AI: Investing in the Global Future

Published Date : 24/06/2025 

Artificial intelligence is reshaping global investment trends, with AI and Big Data funds seeing explosive growth. Discover how investors can engage with this transformative theme. 

Artificial intelligence marks a seismic shift that’s reshaping global investment trends, with AI and Big Data funds experiencing explosive growth and attracting significant investor interest. By the end of the first quarter this year, global assets in artificial intelligence and Big Data funds had surpassed USD 30 billion.

From voice assistants to financial forecasting to healthcare diagnostics, AI now fuels the operations and growth of many of the world’s most valuable companies. In the “Investing in Artificial Intelligence Handbook,” we delve into what’s driving the growth of this theme and how investors can engage with it.

The exponential growth of AI and Big Data funds saw a significant influx in late 2022, driven by investor enthusiasm around the public debut of ChatGPT 3.5. This event demonstrated AI’s transformative potential to hundreds of millions of users worldwide. Record inflows in early 2025 were further fueled by a surge of interest from Chinese investors, sparked by the success of domestic AI leader DeepSeek.

These breakthroughs have contributed to US-domiciled AI and Big Data fund assets growing fourteenfold in just two years—albeit from a low base—to reach a record USD 5.5 billion by May 2025. However, the US accounts for only 15% of global AI and Big Data fund assets, trailing Europe, where AI fund assets have grown fivefold over the past five years to reach USD 22.7 billion.

As AI continues to integrate into the fabric of our lives, the question “What qualifies as an AI stock?” becomes increasingly nuanced. While mega-cap tech companies like Microsoft (MSFT), Alphabet (GOOG), and Nvidia (NVDA) immediately come to mind, the AI ecosystem is broad and includes companies that provide supporting infrastructure or apply AI in transformative ways.

For instance, firms like Vertiv (VRT), which supply the power and cooling infrastructure essential for AI data centers, play a crucial role. Even large retailers like Walmart (WMT) and Tesco (TSCO), which leverage vast datasets to optimize operations using AI tools, are part of the broader AI theme. This diversity complicates the task of building thematic portfolios but also presents opportunities for differentiated exposure.

To help identify meaningful exposure to AI, Morningstar employs a consensus holdings-based approach. By analyzing all non-China-domiciled funds tagged as AI and Big Data funds, we identify the most commonly held stocks across these portfolios. This method provides a transparent, data-driven view of the core holdings shaping the AI investment narrative.

Our analysis reveals a clear trend: The Magnificent Seven dominate AI and Big Data fund holdings. Nvidia, in particular, appears in nearly 90% of AI and Big Data fund portfolios, thanks to its market leadership in AI chips. Other names in the Magnificent Seven, including Microsoft, Amazon.com, Google, Meta, Apple, and Tesla, also contribute uniquely to the commercialization of AI—from cloud computing to data monetization and advanced robotics.

These companies not only provide the hardware and software backbone for AI development but also benefit from massive data ecosystems and global scale. Their central role in AI has made them cornerstones of performance for AI-focused strategies.

While the Magnificent Seven companies are logical inclusions in any AI-tracking portfolio, their dominance presents a dilemma for fund managers. Including them heavily leads to significant overlap with mainstream equity indexes like the S&P 500 and Nasdaq-100, diluting the uniqueness of AI-themed funds and challenging the justification for higher fees often associated with active management.

Conversely, excluding these giants altogether introduces performance risk, as it could mean missing out on some of AI’s biggest beneficiaries. Most fund strategies seek a middle path: maintaining a core allocation to the Magnificent Seven while using the remaining portfolio to highlight more specialized or lesser-known AI players.

Despite Europe being the largest market for AI and Big Data fund assets, the United States continues to dominate in terms of stock representation. Nearly all of the most frequently held stocks in global AI funds are US-listed and -domiciled. Though there are exceptions, like Dutch semiconductor equipment giant ASML (ASML), they are few and far between.

This geographic skew reflects the US’s continued leadership in tech innovation and its deep capital markets. It also highlights the structural challenge for investors seeking geographic diversification within the AI theme. At present, no comprehensive fund exists that enables full diversification away from US-centric AI exposure.

The Morningstar Global Artificial Intelligence & Big Data Consensus Portfolio—built from the most commonly held stocks in AI-focused funds—has outperformed the Morningstar Global Target Market Exposure Index by 35% since the release of ChatGPT 3.5 in November 2022. However, this impressive outperformance has come with higher volatility and deeper drawdowns, illustrating the high-risk, high-reward nature of investing in emerging technologies.

Investors should be mindful that while the AI theme offers tremendous growth potential, it also carries elevated risks. Concentration in a few dominant names, exposure to rapidly evolving technologies, and valuation concerns are all factors to consider when allocating to this space. 

Frequently Asked Questions (FAQS): 

Q: What are the most commonly held stocks in AI and Big Data funds?

A: The most commonly held stocks in AI and Big Data funds are often referred to as the Magnificent Seven: Nvidia, Microsoft, Amazon.com, Google, Meta, Apple, and Tesla.

Q: How does Morningstar evaluate AI stocks?

A: Morningstar employs a consensus holdings-based approach by analyzing non-China-domiciled funds tagged as AI and Big Data funds to identify the most commonly held stocks across these portfolios.

Q: What are the risks associated with investing in AI?

A: Investing in AI carries elevated risks, including concentration in a few dominant names, exposure to rapidly evolving technologies, and valuation concerns.

Q: Why is the US dominant in AI stock representation?

A: The US dominates in AI stock representation due to its leadership in tech innovation and deep capital markets, making it a hub for AI-related companies.

Q: What is the performance of AI and Big Data funds compared to mainstream indexes?

A: The Morningstar Global Artificial Intelligence & Big Data Consensus Portfolio has outperformed the Morningstar Global Target Market Exposure Index by 35% since the release of ChatGPT 3.5 in November 2022, though with higher volatility and deeper drawdowns. 

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