Hey. We will go ahead and get started. My name is Cameron McVeigh. I cover communications infrastructure here at Morgan Stanley, and it's my honor to welcome Matt Mercier, CFO of Digital Realty. Welcome, Matt. Thank you. Great to be here. Before we get started, I'll read this. For important disclosures, please read our Morgan Stanley Research Disclosure website. If you have any questions, please reach out to your Morgan Stanley sales representative. Okay. We will get started. Matt, you know, Digital Realty reported strong fourth quarter and full-year results in February. There's a record zero to 1 MW bookings and a near-record backlog. I guess, as you think about the past year and the year ahead, you know, what would you identify as the one or two main drivers behind recent results, and what are the key priorities for 2026? Yeah, I mean, you know, thanks for, thanks for the setup. I mean, we came into 2025, with, you know, roughly guiding to a little bit over 5% bottom-line Core FFO growth. We ended up the year, basically almost 300 basis points above that. I would say the setup for 2025 is very similar to kind of where we're setting up for 2026, partly why you're seeing a congruence in terms of where we're, where we started our initial guidance, you know, close to 8% for 2026. The key drivers I would say are, one, continuing our momentum on our zero to 1 MW interconnection business, which I'm sure we'll dive into more. We've seen great growth and execution across that segment for a number of reasons in terms of the number of markets that we're in, our connectivity profile and capabilities and product set. As a result, we grew the signings as an example there over 30%, interconnection bookings over 20%. We see that as a very stable, sticky, connectivity-rich business that we're seeing overall demand increase from an enterprise perspective. We see a long-term tailwinds in terms of not only continued digital transformation from that same enterprise base, but also, I think, near and long-term scaling for, you know, AI, in particular inference, which from our standpoint, we're still in quite the early innings. I think that's a foundational layer of our growth. In addition, we're also, you know, we're also, did well on signings that we did in late 2024 in through 2025. We had over $1 billion in overall bookings at our 100% share. That led to a very healthy backlog of over $600 million in revenue that we've got expected to commence in 2026. Again, kind of de-risking the majority of our revenue profile for 2026 and therefore, supporting that overall bottom line growth per share. Then I think all those things, you know, largely the favorable supply-demand dynamics are proving to be a, call it a pricing tailwind, you know, favorable pricing dynamics throughout both of those segments, leading to improved mark-to-market story, which is benefiting our same-store portfolio. I think all those things together are what's giving us conviction for continued bottom-line growth that we put up for 2026, but also continuing that in 2027 and beyond. As we've said, that's a clear and key focus for us in sustaining that momentum on bottom-line growth. Great. That's helpful. Just to follow up on the, on the 2026 guide with, you know, it's about 8% growth at the midpoint on a core FFO per share basis. When you think through the key building blocks here, you know, what do you think could drive you to the high end of this guide? Sure. I mean, it's a couple of those components that we just talked about. I'd say the two that probably have the most near-term call revenue through to bottom-line impact are, one, you know, outperforming on our zero to 1 MW in interconnection business. Those signings generally have a shorter sign-to-commence lag, generally in like the one to three months, right? The more that we can outperform in that should accrue to further in-year revenue growth and as well as longer term growth, but has a near-term impact. I would say two would be outperformance on call it mark-to-market renewals, and that could be both within our zero to one as well as our greater than a megawatt category. Again, I would say we're in a favorable supply-demand dynamic where pricing continues to be in our favor. There's broad-based, you know, constraints to bringing on capacity. That should continue for an extended period of time. I would say those are probably some of the two near-term items that would be levers for us to outperform within at least the current year. Got it. That's great. I wanted to ask about the, you know, power-based occupancy. It was guided to improve 50 to 100 basis points at the end of the year. I think around 89% or so. I guess what's, you know, what's driving this transition to reporting power-based metrics, and how should investors interpret occupancy progression given the shift? Sure. Yeah. For those. I'll add a little bit more color for those who may not have heard us talk about this on the last call. For, you know, almost throughout for our history, we've reported occupancy more on what you would call more of a real estate-oriented basis, which is on square footage. If you look at a lot of the other metrics and key metrics that we report on, whether that be leasing, development capacity, like almost all of our other key metrics are power-oriented, you know, based on per kW generally metrics. We just thought it was time, given how much power is a part of the overall dynamic and the overall marketing messaging around our space to align all those things together and really make some consistency across those key metrics, which are pricing, signings, development deliveries, and therefore utilization/occupancy. That was the main impetus behind that change to create more consistency and uniformity in how we look at our business and what really drives our business. In terms of what that, you know, the relative change in occupancy, which is kind of why we've guided towards more of this relative versus absolute within our occupancy guidance, is really