Goldman Sachs Issues AI Warning to Microsoft, Google, and Facebook: Beware of the Hype vs Reality

Goldman Sachs Raises Concerns Over US Tech Giants’ Massive Spending on Artificial Intelligence

Goldman Sachs Raises Concerns Over US Tech Giants’ Massive Spending on AI

Goldman Sachs has raised concerns about the staggering amount being spent on artificial intelligence (AI) by leading US tech giants, according to a report by Bloomberg. The report highlights the analysis conducted by strategists at Goldman Sachs, who closely examined the spending patterns of “hyperscalers” such as Amazon, Meta, Microsoft, and Alphabet.

Collectively, these tech behemoths have poured a jaw-dropping $357 billion into capital expenditure (capex) and research and development (R&D) over the past year, with a significant portion of this investment directed towards AI. In fact, AI accounts for nearly a quarter of the S&P 500’s total capex and R&D expenditure, indicating the immense focus on AI technologies by these companies.

Lead strategist at Goldman Sachs, Ryan Hammond, issued a warning in a note stating that the current hyperscalers must demonstrate that their AI investments will yield substantial revenues and earnings in the future. He emphasized that a lack of early returns could potentially lead to a decline in the valuations of these tech giants.

The report further reveals a sharp increase in spending on AI by the tech giants, with Amazon projected to reach a record $63 billion in capex this year, up from $53 billion in 2023. Meta and Alphabet are also expected to invest significant amounts in AI in 2024.

While the AI frenzy has propelled US stocks to all-time highs, with companies like Nvidia Corp. reaping the benefits, some investors are cautious about the sustainability of this trend. They believe that sectors like infrastructure and utilities might outperform the tech sector in the remaining months of 2024.

The strategists at Goldman Sachs draw parallels to the dot-com bubble era, cautioning that the current AI spending levels, while substantial, are still below the excessive capex witnessed during the early 2000s crash. However, they underscore potential risks, such as the depreciation of AI-related investments impacting profitability.

Hammond concludes by emphasizing the importance of monitoring sales figures as a key metric for investors to assess the longevity of the AI trade. As history has shown during the tech bubble, sales revisions will be crucial in determining if the AI investments are translating into tangible revenue growth.

In a landscape dominated by AI innovation, the scrutiny over the tech giants’ spending on this transformative technology underscores the evolving dynamics of the industry and the need for careful evaluation of investment strategies.

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