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Real assets and the infrastructure behind AI

4 August 2026

Christopher Walsh, CFA, Senior Portfolio Manager, Multi-Asset Solutions

Paul Kalogirou, Head of Client Portfolio Management, Asia & Global Multi-Asset Solutions

Artificial intelligence (AI) is often positioned as a story of models and applications, but its growth depends heavily on something far more tangible. Real assets such as data centres, power grids, and raw materials form the physical that supports AI development. As structural forces reshape the investment landscape, real assets are emerging as an enabler of the AI buildout.

Key points:

  • The current macro backdrop of elevated inflation, AI-related infrastructure demand, and geopolitical tensions may be supportive of selected real assets.
  • Infrastructure and energy are important elements supporting the development of AI.
  • Some real assets have characteristics that may provide exposure to inflation-linked return potential.
  • Structural forces such as deglobalisation, energy and materials security, electrification, and scarcity are contributing to renewed interest in real assets.
  • Data centre growth could contribute to demand for electricity generation and selected key minerals.

Three major macro trends

We believe three major trends are influencing the current investment regime and may affect the outlook for selected real assets:

  1. Persistent, higher inflation: Persistent inflation may be supportive of certain real assets, given their tangible nature and, in some cases, their ability to pass through higher costs.
  2. Artificial intelligence: The expansion of AI requires significant power and infrastructure, which could create long-term demand for selected real assets.
  3. Geopolitical risk: Rising geopolitical uncertainty has affected supply chains and increased focus on physical assets and resource security.

Among these themes, AI-related infrastructure and energy demand provide an example of where real assets may play a role in the age of intelligence.

The intersection of real assets and AI

The AI stack is sometimes described as a five-layer cake: energy, semiconductors, infrastructure, models, and applications. Real assets intersect with two key layers: energy and infrastructure.

intersection-of-real-assets-and-ai

At its core, economic growth can be viewed through the lens of energy use – a principle that helps explain why AI’s expansion is closely linked to the energy required to power it. Meanwhile, the infrastructure layer represents the physical buildout needed to support AI, including data centres, construction, and electrical systems.

Together, these layers form an important foundation supporting the AI ecosystem.

Key traits and types of real assets

Certain real assets may share traits such as relatively inelastic demand, long lead times for new supply, high barriers to entry, and essential-service characteristics. They can be grouped into four broad categories, which may provide exposure to real-return potential and income generation.

  • Natural resources: Raw materials that support economic activity, including companies involved in the extraction, production, refinement, and distribution of energy and other raw materials.
  • Infrastructure: Essential services with high barriers to entry, such as utilities, which may become increasingly important as AI-related demand grows.
  • Real Estate Investment Trusts (REITs): Real estate across various sectors, such as residential, office, healthcare, and industrial, that may offer exposure to rental income, and in some cases, inflation-linked cash flows.
  • Inflation-resilient fixed income: Certain fixed income may offer inflation protection features through principal adjustment.
     
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Structural forces supporting real assets

Beyond inflation, we believe several broader themes could provide support for selected real assets:

  1. Deglobalisation and supply chain resilience: Events such as the COVID-19 pandemic have prompted many countries to strengthen regional resilience through reshoring, nearshoring, and friendshoring, reshaping global supply chains.
  2. Securing power, materials, and energy: Recent geopolitical shocks have highlighted the importance of strategic reserves and inventories in helping manage supply disruptions.
  3. AI, electrification, and industrial rebuild: The global development of AI and increased electrification require significant power consumption and capital investment across infrastructure.
  4. Supply scarcity and underinvestment: Periods of underinvestment by some energy and materials producers may have contributed to supply constraints in certain areas, which may provide support for selected real assets.

The data centre boom and its potential beneficiaries

Demand for data and compute capacity is increasing alongside the growth of AI. McKinsey estimates that global demand for data centre capacity could rise at an annual rate of 19% to 22% from 2023 to 2030, reaching annual demand of 171GW to 219GW by 2030.

Companies involved in the infrastructure layer supporting this growth, including engineering and construction firms, may benefit from increased demand, although the timing and scale of opportunities will vary.

In addition, the International Energy Agency (IEA) expects global electricity demand from data centres to more than double by 2030, with AI an important driver of this increase. It also notes that a range of energy sources will likely be needed, with renewables and natural gas expected to play leading roles in key markets. Similarly, data centres could contribute to copper demand over the coming years.

While volatility is likely to accompany the AI infrastructure buildout, we view the theme as a multi-year opportunity that should be assessed alongside valuation, execution, policy, and commodity-cycle risks. Real assets may offer exposure to inflation-sensitive income streams and participation in selected areas of long-term structural growth.

estimated-global-data-centers-capacity-demand

 

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  • Global Equity Diversified Income (GEDI) Fund: Staying selective through market volatility

    Global equity markets have recently experienced greater volatility. Much of this has been driven by earnings announcements from AI hardware, semiconductor and large cloud-computing companies. Concerns about potential interest rate hikes have also added to investor uncertainty. After a prolonged period of strong performance in AI-related areas, market expectations have become demanding. Even companies reporting solid results have experienced sharp share-price moves when their outlook has only met, rather than exceeded, investor expectations. Against this backdrop, the GEDI Fund remains focused on its core objective: generating income while maintaining diversified exposure to potential capital growth.

    read more
  • Real assets and the infrastructure behind AI

    Artificial intelligence (AI) is often positioned as a story of models and applications, but its growth depends heavily on something far more tangible. Real assets such as data centres, power grids, and raw materials form the physical that supports AI development. As structural forces reshape the investment landscape, real assets are emerging as an enabler of the AI buildout.

    read more
  • The engine behind AI: Semiconductors are fuelling the next era of technology

    Semiconductors belong to one of the most specialised yet globally integrated industry chains. From design, equipment, and materials to manufacturing and commercialisation, the production of a smartphone chip alone spans many countries across continents, creating tremendous opportunities for companies, consumers, and investors. With semiconductors increasingly becoming the backbone of an artificial intelligence (AI) race few are prepared for, understanding this sector is key to unlocking where the next wave of technology competition is heading.

    read more
see all