It has been tough week for the magnificent seven, the group of technology stocks that has played a dominant role in the US stock market, buoyed by investor excitement about breakthroughs in artificial intelligence.
Last year Microsoft, Amazon, Apple, the chipmaker Nvidia, Google’s parent, Alphabet, Facebook’s owner, Meta, and Elon Musk’s Tesla accounted for half the gains in the S&P 500 share index. But doubts about the return on AI investment, along with a mixed set of quarterly results, investors shifting their focus to other sectors and weak US economic data have hit the group over the past month.
That came to a head this week when the seven companies moved into correction territory, meaning their combined share prices have fallen more than 10% since their peak on 10 July.
Here we answer some questions about the seven and the AI boom.
Why have AI-linked stocks suffered?
Primarily, there is concern about whether the vast investment in AI byMicrosoft, Google and others will pay off. This has been bubbling away in recent months. Analysts at Goldman Sachs published a note in June with the title “Gen AI: too much spend, too little benefit?” The Wall Street bank asked if a $1tn 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 $600bn to pay back their AI investments.
Zino says the Magnificent Seven has been hit by these concerns.
“There is clearly some concern about the return on the AI investments they are making,” he says. He adds that the 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 expectation that the US central bank, the Federal Reserve, may lower interest rates as soon as next month. The prospect of a drop in the cost of borrowing has buoyed investor support for companies that might benefit, such as smaller businesses, 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 tech stocks make up so much of the index’s value.
“Given the rising concentration of that group among US equities, that’s going to have an impact more broadly,” says Henry Allen, a macro strategist at Deutsche Bank. Fears about weakness in the US economy also hit global stock markets on Friday.
What has happened to tech stocks this week?
By Friday morning, the seven had fallen 11.8% from their peak last month, although they have been in and out of correction territory – a fall of 10% or more from recent highs – in recent weeks as doubts have spread.
Quarterly results this week have been a mixed bag. Microsoft’s cloud computing division, which plays a key role in helping companies to train and operate AI models, reported lower-than-expected growth. Amazon, another big cloud computing player, also disappointed as growth at its cloud business was offset by higher spending on AI-related infrastructure such as datacentres and chips.
However, Meta’s shares rose on Thursday after strong revenue growth at the advertising-dependent Facebook and Instagram owner offset its commitment to spend heavily on AI. Apple sales also beat expectations on Thursday.
“Expectations have arguably become too high for the so-called magnificent seven group of companies,” said Dan Coatsworth, an analyst at the investment platform AJ Bell, in a note this week. “Their success has made them untouchable in the eyes of investors and when they fall short of greatness, out come the knives.”
A general sense that tech valuations may have become too high has also played a role. Angelo Zino, a technology analyst at CFRA Research, says: “Valuations were getting to 20-year highs and we were due 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 Nvidia, which has been a huge beneficiary of the boom, is in a “bubble”.
Should we expect more AI breakthroughs over the next 12 months?
More breakthroughs are practically guaranteed, which may reassure investors. The largest companies in the field have clear roadmaps ahead, with training runs already in progress for the next generation of frontier models and new records being set practically every month. Just last week, the Alphabet-owned Google DeepMind announced a record performance by its systems on the Internationals Maths Olympiad, a high-school level maths competition, that has observers wondering whether the company will be able to tackle long-unsolved problems in the near future.
The question for the researcher labs is whether the breakthroughs will be sufficiently revenue-generating to pay for the rapidly growing cost of their achievement. The bill for a frontier AI training run has increased tenfold every year since the AI boom took off in earnest, leaving even well-capitalised companies such as OpenAI, the Microsoft-backed startup behind ChatGPT, with question marks over how they finance such expenditure in the long run.
Is generative AI already reaping rewards for companies using it?
The most successful uses of generative AI – the term for AI tools that can create plausible text, audio or image from simple prompts – in many companies have come from the bottom up: people who have worked out how to effectively use tools such as Microsoft’s Copilot or Anthropic’s Claude to work more efficiently, or cut out time-consuming tasks from their day altogether. But at a corporate level, there remain few stark success stories. Where Nvidia has got rich selling shovels in a gold rush, the best narrative from an AI user remains Klarna, the buy now, pay later company, which 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 the investment case.
“There is still an issue of translating this technology into real, tangible economic benefit,” he said.