Bridgewater and Tiger Global ramp up Nvidia, Microsoft, Alphabet stakes in AI push

Hedge funds made decisive moves in the second quarter of 2025 to increase exposure to the artificial intelligence (AI) ecosystem, signalling confidence in the sector’s long-term growth trajectory despite concerns about valuations. According to public filings compiled by Reuters, some of the world’s largest funds—including Bridgewater Associates, Tiger Global Management and Discovery Capital Management—significantly boosted their stakes in major technology companies at the forefront of the AI infrastructure race.

Bridgewater Associates doubled its holdings in Nvidia Corporation (NASDAQ: NVDA) to 7.23 million shares, a 154 percent increase from the previous quarter. The fund also raised its stakes in Alphabet Inc. (NASDAQ: GOOGL) and Microsoft Corporation (NASDAQ: MSFT) by 84 percent and 112 percent, respectively. Tiger Global Management added more Amazon.com Inc. (NASDAQ: AMZN) and Microsoft shares to its portfolio, while Discovery Capital Management increased positions in UnitedHealth Group Incorporated (NYSE: UNH) and América Móvil, S.A.B. de C.V. (NYSE: AMX), blending AI exposure with defensive sector holdings.

These moves come as the S&P 500 index has gained more than 18 percent year-to-date, led by AI-related equities, with Nvidia’s stock price more than doubling over the same period.

Why are hedge funds ramping up exposure to AI-focused Big Tech despite valuation concerns?

Institutional investors appear to be betting that the ongoing AI arms race—fuelled by surging demand for high-performance computing, cloud services and advanced semiconductor technology—will sustain revenue and margin growth for market leaders. Nvidia’s dominance in AI-optimised graphics processing units (GPUs), Microsoft’s aggressive rollout of AI-enabled cloud products, and Alphabet’s expanding AI model portfolio are seen as structural advantages that could extend into the next decade.

Analysts suggest that the buying patterns reflect a broader shift in hedge fund strategy, from opportunistic trading to concentrated, conviction-driven positions in companies building the infrastructure and software layers of AI. Funds are not just chasing recent gains but are positioning ahead of anticipated demand from enterprise adoption, AI-driven consumer products, and regulatory-driven digital transformation.

Despite price-to-earnings multiples that some view as stretched—Nvidia’s forward P/E remains well above historical norms—managers appear comfortable with current valuations given the earnings growth trajectory. This conviction, however, comes with inherent concentration risk: when large funds cluster into the same high-beta names, any sentiment reversal can amplify volatility.

How does this investment wave compare to previous hedge fund positioning during tech supercycles?

Historically, hedge funds have increased exposure to technology during inflection points, such as the early-2000s internet boom, the post-2009 cloud adoption cycle, and the 2020 pandemic-era digital acceleration. What distinguishes the current cycle is the speed at which AI adoption is influencing both consumer and enterprise markets.

In the past, hedge fund positioning often diversified across multiple subsectors. Now, the focus is heavily tilted toward a smaller group of mega-capitalisation names, raising parallels to the “Nifty Fifty” concentration patterns of the 1970s. This approach can yield outsized returns during momentum phases but also risks sharp drawdowns if growth assumptions falter.

The inclusion of defensive holdings—such as UnitedHealth in healthcare and América Móvil in telecommunications—indicates that some managers are hedging against macroeconomic or sector-specific shocks, creating a barbell portfolio structure.

What institutional sentiment signals can be drawn from these Q2 2025 disclosures?

The Q2 disclosures suggest a broadly bullish institutional view on the AI investment theme, with hedge funds treating AI as both a secular growth story and a tactical momentum play. The simultaneous allocation to healthcare and telecom stocks reflects a measured approach to risk management.

Market observers note that this behaviour aligns with broader fund flow data, which has shown consistent inflows into technology-focused exchange-traded funds (ETFs) and thematic AI investment vehicles over the past six months. The sustained appetite suggests that large allocators view AI not as a transient hype cycle but as a multi-year capital deployment opportunity.

From a market structure perspective, these concentrated positions may enhance liquidity in the short term but also set the stage for higher correlation between top AI names in periods of market stress.

What are the potential risks for investors following hedge funds into these AI leaders?

While hedge fund moves can provide directional cues, investors face several risks when following such trades. Valuation risk remains the most discussed, particularly for Nvidia, which trades at earnings multiples far above its semiconductor peers. Regulatory risk is also rising, as U.S., European and Asian authorities intensify scrutiny of dominant technology platforms on antitrust, data privacy and AI governance grounds.

Geopolitical factors could also affect supply chains for advanced chips, especially if U.S.–China technology tensions escalate. In addition, a slowdown in enterprise AI spending—due to budget constraints or slower-than-expected returns on AI projects—could temper revenue growth for cloud providers.

Finally, concentration risk is non-trivial: with multiple hedge funds holding large stakes in the same companies, any coordinated or sentiment-driven sell-off could create sharp price declines.

How might these positions evolve in the next 12 months based on sector fundamentals?

If AI adoption maintains its current growth trajectory, institutional investors may continue to build or at least maintain overweight positions in Big Tech. Microsoft’s integration of AI assistants across Office, Azure and Dynamics 365 could sustain enterprise subscription growth, while Alphabet’s AI-driven advertising and cloud offerings may diversify revenue streams beyond search. Nvidia’s upcoming product cycles, including next-generation AI accelerators, could reinforce its market dominance.

However, portfolio rebalancing may occur if valuations overshoot earnings revisions or if regulatory developments introduce uncertainty. Funds may also rotate into AI-adjacent plays in sectors such as industrial automation, cybersecurity and telecom infrastructure to capture second-order growth effects while diversifying risk.

For retail investors, the broader takeaway is that chasing hedge fund trades in isolation can be risky—especially when those portfolios are heavily concentrated in a handful of high-beta technology stocks. While the artificial intelligence sector has delivered exceptional returns over the past two years, its leaders such as Nvidia, Microsoft and Alphabet are already trading at premium valuations that leave less margin for error. Instead of attempting to replicate concentrated hedge fund positions, individual investors may benefit from building a more balanced allocation that combines direct AI infrastructure plays—such as semiconductor manufacturers, cloud computing providers and AI-driven software platforms—with diversified exposure to industries poised to benefit indirectly from AI adoption.

This can include sectors like cybersecurity, where AI is reshaping threat detection; industrial automation, where AI enables predictive maintenance and robotics; and telecommunications, where AI is optimising network performance and 5G rollouts. By blending core AI holdings with these adjacent growth themes, retail investors can participate in the upside of the AI boom while reducing the portfolio volatility that comes from overexposure to a small set of mega-cap stocks. Over time, this diversified strategy can help capture the structural tailwinds of AI while protecting against sector-specific setbacks, regulatory headwinds or cyclical downturns in technology markets.