Tech giants set to invest over $1 trillion in AI infrastructure
\nExperts express skepticism about AI\u2019s cost-effectiveness
\nDespite differing views, Goldman Sachs analysts remain optimistic about AI\u00a0<\/p>\n
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Tech giants are expected to spend over US$1 trillion on artificial intelligence infrastructure in the coming years, which includes investments in data centres, chips, and power grids.<\/p>\n
The Magnificent 7<\/em>, which refers to seven tech stocks closely related to AI, have also contributed a significant portion of the stock market\u2019s returns in recent years, including in 2024.<\/p>\n But despite this massive outlay and relentless rally, the future return on investment remains uncertain.<\/p>\n Goldman Sachs<\/strong> has recently published a report<\/a> outlining its insights on the potential of AI,\u00a0highlighting the differing expert opinions on AI for both the economy and investors.<\/p>\n \u00a0<\/p>\n Daron Acemoglu<\/strong>, an MIT professor, is among the skeptics.<\/p>\n He believes that AI will have limited economic benefits over the next decade. According to him, only a small fraction of tasks\u2014or around a quarter of AI-exposed tasks\u2014will be cost-effective to automate.<\/p>\n This implies that AI will impact less than 5% of all tasks, leading to a modest 0.5% increase in productivity and a 0.9% boost in GDP over ten years.<\/p>\n Acemoglu also questions the belief that AI technology will improve rapidly and become more cost-effective. He argues that advances in AI models are unlikely to occur as quickly or be as impressive as many expect.<\/p>\n \u201cGiven the focus and architecture of generative AI technology today, truly transformative changes won\u2019t happen quickly and few \u2013 if any \u2013 will likely occur within the next 10 years,\u201d said Acemoglu.<\/p>\n He also doubts that AI will create new tasks and products at a significant rate, which is crucial for substantial economic impact.<\/p>\n Jim Covello<\/strong>, Head of Global Equity Research at Goldman Sachs, shares similar doubts.<\/p>\n He argues that AI is not designed to solve the complex problems that would justify its high costs.<\/p>\n He points out that past revolutionary technologies, like the internet, provided low-cost solutions that disrupted existing high-cost solutions.<\/p>\n In contrast, AI remains expensive and may not see significant cost reductions.<\/p>\n Covello isn\u2019t the only one who thinks companies are spending too much on AI.<\/p>\n David Cahn<\/strong> from Sequoia Capital says tech companies need to earn US$600 billion per year to justify their current AI investments. This figure is about six times higher than his best-case revenue projection for the AI industry.<\/p>\n However, Cahn says that if the AI industry is indeed a bubble, its burst might not be as severe as the dot-com crash.<\/p>\n He suggests that today\u2019s tech giants have more cash reserves than companies did back in 2000, potentially cushioning the impact.<\/p>\n \u00a0<\/p>\n On the other hand, some analysts at Goldman Sachs remain optimistic.<\/p>\n While current AI automation isn\u2019t cost-effective, GS senior global economist Joseph Briggs<\/strong> estimates that generative AI will ultimately automate 25% of all work tasks and raise productivity by 9% and GDP growth by 6.1% cumulatively over the next decade.<\/p>\n Kash Rangan<\/strong> and Eric Sheridan<\/strong>, also analysts at Goldman Sachs, share this enthusiasm.<\/p>\n They argue that, despite high spending on AI infrastructure, current investment levels aren\u2019t irrational.<\/p>\n Sheridan notes AI spending relative to revenues mirrors past tech investment cycles, and companies linking AI investments to revenue growth are being rewarded.<\/p>\n Rangan adds that the returns from this AI investment cycle look more promising due to leading companies with low capital costs and vast distribution networks driving the investments.<\/p>\n However Toshiya Hari, a GS\u2019 semiconductor analyst, points out that chip shortages will limit AI expansion in the near term.<\/p>\n The demand for critical components like High-Bandwidth Memory technology and Chip-on-Wafer-on-Substrate packaging exceeds supply, hindering progress, he says.<\/p>\n Meanwwhile, Carly Davenport<\/strong> and Alberto Gandolfi<\/strong>, utilities analysts at Goldman Sachs, predict that the proliferation of AI will drive a surge in power demand, stressing an already aged and underprepared power grid.<\/p>\n \u00a0<\/p>\n GS senior US equity strategist Ryan Hammond<\/strong> says he sees more room for the AI theme to run and expects AI beneficiaries to broaden out beyond just Nvidia, and particularly to what looks set to be the next big winner: Utilities.<\/p>\n That said, looking at the bigger picture, GS senior multi-asset strategist Christian Mueller-Glissmann<\/strong> finds that only the most favourable AI scenario, in which AI significantly boosts profitability without raising inflation, would result in above-average returns over the S&P 500.<\/p>\n Meanwhile, Covello cautions that the AI bubble could take a long time to burst; and in the meantime, AI infrastructure providers might continue to benefit.<\/p>\n He\u2019s sceptical about AI\u2019s ability to enhance company valuations, as any efficiency gains could be offset by increased competition and unclear revenue pathways.<\/p>\n \u201cMany people attempt to compare AI today to the early days of the internet,\u201d Covello said.<\/p>\n \u201cBut even in its infancy, the internet was a low-cost technology solution that enabled e-commerce to replace costly incumbent solutions.<\/p>\n \u201cAmazon could sell books at a lower cost than Barnes & Noble because it didn\u2019t have to maintain costly brick-and-mortar locations.<\/p>\n \u201cFast forward three decades, and Web 2.0 is still providing cheaper solutions that are disrupting more expensive solutions, such as Uber displacing limousine services.<\/p>\n \u201cWhile the question of whether AI technology will ever deliver on the promise many people are excited about today is certainly debatable.<\/p>\n \u201cThe less debatable point is that AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn\u2019t designed to do,\u201d said Covello.<\/p>\n \u00a0<\/p>\n Now read: TECH-HEAVY: Musk got his money, now TSLA will too; this AI craze is no dot-com crash<\/a><\/strong><\/em><\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n The post Is AI a bubble? Goldman Sachs issues reality check for investors<\/a> appeared first on Stockhead<\/a>.<\/p>","protected":false},"excerpt":{"rendered":"Skeptical views on AI<\/h2>\n
Optimistic perspectives on AI<\/h2>\n
What this means for markets and AI-related stocks<\/h2>\n