Real assets, AI and the case for a total portfolio approach 

At a time when traditional asset correlations have been tested, allocations to real assets have increased for a simple reason: they have helped to deliver resilient returns, diversification and inflation sensitivity as intended. 

In the age of AI, however, describing real assets as stable, steady and resilient no longer tells the whole story. While continuing to perform their core portfolio function, real assets are becoming more central to the next phase of economic development, with select parts of these markets emerging as direct expressions of the structural themes reshaping the global economy.

The evolution of real assets investment is often expressed through the lens of megatrends. Societal needs are evolving, reconfiguring the physical and operational systems required to support future growth. In the real assets arena, AI, digitization and the energy transition are reshaping demand for power, connectivity, logistics capacity and digital infrastructure, while reinforcing the need for long-term capital to finance, develop and operate underlying assets.

Rapid growth in data usage and artificial intelligence has increased demand for data centers, fiber networks and connectivity assets, while the global energy transition is arguably creating new investment opportunities across renewable generation and grid infrastructure. Increasingly, capital-constrained governments are relying on private capital to help finance these developments, expanding the role that institutional investors can play in delivering essential infrastructure.

In the AI boom, the role of real estate includes securing and productizing scarce data center sites – land, entitlements, and buildings in locations with power and fiber optic access – to enable computing capacity to be delivered at scale. Structural AI demand is converted into durable cashflows through leasing structures including co-location and hyperscale built-to-suit properties.

Through real assets, access to the future economy becomes broader and more immediate. Allocations to these areas are attracting investors not merely as portfolio ballast, but as a means of accessing structural growth through assets with tangible utility and potentially durable cashflows. In this respect, real assets are not simply “housing” the AI boom; they are also helping make it investable, particularly for investors seeking resilience alongside thematic exposure.

There is a “picks and shovels” logic to this approach, but these allocations are more sophisticated than the phrase implies. Accessing AI through real assets is not simply about avoiding technology risk, but about gaining exposure to the enabling assets and systems on which AI deployment depends. Opportunities tend to be underpinned by business models that are more asset-backed, more cashflow-oriented and, critically for investors, less reliant on a narrow set of corporate winners in public equities.

AI may be the clearest illustration of how real assets are evolving, but it is not the only one. Other societal needs continue to create substantial forward opportunity across private markets: underinvestment in water infrastructure, the increasing complexity of transport networks and the demand for more efficient essential-service platforms all point to a broader investment landscape in which infrastructure and real estate have a more significant role to play.

This shift is evident not only in the assets themselves, but also in the businesses that own, operate, and improve them. In the mid-market, in particular, the opportunity is not only to own assets linked to long-term themes, but to back businesses and platforms where value can be created through operational improvement. In more fragmented parts of the market, managers may have greater scope for bilateral origination, bespoke structuring, and active asset management, particularly where businesses are undermanaged, founder-led, or early in their institutionalization. For asset owners, this expands the opportunity set in two ways at once: by increasing access to structural growth themes, and by opening up a wider range of manager-led return opportunities. It also increases the importance of manager selection, since broader opportunity sets are not necessarily easier to navigate well.

The same forces creating opportunity can also create a different kind of portfolio challenge. For investors, the nexus of AI and real assets is both a return opportunity and a potential source of hidden concentration or overlap. An allocation to AI-linked infrastructure or data-center-driven real estate may appear distinct from public market technology exposure. In economic terms, however, the underlying driver may be more closely related than traditional asset class labels suggest. This overlap can become more pronounced when similar themes are present across public equities, private equity, infrastructure and real estate at the same time. AI-related demand may feature across the portfolio in different ways, but it can still create concentration to the same structural driver. In this context, diversification by vehicle or asset class does not necessarily equate to diversification of underlying exposure.

If infrastructure is to continue to serve as a portfolio stabilizer, investors need to understand where the same AI thesis is being reinforced across multiple parts of the portfolio, and where it is providing genuine diversification. The risk of “doubling up” stems not from any one allocation, but from assessing the portfolio in silos rather than the traditional holistic approach. A total portfolio approach matters here not as an abstract governance concept, but as a practical discipline. It requires alignment across teams, a more integrated view of risk and exposure, and the flexibility to respond as themes migrat and evolve across public and private markets. The pace of innovation in AI means there may continue to be uncertainty around how the technology develops, where value ultimately accrues and how durable particular business models prove to be. But one point is already clear: the energy, connectivity, water requirements and physical capacity required to support this transformation, as well as the potential for policy risk, are changing the way investors think about real assets.