There is no doubt that artificial intelligence (AI) is the driving force in global equity markets right now. Nowhere is this more apparent than in the United States, where the AI boom has propelled a handful of megacap tech stocks to record highs.
Today, the S&P 500 is more concentrated than at any point since the late-1990s tech bubble. The 10 largest stocks—led by household names like Microsoft, Apple, NVIDIA, Amazon, Alphabet, and Meta—now make up almost 40% of the index’s total market capitalization.
For perspective, that figure was about 25% during the dotcom era and just 15% in 1980. NVIDIA, the poster child of the AI revolution, recently crossed the USD 5 trillion market cap mark. AI-related firms are making headlines, while the rest of the market—especially non-tech and non-US sectors—has lagged.
What’s especially notable is that, despite big price swings in individual tech names—particularly in semiconductors—overall volatility for the S&P 500 remains muted. That’s because correlations between stocks are at historical lows, a pattern reminiscent of the late 1990s, when the index looked calm on the surface but masked plenty of turbulence underneath.
It’s only natural for investors to wonder if we’re seeing the early signs of a bubble. History offers some important lessons. In the 1970s, the “Nifty Fifty” era saw investors crowd into a handful of blue-chip growth stocks, with the top five—Coca-Cola, Johnson & Johnson, McDonald’s, IBM, and Procter & Gamble—spanning a range of sectors.
The dotcom boom of 2000 was even more extreme, with tech and internet stocks reaching dizzying valuations before the bubble burst. At that time, the largest companies by market cap included Microsoft, Cisco Systems, General Electric, Intel, and ExxonMobil—a more diverse group than the current AI-driven leaders.
Similarly, in late-1980s Japan, market concentration in a few sectors, particularly banks, led to a painful correction and years of stagnation. In each case, extreme concentration and high valuations eventually led to sharp corrections, reminding investors that no trend lasts forever.
Looking at current numbers, US market concentration is unprecedented. In emerging markets, the AI theme is also a key driver of returns. Taiwan and South Korea’s tech leaders account for most of emerging market gains this year. The top five stocks account for over 30% of the MSCI Emerging Market Index.
Japanese and European markets tell a different story owing to lower exposure to the AI infrastructure buildout. Yet, we downgraded European IT to Neutral because the sector is up around 40% since the start of the year and price-to-earnings valuations have reached highs not seen since the dotcom bubble in the early 2000s.
In fact, looking back at previous periods of market concentration, there seems to be some pattern. In the 1970s, the focus on blue-chip growth stocks ended with a long period of stagnation. In 2000, the internet and software boom ended in a dramatic correction. Today, with some 40% of the S&P 500 concentrated in just 10 stocks, the outcome remains uncertain and not without risks.
For investors, the lessons from history are clear. If growth expectations aren’t met, the current sector concentration can be challenged as in previous cycles. Investors should therefore keep an eye on declining capital efficiency and excessive investment, but the extension of the AI capex cycle continues to underscore the sustained demand for AI compute. For example, this week, Taiwan Semiconductor Manufacturing Co reported a 30% rise in sales for May.
We therefore remain constructive on global equities over the medium term. However, with index performance still heavily driven by a narrow group of large technology names, we believe periods of strength in tech should be used to rebalance portfolios and reduce excessive concentration rather than add further to it. In practice, that means broadening exposure beyond the market leaders and complementing core holdings with markets and sectors where we continue to see attractive opportunities, including Germany, Switzerland, and European health care and consumer discretionary.
This broadening should also apply within the AI theme itself. We do not see this as a call to move away from AI, but rather to extend exposure beyond the best-known megacap winners. While those companies remain central to earnings delivery, we believe the impact of AI is increasingly spreading into other parts of the market, including infrastructure, power, and industrial supply chains. In our view, that supports widening exposure across the AI value chain into areas such as industrials, automation, and space, where the next phase of the theme may be expressed more broadly.
For investors with concentrated positions, rallies in megacap technology can also provide an opportunity to lock in gains and rebalance part of that exposure into structured investments, including capital preservation strategies. This can help reduce concentration risk, improve downside protection, and retain some participation if markets continue to move higher.
