Vanguard warns investors about a subtle but significant risk: many seemingly diversified value funds increasingly hold substantial exposure to artificial intelligence. This means individuals attempting to shield their portfolios from high-growth tech stocks may inadvertently maintain considerable investments in the very companies driving the AI boom. Such a scenario challenges traditional diversification strategies.

For years, investing in broad market index funds, growth funds, or target-date funds provided significant exposure to the AI data center expansion. This strategy proved highly beneficial as the entire supply chain, from semiconductor manufacturers to server farm builders, experienced widespread growth. Investors often gained without needing to distinguish between individual winners and losers.

However, the market dynamics are shifting. Recent declines in chip stocks, including a 12% drop in July and a 10.2% decrease in semiconductor and data center funds between October 1 and October 16, signal increased volatility. A common response is to pivot to value funds, traditionally seen as safer havens filled with established “old economy” companies. Yet, this shift may not reduce AI exposure as much as investors anticipate.

Andrew Shuman, director of research for Vanguard Oversight & Manager Search, cautioned against this trend in commentary. He stated that “naively chasing the recent winners of the AI buildout creates a risk of buying high.” This warning, part of Vanguard’s October 21 commentary titled “Navigating the AI hype cycle: A case for active,” underscores a growing concern about market concentration.

AI Investment Risks and Historical Parallels

The influx of capital into artificial intelligence investments has been substantial. Data from Morningstar, cited by Shuman, indicates that investors poured nearly $82 billion into technology stocks over the 12 months ending August 2026. This figure was more than triple the net inflows into industrials, the next most popular sector. Such significant inflows often create a self-fulfilling cycle, pushing asset prices higher and attracting even more buyers.

This aggressive investment contributes to heightened volatility, particularly within chip stocks. Shuman noted that “semiconductor and semiconductor equipment stocks tend to have higher betas and volatility, often experiencing significant drawdowns, given their cyclicality.” This inherent fluctuation poses a challenge for long-term stability.

Vanguard draws parallels to historical technology cycles, suggesting that a shift in market leadership is likely. Shuman compared the current AI buildout to the expansion of railroads in the mid-19th century and broadband infrastructure in the 1990s. In those previous cycles, the companies that established the foundational infrastructure rarely captured the largest long-term profits. Instead, the ultimate winners were often businesses that built services and applications on top of these new infrastructures, such as e-commerce and social media companies following the internet’s widespread adoption.

This historical pattern implies that while the initial beneficiaries of AI infrastructure development see substantial gains, the next wave of winners may emerge from companies leveraging AI rather than those solely building its foundational components. Understanding this potential market evolution is crucial for investors planning their future allocations. The current surge in AI-related stock valuations may not sustain itself over the long term if history is any guide.

Undisclosed AI Exposure in Value Funds

The unexpected truth about many value funds is their increasing exposure to leading AI companies. Investors often turn to value stocks expecting to invest in established, lower-growth companies with strong balance sheets, thereby diversifying away from rapidly expanding, high-valuation tech firms. This strategy aims to reduce overall portfolio volatility and mitigate risks associated with speculative growth. However, the composition of major value indexes has changed significantly.

Vanguard highlights that Amazon and Microsoft, both heavily investing billions in AI data centers, are now among the three largest holdings in the Russell 1000 Value Index. This integration means that a fund designed to track this index will automatically include substantial positions in these tech giants. For instance, the iShares Russell 1000 Value ETF (IWD) held Amazon at 6.12%, Apple at 6.11%, and Microsoft at 5.26% as of October 8.

This means approximately 17.5% of a fund often considered a hedge against tech growth is actually concentrated in three of the world’s largest technology companies. This high concentration can undermine the diversification goals of investors who hold value funds alongside broader market or growth-oriented funds. It becomes critical for investors to examine the top holdings of their value funds rather than assuming they are fully diversified away from big tech.

Furthermore, Vanguard points out that any cost savings achieved by old-economy companies through AI integration may not necessarily translate into higher stock prices or greater profits for shareholders. In highly competitive industries, all participants might achieve similar AI-driven efficiencies. This widespread adoption could lead to competition driving down prices, passing those savings to customers rather than boosting profit margins for the companies themselves. Consequently, the anticipated financial benefits from AI adoption may not materialize for equity holders as expected.

The Argument for Active Management

In an interesting turn for an organization known for its low-cost index funds, Vanguard makes a case for active management in the current AI-driven market. Shuman suggests that “talented active managers, when accessed at reasonable costs, could prove their mettle in navigating this environment across both equities and fixed income.” This stance is rooted in the belief that market conditions are becoming more nuanced, presenting opportunities for skilled stock pickers.

Vanguard observes that while overall market volatility has remained historically normal, the “dispersion within individual stocks has widened significantly.” This divergence between the performance of individual stocks, even as the broader index appears stable, creates an opportune environment for active selection. In such a setting, managers with expertise in identifying specific winners and avoiding potential losers can theoretically outperform passive index strategies.

According to Vanguard, active managers should scrutinize “hyperscalers”–the cloud computing giants investing heavily in AI data centers–for several key attributes. They should seek companies demonstrating the highest potential return on investment from their AI products, both for consumers (like search engines and personal assistants) and businesses (such as cloud computing services). Additionally, these companies must deliver these products efficiently and cost-effectively, maintaining strong balance sheets despite significant capital expenditures.

Despite current valuations placing hyperscalers at roughly 20 to 25 times expected earnings, Vanguard still cautions about potential overcapacity. Trillions of dollars flowing into AI data centers “could result in overcapacity that leads to broadly disappointing profits and stock returns,” Shuman warned. This highlights a significant risk even for the most dominant players in the AI infrastructure space.

Opportunities for Smaller Companies

Vanguard also anticipates a more level playing field for artificial intelligence, particularly as the cost of AI tokens decreases. This reduction in cost diminishes the advantage previously held by companies with massive budgets, allowing smaller, more agile firms to compete effectively. Shuman noted that “as costs decrease and the ability to experiment increases, value could accrue to smaller companies with more nimble cultures and management teams willing to disrupt their existing business models.”

This trend suggests that the next generation of AI leaders may not solely come from the established tech giants. Vanguard draws a comparison to the early days of e-commerce and mobile internet companies, which started small but eventually grew into multi-trillion-dollar market capitalizations. New companies, built from the ground up on AI principles, may currently be private or hold only negligible weights in cap-weighted indexes. Identifying these emerging leaders before they become mainstream will be crucial for capturing significant returns.

However, the historical performance of active funds presents a challenging backdrop. According to S&P Dow Jones Indices’ SPIVA report, approximately 67% of active large-cap U.S. stock funds underperformed the S&P 500 in the first half of 2026. Looking back 20 years, an overwhelming 93% of active funds failed to match the index’s returns. This consistent underperformance underscores why Vanguard’s emphasis on “reasonable costs” for active management is so important, as high fees often erode any potential gains from stock selection.

Ultimately, the practical message for investors is not necessarily to abandon index funds, but to be acutely aware of their underlying holdings. Many portfolios may contain far more AI exposure than their fund labels suggest. Vanguard believes the next frontier lies in identifying “the Amazons and Googles of the 2030s,” suggesting a future where active managers who can spot these nascent disruptors will be well-positioned to deliver strong shareholder returns.