How to Invest in AI Funds and AI-Focused Investment Vehicles
Artificial intelligence is the defining investment theme of the current decade. But for internationally mobile investors who want exposure to AI's growth without the challenge of picking individual AI stocks, AI-focused investment funds, ETFs, and structured vehicles offer a range of accessible entry points.
This guide sets out the main categories of AI investment vehicles, what to look for in each, and how to think about structuring AI exposure within a broader portfolio.
The Investment Case for AI Exposure
Before examining the vehicles, it is worth clarifying the investment thesis. AI is not simply a technology trend — it is a broad-based productivity revolution affecting virtually every industry. The compounding effect of AI on productivity, margins, and competitive dynamics creates investment opportunities across:
- The infrastructure layer: companies providing the hardware, data centres, and cloud infrastructure that AI requires
- The platform/model layer: companies developing and commercialising foundation AI models
- The application layer: businesses using AI to achieve durable competitive advantages in specific industries (healthcare, finance, manufacturing, professional services, media)
The challenge is that the investment opportunity varies significantly by layer and by company. Infrastructure has already attracted substantial capital and some valuations reflect significant AI revenue growth expectations. The application layer, where AI transforms specific industries, may offer more varied and less fully priced opportunities over the next 5–10 years.
Investment vehicles that provide exposure across all three layers — or allow deliberate emphasis of specific layers — offer the most flexible approach.
1. Thematic AI ETFs
Exchange-Traded Funds (ETFs) tracking AI and robotics themes are the most accessible and cost-effective route to diversified AI exposure for most investors. They are bought and sold on stock exchanges like individual shares and carry relatively low annual management fees (typically 0.4–0.75% for thematic ETFs).
What thematic AI ETFs typically hold:
- Semiconductor manufacturers (hardware enablers of AI)
- Cloud computing platform companies
- Data analytics and software companies
- Robotics and industrial automation companies
- Healthcare and diagnostic AI companies
Examples (for illustrative purposes — not recommendations):
The Global X Artificial Intelligence & Technology ETF holds a diversified portfolio of AI-related equities globally. The iShares Automation & Robotics UCITS ETF covers both AI and physical robotics companies. L&G Artificial Intelligence UCITS ETF focuses specifically on companies deriving a meaningful portion of revenues from AI.
These examples are mentioned for illustration only. Specific ETFs' compositions, fees, and performance change — verify current details directly from providers before investing.
What to look for in an AI ETF:
- Index methodology: how does the index define "AI-related"? Is it based on revenue derived from AI, or a looser inclusion criteria?
- Top holdings and concentration: does the ETF hold 200 well-diversified companies, or are the top 10 positions 60% of the fund?
- Rebalancing methodology: how and how often is the index rebalanced? Does it add emerging AI companies as they grow?
- Fees: annual total expense ratio (TER). For a passive ETF, fees above 0.75% are difficult to justify
- Currency: is the ETF denominated in USD, GBP, or EUR? Currency hedging is available on some versions
2. Actively Managed AI Funds
Active AI fund managers select specific companies they believe are best positioned within the AI theme. In theory, this allows concentration in the highest-conviction ideas and avoidance of companies included in an index simply because of their size rather than genuine AI credentials.
Potential advantages of active management:
- Ability to distinguish between genuine AI businesses and superficial "AI-washing"
- Flexibility to emphasise specific sub-themes or geographies
- Faster adjustment to rapidly evolving AI landscape than index rebalancing cycles
Key considerations:
- Management fees: typically 0.75–1.5% per annum, materially higher than passive ETFs
- Track record: AI investing is a relatively recent specialism — most "AI-focused" funds have limited long-term track records
- Underlying conviction: examine whether the fund truly concentrates in pure-play AI companies or simply overweights large technology companies that any technology fund would hold
- Manager insight: is the team genuinely technologically literate and close to the AI industry, or is this a standard technology fund with a new label?
3. Private Equity and Venture Capital in AI
For sophisticated investors with longer time horizons and the capacity to absorb illiquidity, private markets offer access to AI companies at earlier stages of development — before they are publicly listed.
