Why Now Is the Perfect Time to Load up on the AI Stocks in the Mag 7
One could argue there hasn’t been a better time in the last decade to buy the so-called Magnificent Seven stocks — the mega-cap companies that sit at the top of the market today.
That may sound odd given all the AI bubble talk over the last year, after the Mag 7 drove parabolic gains in the S&P 500 following ChatGPT’s launch in November 2022.
But with the basket of stocks — which includes Nvidia (NVDA), Amazon (AMZN), Microsoft (MSFT), Meta (META), Alphabet (GOOG), Apple (AAPL), and Tesla (TSLA) — down as much as 19% since October, their valuations relative to the S&P 500 have rarely been this cheap, said Marta Norton, the chief investment strategist at Empower Investments.
In an interview with Business Insider last week, Norton specifically noted that the Bloomberg Magnificent Seven index is in its cheapest decile since 2015.
“You’re essentially paying the same type of valuation for these names as you would be just to get a broad collection of the US stock market,” Norton said.
Among the Mag 7 stocks, Norton said she favors the five most closely tied to the AI trade, which she sees as a secular tailwind in the years ahead. Those include Nvidia, Amazon, Microsoft, Alphabet, and Meta.
Hyperscaler stocks, in particular, have an advantage as they play both sides of the AI coin, she said. Nvidia is only one of the five stocks listed above that is not considered a hyperscaler, as it acts as a supplier to the tech giants building out the technology.
“They’re actively not only building out the infrastructure, but they’re looking for ways to monetize it,” Norton said of hyperscaler stocks. “They’re kind of coming at it from two different directions.”
Norton said that initial valuations are particularly important for the big AI names because of their significant spending on the AI buildout. The more they spend on AI infrastructure, the greater the risk that future cash flows won’t justify the costs. So, cheaper valuations mean a lower amount of risk taken on by investors.
The four hyperscaler firms are expected to spend almost $600 billion combined in 2026 alone.
She emphasized that the stocks look attractive on a long-term basis and said they could see more downside in the near term. A clear path to monetizing their AI products would start to spark the outperformance Norton expects, she said.
“If I were to fall asleep for 10 years, these are the names I would want to have in my portfolio,” Norton said.
