10+ hours of podcasts, in 5 minutes.
11 quotes from 1 episode on The Infrastructure Investor Podcast, each with a timestamped link to the source.
Andrew Thomas predicts AI inference demand will direct data center investment into tier-one cities near end consumers. Activating 100-megawatt campuses ahead of grid schedules allows developers to secure returns of 10% or higher.
Delivering 100 megawatts of capacity ahead of schedule directly increases the final yield on cost.
“As you approach a commencement date that is sooner and you have a real imbalance between demand for certain capacity and supply that can bring on 100 megawatts plus of capacity in that kind of timeframe, that yield on costs that you can achieve goes up.”
Urban infrastructure assets benefit from high entry barriers and steep switching costs that improve contract quality.
“You've got mission criticality of assets. You've got very high barriers to entry, very high switching costs. You have improved contract quality as well.”
From Why AI Inference Pulls Data Centers Back to Tier-One Metros
Andrew Thomas expects inference capacity to exceed AI training by several multiples. Delivering fast response times requires placing facilities in metropolitan hubs with dense network connections.
“We are going to see a material step change in the number of deployments that are catering towards AI inference. Most of what we're seeing and most of the management teams that we spend a lot of time with think that the inference opportunity is going to be several multiples the size of the AI training capacity.”
From Why AI Inference Pulls Data Centers Back to Tier-One Metros
“That is going to be more latency specific. That is going to be back to tier one markets that are closest to end consumers. We're going to see a meaningful amount of investment and shift for people who have existing data center platforms to try to address that demand need.”
From Why AI Inference Pulls Data Centers Back to Tier-One Metros
Constructing a hyperscale campus costs $10 million to $15 million per megawatt for footprints of 100 megawatts or more. Operators secure yields near 10% through 15-year contracts with investment-grade tenants.
“When you think about the typical hyperscale investment, you're spending somewhere between $10 to $15 million per megawatt in building out a facility. You're generally looking to build a campus that is going to be at least of 100 megawatts size or greater.”
From Data Center Yields: Underwriting Hyperscale vs. Urban Colocation
“And from a return standpoint, we're generally looking to sign 15-year contracts with investment grade counterparties where we're getting a yield on cost that is as close to 10% or above as possible.”
From Data Center Yields: Underwriting Hyperscale vs. Urban Colocation
Utility providers frequently fail to connect large deployments within 36 months. Data centers deploy natural gas turbines and fuel cells to bring facilities online faster and capture higher yields.
“I think the inability for the grid to service the large majority of deployments that people want to bring online over the next 12 and 24, 36 months means that you need to find alternatives to bridge to the grid.”
“And so already there are many projects in the market that are using either fuel cell solutions, natural gas solutions to bridge to when the grid can arrive. That is going to accelerate. That is going to be a higher percentage of projects that have that kind of bridging solution to it.”
Securing electricity and lining up specialized contractors extends delivery timelines for years. Andrew Thomas notes this prolonged development cycle creates execution risk.
“You're looking at a development cycle that is going to last for several years from the time in which you can procure power, line up all of the contractors that are required, actually go through construction, and bring a facility to ready for service…”
From Why Inexperienced Capital in Data Centers Will Get Burned
“Tenant quality is critically important, but you have diversity of tenant as well because of the incremental operating risk or operational complexity associated with having multiple customers and because you're able to charge higher price points…”
From Data Center Yields: Underwriting Hyperscale vs. Urban Colocation
“When you have more of a move to inference and a heightened focus again on what is the interconnection position that a lot of these assets have to capitalize upon the shift into inference, I think you'll see people recognize, all right, that's a strategically important asset.”
From Why AI Inference Pulls Data Centers Back to Tier-One Metros
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