Early-stage AI venture capital (VC):
- Funds investing in AI start-ups at seed and Series A/B stages
- High risk — most early-stage companies fail; returns are concentrated in a small number of breakout successes
- Typical hold period: 7–10 years
- Minimum commitments: USD 250,000–1 million or more for institutional-quality funds
- Expected return profile: wide range, with top-quartile VC funds targeting 3–5× returns on invested capital over a decade (with no guarantee of achieving this)
Growth equity and late-stage AI:
- Funds investing in AI companies at later funding rounds (Series C, D, or pre-IPO stages)
- Less binary than early-stage VC — companies have demonstrated product-market fit
- Still illiquid; 5–7 year hold periods typical
- Lower risk than early-stage VC but still substantially higher than public markets
Co-investment and secondary market platforms:
- Some wealth management platforms and specialist firms offer individual investors the ability to invest in specific AI companies alongside lead VC investors, or to purchase existing stakes on the secondary market from employees or early investors
- Minimum thresholds vary widely — from USD 25,000 on some retail platforms to USD 500,000+ for institutional co-investments
4. Structured Notes Linked to AI Indices
For investors who want AI upside with some capital management (protection or enhanced participation), structured notes linked to AI-related indices offer a further option.
Issuers (typically major investment banks) create notes where:
- Capital protected notes: the investor's principal is returned at maturity regardless of index performance, with participation in index upside above a given level
- Autocall notes linked to AI indices: the investor earns a conditional coupon if the AI index is above a trigger level at regular observation dates, with capital protection barrier
These combine the thematic AI exposure with the structured product mechanics described in separate guides on this site. As with all structured products, the key considerations are the issuer's creditworthiness, the participation rate, the underlying index composition, and the tax treatment.
Portfolio Construction: How Much AI Exposure?
The appropriate level of AI exposure depends on the investor's existing portfolio:
- If you hold broad global equity funds or ETFs: you already have indirect AI exposure through large-cap technology companies that dominate global indices. Adding a dedicated AI ETF increases AI concentration above what the market weight implies — a legitimate active decision but one that warrants deliberate thought
- If you hold a concentrated equity portfolio: adding an AI fund provides both thematic focus and potential diversification across the AI value chain
- Core vs satellite framing: many advisers treat AI as a satellite allocation (10–20% of the equity portion of a portfolio) rather than the core holding. The core remains diversified global equities; the satellite positions for specific themes
Whatever the allocation, investors should be comfortable with the concentration risk, understand that thematic investing cycles can produce periods of significant underperformance versus broad indices, and resist the urge to over-allocate at peak sentiment.
The information in this guide is for educational purposes only and does not constitute financial advice. Investment values can fall as well as rise. Thematic funds are subject to concentration risk. Past performance is not a guide to future results. Seek independent financial advice before investing.
How Global Investments can help
Global Investments keeps its clients informed about developments in AI investment vehicles — from institutional-grade AI funds to structured products with AI index linkage. We can review your existing portfolio for AI exposure, recommend appropriate vehicles for your investment profile and jurisdiction, and ensure that any AI allocation is proportionate and well-integrated with your overall wealth plan.
Contact us to arrange a consultation and discuss your approach to the AI mega trend.
Frequently Asked Questions
What is the difference between an AI ETF and an AI-focused active fund?
An AI ETF tracks an index of AI-related companies using a rules-based methodology — it holds whatever the index holds. An active AI fund is managed by a portfolio manager who selects specific companies they believe will outperform, potentially concentrating positions in high-conviction ideas. ETFs offer lower fees and broad diversification; active funds offer the potential for outperformance but carry higher fees and manager selection risk.
Are AI ETFs diversified across the AI value chain?
Quality varies. Some AI ETFs are genuinely diversified across infrastructure, platform, and application layers of the AI value chain. Others are more narrowly concentrated in a few large-cap technology companies. Always examine the underlying holdings of any AI ETF before investing — concentration in the top 5–10 holdings is common and should be evaluated.
What is concentration risk in AI funds?
Concentration risk means that a fund's returns are heavily dependent on a small number of holdings. Many AI-themed ETFs hold a large proportion of their assets in a handful of mega-cap technology companies. If those companies underperform — even if the broader AI theme is intact — the fund performs poorly. This is not unique to AI funds but is common given the dominance of a few large players in AI infrastructure.
What are AI structured notes?
Some structured product issuers offer notes whose return is linked to the performance of an AI-related index (such as a custom AI technology index). These can combine capital protection or autocall mechanics with AI exposure. As with all structured products, the return mechanics, participation rates, and counterparty risk must be carefully evaluated.
Can I invest in private AI companies through a fund?
Yes — a number of venture capital and growth equity funds provide access to private AI companies for sophisticated investors. These typically require minimum commitments of USD 250,000 or more, have 7–10 year lock-up periods, and are suitable only for investors who understand illiquidity and venture-stage risk. Some wealth platforms offer access to secondary stakes in AI companies at later funding stages.
This guide is for general information only and does not constitute financial advice or a personal recommendation. The value of investments can fall as well as rise and you may get back less than you invest. Past performance is not a guide to future returns. Tax rules, investment regulations, and the availability of specific investment vehicles change — always verify current rules and seek advice from a qualified independent financial adviser before making any investment decisions.