Global Market: Wall Street's top asset managers bet big on AI infrastructure boom

ETMarkets.com

Long-term leases and financially strong tenants are central to asset managers’ strategy as AI infrastructure spending accelerates.

However, concerns are mounting that heavily indebted cloud infrastructure companies, known as neoclouds, could default and that the enormous spending on AI infrastructure may not generate sufficient returns. Against this backdrop, industry executives are highlighting their focus on creditworthy customers, long-term contracts and predictable rental income.

Blue Owl co-Chief Executive Officer Marc Lipschultz said the company owns physical infrastructure critical to the growth of the digital economy. According to Reuters, Blue Owl typically leases these assets for 15 to 20 years, with annual rent increases, providing investors with a predictable and growing income stream.

Lipschultz added that the firm seeks to limit risks associated with shorter lease agreements and uncertain pricing.

Shares of alternative asset managers advanced on Thursday. Blue Owl gained 6.5%, while Ares Management rose 2%. KKR and Blackstone each added 2.5%, and Apollo Global Management climbed 3.7%.

The great AI buildout

Data centres have emerged as a critical component of the AI boom, housing the servers and computing equipment required to train and operate artificial intelligence models.

As the world's largest technology companies race to expand computing capacity, demand for data centre facilities has surged, creating what industry executives consider a generational investment opportunity for alternative asset managers, according to Reuters.

Blue Owl said it has more than 130 data centres operating or under construction, representing nearly 14 gigawatts of leased and owned capacity. The company has another 21 gigawatts in its development pipeline.

Blue Owl Chief Financial Officer Alan Kirshenbaum said the company's investments in data centres were not simply a bet on the growth of artificial intelligence. Instead, the firm was taking credit exposure to major technology companies such as Microsoft, Amazon and Meta, which require substantial computing infrastructure.

Ares Management is pursuing a similar strategy, focusing its data centre development activities on major metropolitan markets, including Tokyo, Osaka, London and Sao Paulo.

The firm pre-leases projects to investment-grade hyperscalers under contracts lasting 12 to 15 years. These agreements have no termination rights and include inflation-linked rent increases, helping protect revenue streams against changing economic conditions.

Blackstone has also emphasised its focus on physical infrastructure and assets backed by long-term contracts. The company said last week that the vast majority of its data centre portfolio had initial lease terms of 15 to 20 years.

Around 96% of Blackstone's counterparties are rated investment grade, with an average market capitalisation of $2.5 trillion.

Blackstone President Jonathan Gray indicated that these characteristics made the company's exposure to the sector appear relatively low-risk.

AI capex boom

The investment surge spanning data centres, electricity generation, power transmission, equipment and software represents one of the largest capital expenditure cycles in history, comparable in scale to the development of the internet and the expansion of railway networks.

Ares Management estimates that AI-related capital expenditure demand will exceed $5 trillion through 2030. This includes approximately $2 trillion for physical data centre buildings and associated power generation and transmission infrastructure.

The scale of investment is also changing how companies finance AI infrastructure, with funding increasingly extending beyond equity and investment-grade debt into leveraged finance and private credit markets.

Ares Chief Executive Officer Michael Arougheti said investors were becoming more selective about counterparty risk and how that risk should be priced following a selloff in AI-related stocks earlier this month.

He also played down concerns that higher borrowing costs would significantly undermine AI infrastructure spending, noting that companies could otherwise finance projects through equity.

Arougheti said the financing mix had evolved as AI capital expenditure requirements increased, moving from predominantly equity funding to investment-grade borrowing and, more recently, greater demand for leveraged finance and private credit.

The shift presents an opportunity for alternative asset managers, which have expanded their presence in private credit and infrastructure financing as companies seek funding for increasingly capital-intensive projects.

Private credit risks under scrutiny

The growing financing requirements of AI and digital infrastructure are also broadening the private credit market beyond its traditional focus on direct lending.

Ratings agency Moody's said earlier this week that the sector was generating substantial, long-duration financing needs, creating opportunities for private credit providers.

However, the rapid expansion is also introducing new risks, particularly as capital requirements rise and financing structures become more complex.

Moody's highlighted growing concerns around borrower concentration, construction challenges, residual-value uncertainty and circular financing arrangements, even though many borrowers and counterparties have investment-grade credit ratings.

These risks have become increasingly important as investors assess whether the expected returns from AI infrastructure can justify the scale of spending and borrowing.

For alternative asset managers, the strategy centres on securing long-term contracts with financially strong technology companies while owning infrastructure that remains essential to the expansion of computing capacity.

The approach offers the potential for stable, inflation-linked income over extended periods. However, the sustainability of the AI investment boom will ultimately depend on continued demand for computing power, the financial strength of tenants and the ability of technology companies to generate sufficient returns from their growing infrastructure investments.