A data center landlord shares what he expects for the future of AI demand and revenue

• AI’s physical supply chain, including chips and data centers, is where the early revenue is.
• Data centers, crucial for AI, face high demand, with prices doubling and low vacancy rates.
• Databank CEO says customers are pre-leasing forthcoming buildings two years in advance.

Artificial intelligence may seem intangible, but it has an immense physical supply chain behind it, and at least for right now, that’s . How much do fluctuations in the AI hardware market matter to your planning and how disruptive is this to your customers?

It doesn’t matter. We’re obviously acutely aware of it because, with these developments, we can put our foot on the gas in terms of how quickly we bring capacity online and we can also kind of elongate it a little bit. So we want to moderate that in terms of what we’re hearing from customers.

I think customers might be in some ways annoyed, but in other ways relieved, because there were a lot of complaints that Nvidia is trying to bring out a new architecture every year. It doesn’t allow the people buying these chips to sweat them and get their full useful life.

But when we build, let’s say a 40-megawatt data center, it has 10 four-megawatt data halls. There are 10 little data centers within the building itself. If we were going to build a data center, without a pre-lease, we’re only going to outfit the first four megawatts of it. So you stagger your capital.

BI: Do you think about ROI when it comes to AI when you’re making data center deals?

That’s a fantastic topic, and especially for me, since I have been in the sector since the mid-90s, I saw the dot-com crash. I think everyone realized that the internet is real, it was just that the business models at that time didn’t create earnings, and that’s why things went off a cliff. You could argue that with GenAI that same dynamic could occur.

We’re definitely tracking that in terms of, whether we believe our customers are getting ROI on their investments.

It’s still too early, but, this technology is really revolutionary. It’s probably one of the most transformative technologies since the internet, frankly, or maybe mobile phones. We’re going to look back at it in seven years and say, ‘Oh my gosh, that was so primitive, right?’

Some companies are able to demonstrate ROI, but certainly, it’s not uniform right now. But that’s to be expected from the introduction of such a transformative technology.

We’re looking at the customer’s credit quality, for sure. Just like any landlord, we want to make sure that our tenants are going to be viable for the term of that lease, right? The good news is this technology is so sophisticated and so expensive that you need to be relatively financially stable and have the technical ability to use it.

We’re seeing more larger enterprises — hyperscalers and large technology companies adopt these GPU deployments and I think we’ll start to see a lot more of that next year.

If there’s a company that just got started four months ago, has gotten an allocation of a couple of 1000 GPUs, and wants to take five megawatts of data center space — we’re not going to do that. We’ll let someone else support them. We’re staying close to very creditworthy tenants, or if they are earlier-stage companies, they’re well-funded.

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