Nscale’s planned US$35b IPO has thrown a harsh spotlight on the messy reality of financing huge AI data centres, where billion dollar revenue backlogs can hinge on one delayed project, one local permit, one funding deadline. That uncertainty cuts both ways. It can punish investors who chase the wrong story and reward those who focus on which specialty lenders are actually positioned to support, or sidestep, this build out. This article walks through three stocks from our Specialty Lenders and Lessors to AI Data-Centre Projects screener that appear positively exposed to the Nscale and Anthropic news, and explains why their role in funding complex projects like the Monarch Compute Campus could be relevant for portfolio decisions at this point in time.
The three stocks in focus below are only a sample of this idea, and the broader screen surfaced 25 more listed lenders and lessors with equally detailed stories that are not covered here.
To identify which of these potential funders of AI data-centre build outs best matches your risk, sector, and time horizon preferences, go straight to the Specialty Lenders and Lessors to AI Data-Centre Projects screener.
Overview: Equinix operates a global network of interconnected data centres that host critical digital infrastructure and AI workloads for enterprises and cloud providers.
Market Cap: US$102.6b
Equinix matters in this screener because it sits where AI data-centre demand, massive capex plans, and complex project funding all intersect.
"Equinix plans to invest US$5b to US$7b per year in development from 2027 to 2029, targeting low to mid 20% cash on cash returns with 2 to 3 year stabilizations, which, if achieved, could support higher revenue and AFFO growth than currently reflected in the stock."
What ultimately happens to those returns rests on one pressure that could quietly reshape both future margins and the growth profile investors expect.
That pressure is exactly what the full narrative for Equinix unpacks. It shows how Equinix’s funding model could be accelerating, stalling, or quietly masking future cash returns.
Overview: Digital Realty Trust runs a global network of large data centres where enterprises and cloud providers host, connect, and power AI workloads.
Operations: Digital Realty generates about US$6.8b from commercial REIT activities, with roughly US$3.6b in the United States and US$3.2b from other regions worldwide.
Market Cap: US$67.9b
Digital Realty Trust matters in this screener because it owns the kind of large, interconnected campuses AI tenants need, and it relies on substantial outside funding to keep that build program moving.
"Digital Realty's record signed but not yet commenced lease backlog of about US$1.9b, plus a further US$410m of hyperscale leases signed in July, points to a large pipeline of contracted revenue that has not yet flowed through earnings and could support future core FFO per share."
The real swing factor for investors is how pressure on its funding costs and leverage choices ultimately feeds through to future margins.
That funding question is exactly what the full narrative for Digital Realty Trust unpacks, showing how backlog, leverage and AI demand could be accelerating, or quietly masking, Digital Realty Trust’s true earnings power.
Overview: Fermi develops private, gigawatt scale electric grids that feed AI data centres with dedicated, highly redundant power capacity.
Market Cap: US$1.93b
Fermi matters here because it is not just leasing into AI data-centre projects. It is trying to supply the dedicated power backbone those facilities now demand.
"Rising power needs from artificial intelligence workloads are pushing large tenants to seek long duration, dedicated power solutions."
What investors really need to watch is how one future financing swing factor ultimately shapes pricing power and long term returns on that grid build.
That financing swing factor is exactly what the full narrative for Fermi breaks down, showing where pricing power could be accelerating or quietly masking future returns.
Fresh ideas can gain momentum while the data is still clean and the stories remain under the radar. Consider acting early instead of waiting until much later.
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