Artificial intelligence (AI) chipmaker Nvidia on August 28 said quarterly sales reached a higher-than-expected $30 billion (€27.03 billion) in the last quarter, however, that growth was slower than the furious pace seen in previous quarters. Still, shares in the company dipped about 5% in after-hours trading following the report. Even though sales and profit, which hit $16.5 billion in the period, more than doubled from a year earlier, investors showed nervousness that Nvidia's extraordinary growth, spurred by the AI frenzy, may be showing signs of easing.

"Such a massive amount of money has gone to tech and semiconductors in the last 12 months that the trade is completely skewed," said Todd Sohn, an ETF strategist at Strategas Securities, in a note to investors.

The sums of money currently being invested in AI companies are enormous. US investment bank Goldman Sachs expects an AI investment volume of around $158 billion this year, with about half of that amount going to the United States. In a research report titled AI: too much spent, too little benefit? Goldman says "tech giants and beyond are set to spend over $1 trillion on AI capex in coming years." 

These funds would flow into significant investments in data centers, chips, other AI infrastructure, and the power grid. Whether these massive investments will ultimately generate returns beyond the current "picks and shovels" phase, however, remains unclear.

AI developing at a breakneck pace

But for major tech companies withdrawing from the AI race is not an option. During the presentation of the latest financial results of Google parent company Alphabet, CEO Sundar Pichai said "the risk of underinvesting in AI infrastructure is dramatically greater than the risk of overinvesting."

Facebook parent company Meta appears to view AI's potential in the same way as its spending on the technology also remains high, rising to over $24 billion last quarter. Meta expects AI spending of between $37 and $40 billion this year and is preparing investors for a "significant" increase in 2025," German news agency dpa reported.

Leopold Aschenbrenner, a former employee of AI pioneering company OpenAI who was fired for disclosing classified company documents, wrote in a June 2024 research paper that the boom is "driven by investments," but it is taking time to train AI, build chip factories, and develop energy infrastructure. "Profits will come later, but companies are already generating good revenues now," Aschenbrenner wrote.

Currently, about 27% of companies in Germany use AI, says Klaus Wohlrabe, head of surveys at Munich-based ifo Institute. Some 17% plan to use AI in the coming months. "The trend is likely to pick up more speed," he told DW.

Wohlrabe, however, also says the think tank's surveys "do not show the extent to which business processes are fundamentally changed by generative AI," and that "this is just beginning."

Waiting for 'killer' applications

Christian Temath from an initiative called KI NRW, which seeks to promote AI use in the German state of Northrhine-Westfalia says that practical applications that lead to greater efficiencies in companies and large-scale productivity gains have yet to emerge. "I don't think every billion currently being spent on computing capacity in the US will be recouped one-to-one," he told DW.

Rita Sallam, an analyst at US market research firm Gartner, believes that following last year's AI hype, executives are "impatient" to see returns on AI investments. "Yet organizations are struggling to prove and realize value. As the scope of initiatives widens, the financial burden of developing and deploying GenAI models is increasingly felt." Gartner predicts that at least 30% of AI projects will be abandoned after proof of concept by the end of 2025, due to "poor data quality, inadequate risk controls, escalating costs or unclear business value."

Goldman Sachs also warns that despite its high costs, thetechnology is far from being useful: "Excesses in things the world does not need or is not ready for usually end badly." Venture capital firm Sequoia and hedge fund Elliott share a similar view, suggesting that tech companies are already "in bubble territory."

Gartner's 'hype-cycle model'

To describe the development of breakthrough technologies like generative AI, Gartner's so-called hype cycle is often cited. First, a potential technological breakthrough is announced and celebrated in the press, although no viable products exist yet. Exaggerated expectations lead to hype. Then comes the trough of disillusionment, as initial products are not as successful as expected. Next, new applications emerge that succeed in the market. The development stabilizes on the plateau of productivity when mainstream applications are running.

Applied to generative AI, the release of ChatGPT in November 2022 triggered the hype. It seems clear we have not yet reached the plateau of productivity.

A collapse of the hype was feared in early August when, among other things, shares in Nvidia plummeted and then again in September, when the chipmaker shed nearly $280 billion in market value in one day. The AI race continues, however. How long it will last and whether it will be successful is unknown, as not all hyped technologies make it out of the trough of disillusionment.

AI here to stay despite the bubble fears

Recently, more voices have suggested that the AI hype might be a bubble. And bubbles have the unpleasant tendency to sometimes burst, causing significant turmoil in financial markets.

Experts from the rating agency Standard & Poor's believe that the path to monetization and maturity for AI will be "longer than previously expected."

"By far the biggest beneficiary of AI spending by companies is Microsoft," the S&P experts say.

The number of Microsoft 365 Copilot customers has increased by more than 60% compared to the previous quarter, and the number of daily active users has doubled. Goldman Sachs analyst Sung Cho believes that there could be "a pause in the near term" which is going to "dictate the shorter-term direction of markets." What he called killer applications that justify the massive investments have yet to be invented.

Brook Dane, also a Goldman Sachs analyst, says that investors will "need to see, at some point over the next year to year-and-a-half, applications that use this technology in a way that's more profound than coding and customer service chatbots." If it was just that investors would be spending "way too much."

But Dane and Cho, both portfolio managers on the Fundamental Equity team in Goldman Sachs Asset Management, are convinced that AI will be one of the biggest trends of all time, both in the medium and long term.

Daron Acemoglu, a professor at the Massachusetts Institute of Technology (MIT) is more skeptical. He estimates that "truly transformative changes won't happen quickly and few will likely occur within the next 10 years. "Only a quarter of tasks affected by AI will be cost-effectively automated, meaning AI will impact less than 5% of all tasks," he said in a Goldman Sachs Research newsletter. 

He also predicts that AI's productivity effects within the next decade  should be "no more than 0.66%," and an even lower 0.53% when adjusting for "the complexity of hard-to-learn tasks." That figure, he concluded, roughly translates into merely 0.9% higher gross domestic product (GDP) for the US over the decade.

This article was originally written in German.