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It’s been a tough week for the Magnificent Seven, the group of technology stocks that have played a dominant role in the U.S. stock market, driven by investor enthusiasm over advances in artificial intelligence.
Last year, Microsoft, Amazon, Apple, chipmaker Nvidia, Google parent Alphabet, Facebook owner Meta and Elon Musk’s Tesla accounted for half of the S&P 500’s gains. But doubts about the return on investment in AI, coupled with a mixed set of quarterly results, investors shifting their attention to other sectors and weak U.S. economic data have weighed on the group over the past month.
This came to a head this week when all seven companies entered correction territory, meaning their combined share prices fell more than 10% from their peak on July 10.
Here we answer some questions about the seven and the rise of AI.
First, there is concern about whether the massive investment in artificial intelligence by Microsoft, Google and others will pay off. This has been boiling over in recent months. Analysts at Goldman Sachs published a note In June, under the headline “Gen AI: Too much expense, too little benefit?”, the Wall Street bank asked whether a $1 trillion investment in AI over the next few years “will ever pay off,” while an analysis by Sequoia Capital, an early investor in ChatGPT developer OpenAI, estimated that tech companies will need to earn $600 billion to recoup their AI investments.
Zino says the Magnificent Seven have been affected by these concerns.
“There is clearly some concern about the performance of the AI investments they are making,” he says, adding that big tech companies have at least been “doing a good job” of explaining their AI strategies in their most recent results.
Other factors at play include investor expectations that the U.S. central bank, the Federal Reserve, could cut interest rates as early as next month. The prospect of falling borrowing costs has boosted investor support for companies that could benefit, such as smaller companies, banks and real estate firms. This is an example of “sector rotation,” where investors move their money into different areas of the stock market.
Concerns about the Big Seven have had an impact on the S&P 500, given that a handful of technology stocks account for much of the index’s value.
“Given the increasing concentration of that group on US stocks, that will have a broader impact,” said Henry Allen, macro strategist at Deutsche Bank. Fears about the weakness of the US economy also weighed on global stock markets on Friday.
What’s happening in tech stocks this week?
By Friday morning, all seven had fallen 11.8% from their peak last month, though they have been moving in and out of correction territory (a drop of 10% or more from recent highs) in recent weeks as doubts have spread.
This week’s quarterly results have been mixed. Microsoft’s cloud computing division, which plays a key role in helping companies train and operate AI models, reported weaker-than-expected growth. Amazon, another big cloud computing player, also disappointed, as growth in its cloud business was offset by higher spending on AI-related infrastructure such as data centers and chips.
Meta shares rose on Thursday, however, after strong revenue growth at the advertising-reliant Facebook and Instagram owner offset its commitment to investing heavily in artificial intelligence. Apple’s sales also beat expectations on Thursday.
“Arguably, expectations have become too high for the so-called Magnificent Seven,” Dan Coatsworth, an analyst at investment platform AJ Bell, said in a note this week. “Their success has made them untouchable in the eyes of investors and when they fall short of greatness, the knives come out.”
There has also been a general feeling that valuations of tech companies may have become too high. Angelo Zino, technology analyst at CFRA Research, says: “Valuations were reaching 20-year highs and we were in for a pullback, as well as a pause to digest some of the gains we have seen over the past 18 months.”
On Friday, the Financial Times reported that hedge fund Elliott Management told investors in a note that AI was “overhyped” and that Nvidia, which has been a big beneficiary of the boom, is in a “bubble.”
Should we expect further advances in artificial intelligence in the next 12 months?
More breakthroughs are virtually guaranteed to come, which may reassure investors. The biggest companies in the sector have clear plans for the future, already running training trials for the next generation of cutting-edge models, and new records are being set virtually every month. Last week, Alphabet-owned Google DeepMind announced record-breaking performance by its systems at the International Mathematical Olympiad, a high school-level math competition, which has observers wondering whether the company will be able to tackle long-unsolved problems in the near future.
The question for research labs is whether the advances will be revenue-generating enough to pay for the ever-rising cost of achieving them. The bill for a cutting-edge AI training program has grown tenfold every year since the AI boom took off in earnest, leaving even well-capitalized companies like OpenAI, the Microsoft-backed startup behind ChatGPT, with questions about how they will fund such an expense over the long term.
Is generative AI already bearing fruit for the companies that use it?
The most successful uses of generative AI (the term used for AI tools that can create plausible text, audio, or images from simple prompts) in many companies have emerged from the bottom up: people who have figured out how to effectively use tools like Microsoft’s Copilot or Anthropic’s Claude to work more efficiently or remove time-consuming tasks from their day. But at the corporate level, few clear success stories remain. While Nvidia got rich selling shovels in a gold rush, the best AI user narrative remains Klarna, the buy-now-pay-later company that announced in February that its OpenAI-powered assistant Handled two-thirds of its customer service requests in its first month.
Dario Maisto, a senior analyst at Forrester, says a lack of economically beneficial uses for generative AI is hampering investment.
“There remains the problem of translating this technology into a real, tangible economic benefit,” he said.
