“Data centers are here to stay, and the world is going to need them as AI adoption accelerates,” says Steven Siesser, partner at Lowenstein Sandler, chair of the firm’s private equity practice and co-lead of its data center practice, in conversation with Bloomberg Intelligence’s Associate Director of Research Alexandra Davidov and Senior Technology Analyst Anurag Rana. In this episode of Tech Disruptors, they discuss how AI data centers are reshaping infrastructure finance, from hyperscaler-backed leases and neo-cloud credit risk to private equity, private credit and sovereign capital. Siesser explains why power, community acceptance and supply-chain constraints remain key bottlenecks, while long-term leases and hyperscaler demand are reshaping how lenders underwrite the build-out.

Financing the AI Data Center Boom

Tech Disruptors

# Full Transcript

**Podcast:** Tech Disruptors

## Participants

- **Alexandra Davidoff** (Bloomberg Intelligence)
- **Anna Raghana** (Bloomberg Intelligence)
- **Stephen Caesar** (Loewenstein Sandler)

## Transcript

Hello and welcome to the Bloomberg Intelligence Tech Disruptors podcast. I'm Alexandra Davidoff, Associate Director of Research for Global Industries at Bloomberg Intelligence. With me here today from BI is Anna Raghana, Senior Technology Analyst. I'm pleased to welcome Stephen Caesar to the podcast. Stephen is a partner at Loewenstein Sandler, where he chairs the firm's private equity practice and co-chairs the transactions and advisory group.

He works with investors, companies, intermediaries on a wide range of private equity, credit and other complex transactions, serving as both a legal and strategic advisor. Stephen also co-leads Loewenstein's data center practice, which gives him a close view into how investors, lenders and sponsors are approaching the rapid build out of AI infrastructure.

That perspective is especially timely as data center capital needs rise, financing structures evolve, and lenders weigh risks around power, tenant credit, lease terms, technology change and hyperscaler demand. Stephen, welcome to the podcast. Thank you very much. Good morning and wonderful to be here.

Our discussion with Steve will take a deep dive into various ways lenders are assessing the credit risk associated with financing these deals. The annual capital expenditure relating to data centers is approaching a trillion dollars a year and no signs of any of the hyperscalers slowing down. The amounts being raised are unprecedented and there are multiple risks facing these buildups, with the rapid changes in technology being one of the biggest ones. Stephen, can you please give us an overview of your current role?

Sure. So, as a lawyer, as a transactional lawyer, I'm involved in all aspects of the data center development. They are primarily around the financing, the leasing and the joint venture structure. So, when companies need to develop or build a data center, it takes an inordinate amount of capital to construct even the smallest of the data centers. And that's where I spend my time.

So, I represent the data center developers primarily in their development work and their financing work. So, when you look at the previous buildout, what are some of the similarities and differences between the current AI data center buildout compared to traditional data centers?

So, I kind of would look at it in three different categories. There were the original sort of co-location data centers, right? Where my law firm, for example, used to maintain a whole server farm in our building, in our office. And then we moved those out to, I think, locations in Ohio and Arizona where we co-located.

And those were basically one type of data center. Then the second, you know, we began the Bitcoin mining data centers. And now, of course, is the third, which...

Financing the AI Data Center Boom

Transcript

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Every day you wait, your competitors are finding
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Financing the AI Data Center Boom

Transcript

Built for investment professionals

Every day you wait, your competitors are findingedge in conversations you're not hearing.

Every day you wait, your competitors are finding
edge in conversations you're not hearing.