not any different. I mean, part of the... The other part of the reason for that change is that, you know, we've been seeing increasing densities within our space. Right? You can have the same amount of power or more power within the same amount of space. Again, in creating that consistency within those metrics is, I think is what we've talked to not only our investors about that they thought, largely would be helpful. That doesn't really. The relative change, like we guided last year toward, basically a similar 50 to 100 basis points occupancy. We were basically right in the middle of that. We're guiding to another 50 to 100 on top of that this year. That relative change is consistent whether you're measuring it based on power or square footage. Great. I wonder that shift a bit to AI inference. In the past, you've described the zero to 1 MW- plus interconnection business as the most strategic priority. You know, the last quarter set a new record in terms of bookings. So, you know, what's driving the momentum, and how do you see the segment evolving with both AI inference and, you know, edge case workloads? Yeah. I mean, we're again, to set the stage a little bit, I mean, we're seeing, we're seeing AI come into play. I mean, part of our strategy is that we, you know, we're able to satisfy a broader spectrum of workloads all the way from multi-megawatt hyperscale up to giga scale type deployments, down to single cage and cabinets through our, through our go-global portfolio. Over the last two years, we've seen, you know, we started to talk about more about kind of AI related workloads in terms of signings as a percent of our bookings. For the last two years, more of that was oriented towards our greater than a megawatt, where we saw training come into play, more, you know, early on, more prevalent. We've talked about, on average, we've seen roughly 50% of our bookings, you know, again, going back to last call, one to two years within that greater than a megawatt category be within training. And that's where we, you know, so that's where we started to see more of that workload start early. Inference, we've, you know, we've seen pick up, but I would still say we're in the early stages of that. As a comparative, you know, last year we talked about within our zero to 1 MW and interconnection, which is more that kind of retail colocation enterprise type workload, which more people associate kind of that, where that inference might land. Last year, meaning, I mean, 2024, we had maybe mid-single digits in terms of like the percentage of those bookings that were AI oriented. We, you know, we categorize that based on discussions with customers, types of chips they're deploying, the level of density they need. We did see that increase. Last year, 2025, we saw roughly 20% of those, of the bookings within that category were driven by, you know, AI, had some level of inference workload. A minority, but a growing percentage of that share. I think we'll see that continue to pick up into 2026. Still feels early from our side. You know, we're still seeing where they're looking for, you know, enterprise customers are still utilizing, you know, the large language models from the larger hyperscale and companies that are really focused on that technology. Where we're seeing more of the inferences in financial services, healthcare, some level of content. Companies that are, you know, generally speaking, look to get ahead of the curve and have the resources and the wherewithal to be able to deploy AI specifically within their stack, whether that be for their own customer and use cases or internally for trading algorithms or other needs. I think it's an early... We're in the early innings, I think, of what we see as AI inference, but we see the potential, as that continues to roll out, as we expect to see more enterprises adopt, you know, some level of what we saw and how we saw cloud roll out, you know, over its many years, where it started really with the same customer base. The hyperscalers were driving the majority of the cloud in the early days. You then had enterprises that started to adopt their own private cloud, and now you're kind of in a position where hybrid is like the preferred architecture. We see that same thing rolling out in, you know, in some level for AI, where you've got same large hyperscalers and some new companies driving, you know, the large language models, the training, which has some level of inference embedded within it. You're seeing a very small cohort of enterprises that are driving their own enterprise-level AI and inferencing. We think over time you're gonna see private AI and then some level of convergence into a hybrid AI rollout, which is why we're setting ourselves up in a portfolio that can satisfy both those large training deployments all the way down to more inference, you know, smaller inference workloads, whether that be 100 kW, you know, 800 kW, 4 MW or 50 MW. Got it. That's great. I guess with, you know, with this broadening enterprise AI adoption, how important really is latency? How often does it come up within, you know, customer conversations? How do you think you're positioned in a latency sensitive world? For, you know, where we're seeing, you know, more, you know, more clear workloads in the enterprise, and I should say that that also is we're not only seeing inference happen from enterprise-oriented customers, but, you know, the same companies, hyperscale companies that are taking hundreds of megawatts on, you know, that are training. They're also taking similar to how they did with cloud, smaller deployments within our quote zero to one segment, more in our highly connected facilities, you know, for inference related workloads. I think the theme is that latency continues to be an important factor for not only enterprise deployment of cloud and AI, but also for hyperscale deployment. They still feel that it's important to be for the most part, as close to the eyeballs as possible. Major core markets, as close to as many networks as possible so they can transact and transmit, you know, across a number of telecom providers. And also being as close to as many different customers as possible. Curating these sites and campuses that have multiple customers that they can then connect with. That all comes back to why we've been focused on creating a portfolio that is highly interconnected across 50 + major metropolitan markets, adding capabilities within our interconnection ecosystem through ServiceFabric, bringing partners onto that fabric to enable, you know, further differentiation as well as value to our end customers. 