrastructure and utilities might outperform in the rest of 2024.
A Dot-Com Bubble Replay
The strategists caution that the current AI spending spree “still pales in comparison” to the capex levels witnessed during the dot-com crash. They point out that at the peak of the tech bubble in the early 2000s, tech, media, and telecom companies were spending over 100% of their operating cash flow on capex and R&D. Currently, this figure stands at 72%.
Despite the lower spending ratio compared to the dot-com era, Goldman Sachs sees potential risks. The depreciation of AI-related investments could negatively impact profitability, according to Hammond. He concludes by stating that, “as demonstrated in the tech bubble, sales revisions will be a key indicator for investors to assess the durability of the AI trade.” This implies that investors will be closely monitoring sales figures to determine if the AI investments are translating into actual revenue growth.
