Daniel Roberts
Analyst · B. Riley Securities. You may proceed
Thanks, Kent. So that talked about AI Cloud. Now I'm going to talk a little bit about the infrastructure and the colocation opportunity, specifically behind that. So what we are showing on this slide is the fundamental, I guess, why behind our pursuit and our focus of AI infrastructure. So I think it's clear that the demand profile for AI compute is unlike anything that we've seen before across broader infrastructure. And I don't think it's exactly speculative anymore, particularly given what we are seeing in the market. And what we are seeing is this shift is happening fast and it's really becoming at scale. And what we are seeing is the markets are simply not ready to serve it. So I'll come on to that a little bit more. But if we look at the left-hand side, forecast global AI users, starting with the demand side, it's projected to triple from $346 million to over $950 million in the next five years. And this growth is not driven just by consumers like it's all on ChatGPT, but also by enterprises embedding LLMs and other AI tools into everyday use. And everything from medical imaging to call centers to software development, the expansion of this user base ultimately leads directly to compute growth. And as we see inference workloads scale in production environments, they require persistent infrastructure, not just burst compute for trading, which what brings us to what's on the right-hand side of the slide. So here, we show that user growth translates to global AI data center demand expected to grow 3.5x in the next five years. So that sounds like a big number, but what's even bigger if you understand energy market and the scale of what this really represents in terms of real-world infrastructure, 44 gigawatts today to 156 gigawatts in 2030. So that's more than 100 gigawatts of new infrastructure required globally and today's traditional data center players simply aren't set up to deliver that at the required scale, speed or density. So our 2.9 gigawatts that we've secured that we've worked really hard over the last six years to secure, it's a big number. We all know it's a really, really big number. But in the context of 100 gigawatts, it's still small. So it sets us up for a really interesting few years ahead. So meeting this demand requires a fundamentally new class of infrastructure. So new designs, rack densities for AI have jumped 225% year-on-year and continue to look like they are going to climb. Traditional data center designs simply do not work anymore. They are faster construction cycles. So customers want sites built in nine to 12 months, not two to three years. So that's really forcing a rethink of how infrastructure is designed and delivered in this sector. And we are seeing scale. The industry is now talking about 50 to 1,000 megawatt clusters with customers asking for 250 megawatts or more across multiyear rollouts. All of this is happening in live time and the scale and the intensity just continues to climb month-on-month. So grid connectivity, this is really a gating factor. A greenfield hyperscale site can take up to five to seven years just to secure that transmission access and energization. So that is the critical bottleneck. And it's where we clearly believe IREN has a competitive advantage along with a few other points, which we'll get to. So we are clearly well positioned to meet this demand. We've got 2.9 megawatts of secured power capacity already contracted, including those large-scale grid connections at Childress and Sweetwater. We own our own land, which means we are not reliant on M&A. We are not reliant on third-party developers, and we can move quickly when customer demand materializes and is contracted and importantly, retain the upside on the infrastructure development. So I guess my message here is the demand is real. It's growing more and more real week-by-week, and it's infrastructure constrained. We've got the land, we've got the power. And importantly, we've got the engineering and the execution capabilities to capture a good share of this growth, and we are making it happen right now. So if we zoom out briefly and look at how we are positioned to address one of these biggest barriers to adoption. So it's not just about the GPUs, it's about the ability to deploy those GPUs with power, cooling, permitting and speed, and that's where most of the market is getting stuck today. So we've spent years assembling the fundamental and foundational ingredients for this. We've secured those large-scale sites that I mentioned. They are very quickly becoming strategic emerging AI hubs, particularly in West Texas. We've got a track record in high-density data center delivery going back to 2018. This is not our first rodeo. We have been doing power dense data centers for seven years. Those of you who have followed us for that time understand that, yes, we had origins and our roots in Bitcoin mining, but we never went down the path of CCANS, old abandon warehouses, shipping containers, we built multifunctional data centers from day one. And a testament to that, again, I'll repeat it, in Prince George, in the same data center we originally built. We have Bitcoin mining racks operating right next to latest generation NVIDIA GPUs servicing AI customers, the exact same data centers. So this experience in engineering, designing, deploying and then operating power dense data centers is what our business was set up to do, and it's part of our foundation, and we are continuing to do it. The only difference is we are continuing to iterate on that power dense design to service these future workloads. So that in-house development and procurement team is critical. It gives us a direct control over the project pacing. It reduces reliance on third parties. We don't need to sign big contracts with third parties and outsource all of this. It derisks those execution time lines. But critically, we still work with Tier 1 engineering, Tier 1 OEM, Tier 1 EPCM partners where it makes sense, and they are already engaged on Horizon and the Sweetwater projects. So all of this is what allows us to move with certainty, compress time lines and meet the most demanding specs, whether it's 200-kilowatt racks, whether it's liquid cooling or multi-hundred megawatt campuses. And today, we've got 2.9 gigawatts of aggregate power capacity across those sites to service it. So I guess my message here is simple. We are not just a site developer. We haven't just signed simply options on land and gotten lucky around this power. We are a builder, we are an operator. We've been doing this for seven years. We've structured the company to scale infrastructure in the power dense HPC space simply as fast as customers can commit. So while the demand is clearly global supply is constrained, and we've got the power, we've got the partners, we've got the execution track record to meet that demand at scale. So the next major milestone in our infrastructure rollout is Horizon 1, 50 megawatts of liquid-cooled AI data centers in Childress, which is currently under development and due for delivery in quarter four this year. So as we've mentioned, there is a growing scarcity of sites capable of supporting liquid-cooled GPUs at scale. So this is specifically designed to cater to