'Cause ultimately we believe whether it's for cloud workloads or AI oriented workloads that are still relatively new, especially within the inference and, but expected to grow, that we can satisfy that, and we can bring value to our customers over time. Great. Okay. On that point, you know, I wanted to touch on liquid cooling, and, you know, just curious, you know, if you could provide an update on the rollout of liquid cooling solutions both in new and existing capacities, and, you know, I guess how important is liquid cooling from a AI inference basis? Right now, I would say the majority of liquid cooling needs that we're seeing is more targeted to our newer deployments. Again, you would say most of that is probably more oriented towards training, but there's likely some level of inference happening in those deployments as well. We're seeing more liquid cooling, you know, 50 kW to 150 kW type rack levels that we can satisfy, particularly in our new sites and new developments. We're seeing some level of liquid being requested in some of our existing facilities, which we have the ability to handle and be able to retrofit for. We've done high-performance compute type deployments within our existing facility. We have the ability to do that, you know, broadly across, you know, roughly 30 markets that we have today. We've done it today in, I think, 14 of our sites. I think it helps that we've had sites that were built when water-cooled chillers were still in vogue, so we're able to tap into that. But I think also there's a level of workload today that's still able to be satisfied with air-cooled, air-cooled technologies. Particular, at least what we're seeing on the inference side, where the densities haven't quite reached that, well, at 50 kW average that we're currently seeing from a 50 kW and above training. I think even hear Equinix talk about it's in the 10 kW. That's all relatively manageable within an air-cooled environment. Got it. Okay. On sovereign AI, it seems like that has been recently highlighted as a growing theme. You know, how significant is an opportunity to capture this, the government demand globally? Yeah. You know, I think we see that again as a, as a, as a growing area, and need especially, internationally, and we've actually captured some of that, you know, today. Where we see most of that is it's typically doesn't come directly from government. They're typically working through, in some cases, a hyperscaler or an intermediary. We, you know, that's where we see most of it through a partnership that governments have with some of the even the larger hyperscale or other, or other partnerships. I think the benefit that we have is take our MIA portfolio. You know, we're in, we're in, not only are we in all the FLAP markets, but we have, a presence through the majority of the countries through within the EU. Take that through to APAC, where, you know, we have a strong foothold in Singapore. We have capacity in Tokyo and Osaka, Seoul, Australia. We have an ability to satisfy workloads at a country level, which is where, you know, you're starting to see that more sovereign level being requested. I think our ability to be able to have capacity available in multiple global markets, and the ability to partner with a number of different hyperscale as well as sovereign, whether that be cloud or sovereign AI needs, puts us in a position to be able to satisfy those demands across our global portfolio. That's great. I wanted to ask on pricing. When you think across your customer demographic, you know, how do you think about the price elasticity across the customer base? Secondly, you know, how do market rates currently look for when leases come up for renewal? Yeah, I mean, it's, you know, look, the pricing is largely a supply-demand typically equation through, you know, most of our core markets. Right now we're in a phase in a cycle where the, you know, that is the demand is high, supply is constrained, and it, we have a favorable pricing environment at the moment. You know, we've seen, you know, we've largely seen, you know, when you, when you look at it from a couple different angles, like our mark-to-markets continue to improve, so that's, we talked about this a little bit, I think, earlier in terms of last year we had a little over 6% mark-to-market on our global portfolio. That's a mix and a weighting between our zero to one, which is typically more inflationary, 3%-4% because their contracts are more two to three years in terms, so they're always usually close to market. They're escalating more at like an inflationary type rate even when they come up for renewal. Where we're seeing sort of the higher mark-to-markets is in our greater than a megawatt portfolio, which was north of 10% last year, and essentially expecting very similar type of setup, like I mentioned before, coming into 2026 in terms of the guidance that we set forth. Now I think as you know, as you look at sort of broader pricing dynamics across our global portfolio, I think you're seeing, call it spillover effects. You know, one to two years ago, you saw significant increases in pricing in Northern Virginia as an example, as that was one of the first markets that saw a very heightened level of demand versus in basically a supply constraint that happened almost overnight due to power transmission issues. Now we're starting to see that spillover, I think, into