This is not entirely surprising. In areas of great innovation, there’s always potential for a start-up or new entrant to disrupt the status quo, particularly in today’s environment, where U.S. tech stocks have already been priced for near perfection. Despite impressive earnings, stretched valuations provide little margin for error. This has been reflected in the historically stretched valuation of U.S. stocks, particularly large-cap growth.
Much of this lofty valuation has rested on a key assumption that the leading tech firms will be able to continue to grow earnings based on their “competitive moat.” Whether or not the new open-source AI proves to disrupt the existing AI ecosystem, it is a timely reminder of an enduring investment lesson: Markets can underestimate the chance that dominant incumbents’ business models get disrupted by upstarts or economic changes.
There’s certainly plenty of precedent for this, especially in times of transformational technological change. We cover several examples in an upcoming book on megatrends. One that immediately comes to mind: Between 1900 and 1908, nearly 500 automobile companies came into existence, but more than half also disappeared. Today, only two of them are still around. That’s typical of the creative destruction you see as new entrants wipe away the value of older companies.
According to Stanford University’s annual AI Report, there have been 5,500 AI-related companies launched in the past 10 years in the U.S. alone, both public and private—greater than the number of publicly listed U.S. companies1. They can’t all be winners. And, if history is any guide, a few of them will surely be disruptors to today’s AI ecosystem as we know it.
Investors need to be aware of both the risks and opportunities, though the latter may not always be self-evident.
Sticking with equities for now, if AI is truly transformative, the biggest winners will likely be the beneficiaries of this technology, not necessarily the builders of the technology and its infrastructure, whose prices already reflect that optimism. Our secular outlook is that value stocks might benefit the most from AI over time. And I stress over time.
That said, I’m not saying abandon tech stocks and go all in on value. For most investors, it’s better to diversify by owning the full haystack, instead of searching for those few needles. But diversification goes beyond equities.
I know plenty of investors questioned the value of bonds and balanced portfolios after 2022, when both stocks and bonds plunged. But 2022 was more of a historical anomaly. In the most recent period, while tech stocks fell, bond prices rose. Bonds fulfilled their traditional role as ballast for stocks in a balanced portfolio. As we’ve said in our economic and market outlook for 2025, fixed income looks especially attractive currently, providing generally higher yields than inflation, a return to sound money.
Last but not least, whether in bonds or equities, for those comfortable with active-management risk and perhaps uncomfortable with current valuations in some pockets of the market, using active managers might give bargain-hunting investors an edge. But the bottom line is balance and diversification.
1 See https://aiindex.stanford.edu/wp-content/uploads/2024/05/HAI_AI-Index-Report-2024.pdf
Notes:
All investing is subject to risk, including the possible loss of the money you invest. Diversification does not ensure a profit or protect against a loss. There is no guarantee that any particular asset allocation or mix of funds will meet your investment objectives or provide you with a given level of income.
Investments in bonds are subject to interest rate, credit, and inflation risk.
Investments in stocks or bonds issued by non-U.S. companies are subject to risks including country/regional risk and currency risk.
Funds that concentrate on a relatively narrow market sector face the risk of higher share-price volatility.
Publication date: January 2025
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