Investing in AI: Hidden Gems, False Friends, and Top AI Funds

Early 2026 volatility has left artificial intelligence valuations more attractive, suggesting a potential entry point. But not all so-called AI stocks or funds are created equal. Market chatter has elevated some with limited direct AI exposure and concealed other hidden gems that might offer more tempting opportunities.

In our latest research, we introduce the Core AI Exposure Score, an analyst-calculated metric that enables direct, like‑for‑like comparisons across AI stocks and funds. It leverages the strengths of both Morningstar’s equity research and manager research approaches to create a single score that can be used to reveal the opportunities with the most exposure to AI-driven revenue.

For a complete look at the AI theme and the score’s methodology, download the Opportunities in Artificial Intelligence report.

AI stocks have comfortably outperformed global equities in recent years. The structural drivers behind the AI boom remain strong, as gross data center spending continues to grow at a rapid pace—suggesting that the risks of an AI bubble are limited. 

Here’s the bull case for investing in AI.

• Economy-wide productivity boost. AI enables a step change in productivity, automating cognitive tasks across sectors—not just tech—and expanding the addressable market for enablers and platforms.
• Improving scaling economics. Model performance continues to improve as computational power, data efficiency, and architectures advance, while inference costs fall—supporting sustained investment and broadening adoption.
• Early-stage infrastructure cycle. Data centres, semiconductors, networking, and power remain in the early innings of a multi-year capex cycle, driving durable demand for high-barrier “picks-and-shovels” players.
• Strong strategic alignment. Nations now treat AI infrastructure as critical, with coordinated public and private investment reducing the risk of a cyclical slowdown.

Here’s the bear case for investing in AI.

• Energy and input costs. AI is energy intensive. Geopolitical shocks, such as the Iran war, risk structurally higher or volatile power costs, pressuring margins and deployment.
• Capital intensity and scale risk. The thesis depends on scaling laws justifying heavy capex. If returns to scale weaken, overcapacity and lower ROICs follow.
• Monetisation and competition. Adoption is strong, but monetisation is uneven. Open-source and rising competition may increase usage while compressing pricing power.
• Regulatory risk. Current frameworks focus on data/consent, not usage. Tighter rules on training data, liability, or deployment could raise costs and cap total addressable market.

Structural barriers mean that parts of the global AI growth story remain out of easy reach for many investors. 

Beyond the US, China represents the other major centre of AI development, but access constraints and regulatory complexity mean many managers avoid Chinese equities altogether.

And several of the most prominent AI pure-play companies—including Anthropic, OpenAI, and xAI—remain privately held. These firms are represented in the Morningstar PitchBook GenAI 20 Index, whose returns have dwarfed those of publicly listed AI companies since late 2024.

Unsurprisingly, more than three-quarters of the most frequently held AI companies are in the technology sector, with a further 10% in communication services. 

Our Equity Research-backed scoring methodology puts hard numbers on AI-driven revenues in the future. We categorised firms under the AI theme based on their role in the supply chain, percentage of companywide revenue driven by the theme five years forward, and if exposure to the theme will drive a net profit increase over the next five years. 

We then compared this list with the most frequently held stocks by AI-focused fund managers globally. While the scores broadly align, there are notable disagreements.

These are hidden gems—that is, stocks that earn high AI exposure scores from our analysts but infrequently appear in AI funds. These stocks include:

• CGI GIB.A
• Globant GLOB
• Hua Hong Semiconductor 1347
• TCS TCS
• Entegris ENTG

On the other hand, these stocks frequently appear in AI-focused portfolios but received low AI exposure scores from our analysts.

• Apple AAPL
• Palo Alto Networks PANW
• Intel INTC
• Qualcomm QCOM
• Datadog DDOG

AI has been particularly disruptive for software-as-a-service companies. Structural changes have led to downgrades across economic moats as AI erodes the edge of switching costs, intangible assets, cost advantage, and network effects.

In our recent moat review, these tech subindustries were the most disrupted by AI:

• Enterprise software
• IT services
• Vertical software
• Marketplace
• Payroll processing

These tech subindustries maintained their economic moats or received an upgrade from our analysts:

• Engineering software
• Content
• Exchange
• Gaming
• Cybersecurity

While single stocks allow you to cherry pick the best investment options without a management fee, an AI ETF or mutual fund may be more appropriate for investors who want to diversify and gain broad exposure to a basket of potential AI winners.

Investing in AI through a mutual fund or ETFs offers several benefits.

Investing in one or two stocks exposes investors to idiosyncratic risks unrelated to the theme. A diversified thematic fund should help mitigate this stock-specific risk while retaining price exposure to the technological shift.

In fast‑moving, transformative areas like AI, leadership can change quickly. Thematic diversification helps manage uncertainty as winners and losers emerge over time.

Technology themes such as AI tend to produce dominant winners. A basket approach increases the chance to participate in the returns of future “shooting stars” without needing to predict them in advance.

Skilled active managers can adjust exposure toward the most attractive parts of the value chain as the theme evolves.

Funds targeting the same AI theme can deliver very different outcomes. Broadly, investors have three approaches: core AI, dynamic AI, and peripheral AI.

Core AI plays heavily weight AI companies with high current or expected AI-related revenues, particularly in AI infrastructure. They can serve as a tool to play the AI theme within a portfolio, and typically score highly on the core AI Exposure metric.

Dynamic AI plays seek alpha within the AI theme by tilting toward AI winners and away from laggards. Advisers might consider these for return-seeking investors comfortable with active risk, since the play requires ongoing due diligence and carries underperformance risk. These funds’ AI Exposure scores may vary over time as portfolios rotate.

Peripheral AI plays focus on monetising second-order effects rather than the core build-out of AI technology itself. Advisers might consider them for investors seeking differentiated AI exposure, including diversification away from pure-play technology names. These funds generally score lower on our core AI Exposure metric.

US AI-focused fund assets remain around 75 times the November 2022 level—but not all offer equal exposure to the AI theme.

Our single AI exposure score reflects both analyst assessments of future AI revenue and the frequency with which AI managers hold each stock. For the full methodology, download the report.

The table below shows funds with the highest thematic exposure scores. Some standouts include:

• First Trust Bloomberg AI ETF FAI ranks highest overall, offering strong access to core AI stocks. Its selection and weighting are driven by direct AI revenue.
• Global X AI Semiconductor & Quantum ETF CHPX offers targeted exposure to compute power.
• iShares AI Innovation and Tech Active ETF BAI—the largest AI ETF—targets the core “AI stack.”

Other investment products earned low scores for their focus on adjacent themes, like quantum computing and big data, or AI enablers like utilities, energy, and materials rather than core semiconductors.

The full report shines a light on the methodology behind the AI exposure metrics. Download a free copy for more data-driven insights on:

• The investment case for AI
• Most frequently held stocks in the US, Europe, and AsiaPac
• Analysis of AI exposure by sector
• Stocks with high AI exposure and attractive valuations