The ETFs Powering the AI Supply Chain
27 APR, 2026
By VanEck
Marketing Communication
What Actually Powers AI?
AI may feel purely digital, but it relies on physical infrastructure—hardware, electricity, and raw materials. Training a model like GPT-4 reportedly consumed around 50 gigawatt-hours of energy—enough to power a major city for days. And that’s just the training phase. Inference, serving AI to millions of users, requires continuous, large-scale energy use.
All that computation flows through three critical layers:
- Semiconductors that. perform computations
- Energy to run data centers 24/7
- Strategic metals embedded in hardware.
If any layer faces constraints—chip shortages, power limitations, or restricted access to minerals—it impacts the entire AI ecosystem. Instead of focusing only on software companies, investors can target the infrastructure underpinning AI.
How the AI Supply Chain Works
AI runs on physical infrastructure. Before a model can answer a question or generate an image, semiconductors process data, power plants keep servers running, and raw materials are mined, refined, and built into hardware. Each layer depends on the one below it.
Source: VanEck. These are not recommendations to buy or to sell any security.
Why Semiconductors Are Critical to AI?
Without advanced chips, none of these works. GPUs and custom accelerators handle the computations required to train models and run AI applications. The entire AI wave can be interpreted as, at its core, a semiconductor demand story.
The industry is highly concentrated, with only a few companies producing cutting-edge chips, creating strong demand and pricing power.
VanEck Semiconductor UCITS ETF (SMH) provides exposure to leading U.S.-listed chip companies across design, manufacturing, and equipment. Key risks to consider are liquidity, concentration, geopolitical, and market volatility risks.
Why AI Needs Reliable Energy
AI data centers require constant, uninterrupted power. While renewable energy sources help, their intermittency creates challenges.
Nuclear energy is gaining attention as a reliable, zero-carbon solution, with companies like Microsoft, Amazon, and Meta investing alongside supportive government policies.
VanEck Uranium and Nuclear Technologies UCITS ETF (NUCL) covers the full nuclear value chain—uranium mining, reactor construction, and electricity generation—supporting the growing energy demands of AI infrastructure. Key risks include liquidity, concentration, regulatory, and market volatility risks.
What Materials Are Important to AI?
AI infrastructure depends on specialized metals:
- Neodymium and dysprosium for magnets in cooling systems and drives
- Copper for electrical connectivity
- Tantalum for stable power delivery in chips
- Gallium and germanium for semiconductors and fiber optics.
VanEck Rare Earth and Strategic Metals UCITS ETF (REMX) provides exposure to companies deriving at least 50% of revenue from rare earths and strategic metals—essential to AI hardware, from semiconductors to data centers. Risks to consider are liquidity, concentration, commodity price volatility, and geopolitical risks.
Discover the AI Build-Out with VanEck
The biggest AI winners over the next decade may not be software companies, but the firms enabling its infrastructure—those producing chips, generating power, and supplying essential materials.
VanEck’s AI supply chain ETFs let investors gain targeted exposure to the physical infrastructure that every AI company depends on.
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¹ Global Electricity Initiative. Data Centers and AI Energy Consumption: The Surge in Electricity Demand. 2026.
² The Washington Post. AI firms turn to nuclear power amid soaring energy demand. 2025.
³ International Energy Agency (IEA). Global Critical Minerals Outlook 2025. Paris: IEA, 2025