NVIDIA's Blackwell platform, but also beyond with rack density of 200 kilowatts per rack. So this aligns with the next generation of model training and customer interest has well exceeded the initial 50-megawatt data center. We've got multiple customers actively engaged in due diligence, actively engaged in commercial negotiations. So it is clear that there is a clear gap in the market, and we are looking to fill it. So in terms of the specs, just to recap, it's 50 megawatts approximately of IT load for Phase 1. We are designing it for 200 kilowatts of rack density. And to put that in perspective, that's compared to only 130 kilowatts for the new generation Blackwells that have been released over the course of this year. We've got full UPS and diesel backup systems, sub-six millisecond round trip latency to Dallas, which supports both AI training along with latency-sensitive inference workloads. And finally, forecast CapEx unchanged, $6 million to $7 million per megawatt of IT load, which we continue to gain conviction is very competitive for liquid-cooled data center deployments in the current market. So clearly, securing an anchor customer for Horizon 1 is a top priority. It catalyzes our formal entry into the AI data center colocation market and importantly, builds confidence for the broader site development opportunity across the full 750 megawatts available at Childress. It also further differentiates us in the market as we prepare to bring Sweetwater online in April 2026 and the 1.4 gigawatts immediately available at that point. In terms of financing, we are actively exploring pathways that optimize for capital efficiency. So that includes customer prepayments, project level debt, corporate level debt, equipment leasing and convertibles. So we are also open to joint ventures, particularly with infrastructure capital providers as long as they are aligned with our long-term control strategy. So in terms of milestones, the project is progressing along a well-defined delivery schedule. It's on track. So we are looking to start earthworks and grading in the coming weeks. In the third quarter, we will start preparing structure, cooling and the electrical system. And then in Q4, we expect final delivery and readiness for occupancy. So long lead items already ordered. Procurement team is very active. We remain on track to deliver Horizon 1 on the original schedule that we outlined. So Horizon 1 is our first at-scale AI data center. And it's also the model for how we can potentially develop and scale across our broader platform, including Sweetwater. So we've locked it all in. Now it's a matter of executing over the coming months. So this slide brings the focus back to the 750 megawatts at Childress and our road map for potentially transforming this entire site into a world-class liquid-cooled AI campus. So three main things to take away. Firstly, customer interest, as I mentioned, already exceeds the Horizon 1's initial 50-megawatt capacity. This just validates and reinforces our decision to invest ahead of the curve and make the commitment to build out this capacity and also reinforces why we've already begun work on expanding capacity across the broader campus. Site design is now underway for a full 750-megawatt transformation. So this is not just additional racks. It's a complete reconfiguration of the site for liquid-cooled AI workloads, associated upgrades to power redundancy, cooling infrastructure, network architecture. Thirdly, we are future-proofing. As I mentioned before, 200-kilowatt rack densities as compared to the 130 kilowatts required for Blackwells, well above what we are expected to require for the next generation, setting us apart from traditional data centers even further that are really struggling to handle this basic level of density. So I think the quote here captures the design philosophy. So the project is not being engineered just for what we need now and what we need over the next six to 12 months, both based on the road map we are seeing on the GPU side, but what we think AI will demand next. So we are not just catching up. We are building ahead of the curve, and this is a real step change in capability and what we are offering the market. Top right, you can see a real photo of the Childress site as of April, clearly very active nearing completion of multiple newbuildings. And below that is a rendering of the 750-megawatt horizon concept, illustrating how the site might be evolved to accommodate 750 megawatts of liquid cooling, high rack density and AI-specific workloads. So in context, we own the land, we own the substation and the infrastructure. We are building to rack level specifications required by future workloads, not just what fits today, and it positions us, Horizon and Childress to be one of the few potential large-scale liquid-cooled AI campuses in North America. So this is a blueprint, not just for Childress, but also for Sweetwater and how we can potentially scale our broader platform to meet this rising demand. So Sweetwater is our flagship AI site, which we've mentioned for the last year or so now. And it's a very rare combination of secured land, grid scale power and site readiness that is well in motion. So to recap some of the fundamentals, 1,800 acres with up to 2 gigawatts of high-voltage power capacity already secured through binding contractual agreements. That's enough capacity to support over 700,000 next-generation GPUs, including those liquid-cooled Blackwell GB200s. Substation site level civil works are already well underway. So we are not waiting on paperwork. We are not waiting on anything else. We are actively building this at the moment and preparing the site for construction. So it does feel like we might be entering a super cycle of AI infrastructure build-out, particularly when you look at these forecasts of 125 gigawatts, not megawatts of AI data center capacity over the next five years, over $5 trillion of capital, compute, energy, land, cooling, networking. And this is where Sweetwater stands out. Most of that demand is bottlenecked by land use, zoning, grid connection, politics. And at Sweetwater, we've solved for those constraints. So the site has the potential to support up to $70 billion in end-user AI infrastructure investment, $70 billion. That's the development site that we've been actively incubating and are preparing. So the initial energization is targeted for April next year, all long lead substation equipment on order. The looped fiber connection between Sweetwater 1 of 1.4 gigawatts and Sweetwater 2 of 600 megawatts is already designed and the flexibility to scale in 100 to 500-megawatt increments gives us a lot of agility to align CapEx with customer commitments and the discussions that we are having. So there are very few sites in North America or even globally with this unique combination of scale, power, land, control and readiness. We own the land, we've secured the interconnect, and we've started the site readiness. We believe Sweetwater is one of the most advanced and actionable AI clampests in development today. So with Horizon leading our first delivery and Sweetwater anchoring our medium-term growth pipeline, we really believe we are well positioned to meet this market momentum in AI. Over to Kent now to touch on CapEx and funding.