a number of our other core U.S. markets, where we're seeing mid to high single-digit type annual increases in the U.S. markets. Go over to Europe, you're seeing roughly kind of mid single-digit type increases as not quite the same heightened level of demand versus supply challenge, but still healthy demand, constrained supply. Then you move to APAC, like a market like Singapore, that's, you know, highly constrained, very competitive in terms of mark-to-market pricing, still highest set of demand, so we see really good mark-to-markets within that market in particular in APAC as well as others. Singapore, I think Singapore stands out. I would say the one other thing I'd add to that is as we look out, in particular from a mark-to-market perspective and opportunity at Digital Realty, like we see an improving mark-to-market profile as our expiring rates that we're comparing against markets start to step down in 2027 and 2028, 2029. I think that gives us, you know, kind of continued confidence in being able to have pricing power given the supply-demand dynamics and, you know, having that as a lever to support our continued bottom-line growth going forward. Definitely. Okay. On the international market theme, you've entered several new markets recently, Malaysia, Portugal, Israel, Indonesia, all in the past year. You know, can you walk us through your decision framework for a new market entry and, you know, how these markets fit the global interconnection strategy? Sure. Yeah. I would say the common themes that you've seen, and we even announced another acquisition this morning, a site, a highly connected site in Bulgaria. I think the common themes you see in the all the ones you mentioned, Indonesia and Malaysia, I think there's a couple of highlights. One, in particular, we've been looking to grow our presence in APAC. That's just as a region, finding sites capacity where we can grow there. APAC's roughly, call it 10% of our revenue today. You know, we'd like to continue to grow that region. We see, you know, we see very healthy demand dynamic, and wanna expand that as a overall portion of our overall portfolio and customer number of markets. That kind of hinges some of those new market entries. Two, continuing to build our overall connectivity platform globally. All these sites have been largely some of the more connected sites within those markets, giving us a strong, I think, solid base for not only enterprise customers, but that path to continue as AI continues to roll out throughout the globe, having those connectivity points of presence and networks, we think is gonna be very important. Third is, you know, we have expansion capacity that typically we've been able to procure as part of those acquisitions. Being able to continue to drive our enterprise zero to one signings growth, but also having potential capacity for larger scale deployments within those regions too is creating a broader connected campus ecosystem within each of those markets. Those are the kind of the key things that we look for in terms of expanding within new markets globally. That's great. Okay, I wanted to hit on power. It's growing, a growing theme that a lot of investors are interested in. You know, how does Digital think about using grid connections and utility providers versus behind-the-meter power solutions about fuel cells or turbines? You know, where do those bridging solutions fit into the general strategy? I mean, I think first and foremost, like our view, and I think, and I believe this is a broader industry view, and maybe not everybody, but from who we speak to, I think it's a general consensus, if you will, that at the end of the day, long-term utility grid power is the best primary source. That's again, from our standpoint, from customers we talk to, other in-industry participants, developers, operators. As we've seen we're, you know, the grid is. The grid hasn't necessarily kept up with the needs. You mean, ourselves as well as our customers and other developers, we're looking at ways to bring and bridge ultimately, the power capacity divide that exists today. We see that again, more as a, as a bridge versus a permanent solution. We are looking at a number of our larger markets where it makes sense because of the investment that we need to have, the regulatory approvals, the partnerships we need in order to bring, you know, in order to bring a site online that and a developer and a partner that understands and knows how to do this since it's not our core business. We do see a need to try to bridge that capacity in the near term and put us in a position to be able to continue to bring on capacity in some of these more highly constrained markets like a Northern Virginia or a Dallas in the U.S. We, as well as others, are looking at bridging capacity, whether that be gas or fuel cells, that we can bring to bear and be able to bridge and kind of rotate as power comes online to new to the next set of incremental sites. Those are things that we are looking at. None of those solutions are easy. You still gotta get, you know, it's another complexity within the overall development and procurement process. You know, it's a necessary thing given the power constraints we have in a number of markets in finding these bridging solutions to be able to bring capacity online sooner and be able to rotate that through to the next set of development sites that we have or able to bring online in those markets. Got it. You know, on that point, there have been headlines around grid operators, you know, implementing some of these stricter requirements to, you know, access the grid, for various data centers. I guess, how do you view this? Is this a headwind or because you're scaled with access, you know, more of a tailwind? I mean, I would say. I believe you're speaking more to like, there's either financial or other commitments that grids are looking to, just to maybe clarify for, you know, whether that's, you know, take-or-pay, deposits, guarantees, you know, the. There's