Investment Discipline Amid the AI Infrastructure Boom

by Bryan Tsu , Vineet Agrawal of PIMCO, 6/2/26

Key Takeaways

  • The AI boom is generating tremendous physical infrastructure needs. Data centers, power production, and chips must be built to support AI’s growth, creating long‑lasting investment opportunities.
  • Many of the biggest areas of opportunity are in bonds and loans. Large, established technology companies are increasingly borrowing to fund infrastructure spending, opening a door for fixed income investors.
  • Focus on well-structured deals with claims on hard assets. By investing in essential infrastructure through secured financings, one can seek steady returns while mitigating risk – even as technology continues to evolve.

Businesses are racing to build the physical infrastructure that makes AI usable at scale – data centers, the graphics processing unit (GPU) hardware stack, power, and cooling. Estimates suggest more than $5 trillion could be needed through 2030 to fund this buildout across the broader AI ecosystem (see Figure 1). For investors, the opportunity is not just the scale of spending; it’s the ability to finance essential infrastructure through structured credit backed by real assets and predictable, contracted cash flows.

Figure 1: Hyperscalers’ capital spending is expected to rise further

The key question is how to commit capital to long-duration projects while technology and business conditions evolve. In our view, rather than trying to pick AI winners, the answer is to focus on the infrastructure layer itself – one layer below the AI applications – through enforceable collateral, control over key contracts, and protections that help ensure repayment even if things don’t go as planned.

Stewardship also matters in how these projects are developed. The strongest data center investments are built in partnership with local utilities and communities. Done well, they can add needed power and grid infrastructure, distribute fixed costs, support local economic development, and avoid worsening affordability by ensuring that communities share in the benefits of the buildout. We look for projects where the data center contributes to the broader infrastructure needs of the region, rather than simply adding power demand to an already constrained system.

Counterparty quality matters as well. Large global hyperscalers – the biggest tech companies and cloud service providers – typically have diversified revenues, strong balance sheets, and long-term strategic flexibility, even as their capital spending continues to rise. By contrast, tenants tied solely to a single AI application and still operating at a loss present very different risks.

Read more: AI Credit Expansion: Assessing the Micro and Macro Risks