a lot of operators out there who have and developers who've come and said, "I need this much power," and either not taken it, and that's created some of the concern, congestion. I think from Digital's standpoint, while I don't necessarily love it 'cause it's incremental potential financial commitment that we have to put up, I think because, you know, this is one of many areas where an investment grade balance sheet, I think is a strategic advantage. One, typically that means we have to. If we do have to post anything, we're able to negotiate a lower amount. If we do have to put up anything, typically we can do it at a lower cost. I think it just gives us some incremental, you know, leverage and bargaining power with major power suppliers. Probably first and foremost, because we've already been doing business with a lot of the utility providers in most of the markets throughout, in particular in the U.S., but also throughout Europe and Asia, just given that we've been in business for over 20 years. You know, we've shown that we've not only, you know, we're procuring the power that we've asked for, we're utilizing it like we've said. I think overall it's a benefit for us both from a operational perspective and already having established relationships with most of these utility providers. Two, I think ultimately, from a financial perspective, given that we're an investment grade counterparty, you know, versus some others who aren't able to put that up. Great. I'm gonna open it up to audience Q&A, think of a question. Before I do, I wanted to ask, you know, on the earnings call, you called out a minor interest expense headwind related to newly raised debt. How should we think about market appetite for raising incremental capital, just both from a credit and equity market perspective? Yeah, I mean, there's probably a couple of different angles on that one. I think one, you know, we've in essence, put to bed the headwind that we talked about. I mean, it's still a headwind, but we had done that refinancing in late November, early December in terms of Eurobonds that we had coming maturing in January, so we got ahead of that. Granted, still a headwind from an overall bottom line because we're taking out 2% debt and essentially refinancing it at, you know, a little over... Basically right around 4%. That's in our guidance, already taken care of, so kind of check that one off the list, at least for 2026. I would say, in addition, you know, this is another, I would say, advantage of being a public company. We have access to multiple pockets of capital, both, you know, public bonds, hybrid securities, you know, asset-level financing. And you know, we have great leverage relationships with a number of banks, you know, in our bank group to help support us. And so I think that's an advantage, I think, of being in the public sphere, versus some of our maybe private competitors who are, in essence, probably overly reliant on asset-level type financing and therefore even more diligent, if you will, on the type of customer and credit quality that they're able to finance in this environment where we have potentially a little bit more flexibility. Don't get me wrong. That's not to mean we're very conscious about our, the quality of customers we have. When you look at our top 20 customers, the majority of those are high credit quality customers. I think it gives us. It really goes back to that we have a broader diversity of customer base and ability to finance across different types of products. Great. Okay, we have a couple minutes left if there's any audience Q&A. Don't be shy. If not, I did want to ask about, you know, hyperscalers. If they, you know, you think about this year, they've announced these massive CapEx plans, which creates some worry maybe around, you know, bottlenecks on power construction equipment. How do you manage supply chain risk and, you know, what does elevated hyperscaler CapEx mean for pricing power? You know, I think, I think first, like, when you probably something to note, like, when you look at the, you know, what is almost half or more than half, like, what is it, $600 billion-ish area, well over half a trillion, which is crazy when you say it out loud, that hyperscalers are spending. Not all of that is going into building data centers. Actually, a good majority of that is actually going into the CPUs, GPUs, servers, and equipment that are actually gonna move into a data center. I think it's important to kind of distinguish, you know, what level. Figuring out how much is in each category, that's a little bit of more art than science, but I think it's good to keep that in mind. You know, from a Digital Realty standpoint, in terms of what that means, you know, that just means. I don't think it's any different really from how we've approached it historically, meaning we've lived through the pandemic. We've seen long lead equipment lead times elongate. We've gotten ahead of that. You know, for a number of years, that's really not gotten any better, so we've been on top of it for a long time. We look ahead in terms of what we need to procure given the megawatts that we expect to deliver, working with our partners to strengthen that, those supply chains. That's something we've been doing for a number of years, something we'll continue to do as we deliver even more and more megawatts into our operating portfolio. Has that... I'm not sure if this is exactly where you're going with the pricing part, but I would say we have seen, you know, increases in the cost of that long lead equipment over the last couple years, but we've also seen a corresponding increase in the pricing that we're able to achieve on that deployed cap or related to the deployment of that capital and keeping and/or improving the overall yields that we're getting on our development pipeline. Great. We are at time. Matt, thank you so much. Yeah, appreciate it. Thank you. Hopefully that one was fine. Great. All right. Good to see you. Thanks. Thanks again. Appreciate it.