Brookfield Infrastructure Partners L.P. (BIPC) Earnings Call Transcript & Summary

Thanks, Katie, and thank you for having me and thanks this room for the capital and the investment in the deployment company. We're excited to be here. So your question was about enterprise adoption. It's really interesting. When you look at it -- on the frontier, the capability of the models is really increasing exponentially and accelerating. But when you look at adoption and impact in the enterprise, in most legacy businesses, that curve lags. You don't see that lag with digital native companies and start-ups in many cases because they don't have the legacy systems and data infrastructure and policy and procedure gaps that exist in the legacy business, it's embracing new technology. And so where we see the problem and where in part the deployment company was formed to help address and solve and bring companies that are kind of behind that frontier curve onto the frontiers so they get the benefit of frontier model evolution is to effectively solve 3 things. The first is to stitch together legacy systems and that data into a really rich context layer that allows the model within their harness to sit within an organization. The second thing that we try to do is teach the technology leaders and the business leaders in an organization how to embrace the technology. It's both use of the products and the harnesses themselves, but then also how to think about context, permissions, compliance, use case definition and deployment -- and if we're doing our job right with the legacy business, you'll see them embrace the technology, deploy both our models and their harnesses and then in partnership with the deployment company and their internal teams start to roll out use cases that bring them up the curve. So you see it in digital natives and startups. They don't have the same amount of tech debt that you see in the legacy business, but you also see it in industry leaders that are willing to embrace change and innovative. Like we have really good examples in Life Sciences in infrastructure, in energy and in financial services of organizations that understand that if you give this frontier technology the right context to the right access and just deploy it against the right problems, you could start seeing very rapid and revolutionary change.

And before we get a little bit more into actually the deployed co platform, Dave, with your operator hat on, maybe just tell us a bit about how this resonates when you look across Brookfield.

Yes, absolutely. So I would think about it probably in 2 or 3 categories. But I think there's 1 overarching element to it as well. And Howard touched on this, like this -- we feel this is a pretty revolutionary technology, and it's going to change how global economies work and how people live. But what comes with that is like it's new, it can be scary for people. In some ways, it's intuitive, but it's also actually as the models get better, they get more complex. So there's 3 things that we've seen in our portfolio that I think really matter. It's about leadership, prioritization and then the actual operational know-how to get it done. And so when I think about leadership, even at Brookfield, Bruce is an advocate for deploying AI to create value, a news. All the platform leaders are advocates for it. And then going into the portfolio companies, like we don't successfully deploy it if it's like an IT technology-driven AI for AI's sake. It has to be driven by leadership. So I think it's the first piece. The second piece is maybe more around the value creation side, like you can't do 50 things across the company. Like you have to start with 2 or 3 prioritized areas, and they have to align with like what are the actual priorities of the business. If it's -- so it has to be meaningful, it should align with how can you actually really create value. And so our business is doing it successfully have a really good prioritization framework. And then the last thing I'd say like this is messy and complex, right? So I think the what we're seeing is the technology capability is here, the ability to execute is here. And so this is, I think, where Brookfield strengths play into it, where when you think about getting into a business, getting into the manufacturing plants in the headquarters, like understanding processes, understanding where the data is, the systems, that's what actually separates deployment, which I think really kind of resonated when we were talking to open AI about their thesis for DeployCo, it really aligned with it nicely.

And so Nate, let's jump a little bit into deploy co itself. Why did OpenAI feel like this was the right model to address these challenges. And maybe elaborate on what Dave mentioned just with respect to what Brookfield actually brings to the table.

Yes, I'm happy to. So opening -- it was founded both as a research and a deployment company. It's in the mission for the business. Our job is both to push the frontier from a research perspective, but then also deliver the technology to all of humanity -- and that is both at an individual level and at an enterprise level. When we thought about deployment, this really had to be an ecosystem play. We were building an army of entities and people that could deliver the technology to the world. That was not just open AI, that was not internal researchers and applied researchers and forward deployed engineers that existed in the business. It really needed to be a collection of people some of which sit in deploy co, but then also an ecosystem that we can enable. And so when we thought about this, we wanted to build a purpose-built entity that was focused on elite forward-leaning enterprise deployment and it brought along private capital and operators that controlled thousands of businesses that could be a sandbox for us to think about deployment. It was going to be consulting firms, and it was going to be -- if you look at it, the cloud practices inside of a Capgemini or an Accenture or any of the GSI businesses, those are tens, if not multiple tens of thousands of people that understand how to do this. For a technology that's a little bit more static and less dynamic than AI. And so when we thought about the deployment company, it was let's build a purpose-built entity who has and trains the leading forward deployed engineers, they're going to be hands on keyboard inside of a business, driving, teaching and enabling change. We were also going to teach our partners in the forms of private equity investors and our alliance partners how to do that work. When I think about Brookfield -- to me, it's pretty obvious. And it was funny, I was talking to Bruce about this when we were saying beforehand, I met Bruce actually at a sovereign energy company. He and I were halfway around the world and he was talking about infrastructure and capital and being an operator and transforming in that regard. I was talking about AI transformation. It was very clear that there was a residence in thought. Interest me to David. And to me, within about 5 minutes of talking to somebody, you can really understand have they understood the technology, are they working in it? Or are they thinking about it? And it was very clear to me even in those first conversations that Brookfield was already forward-leaning and action-oriented when it came to AI transformation. I think the second reason is doing this work is hard. It's messy. It's much more akin to open heart surgery than it is going in and doing something quickly. We built the technology and the model still surprise us more often than even you might think. So we had to find partners that had control investments in businesses that would allow us to get in and figure it out together. That was the second thing. The third is just a horizontal slice of the world economy. When you look at Brookfield, there's infrastructure, there's power, there's energy, there's real operating businesses inside of PE and there are services we wanted a chance to work with each of those different vectors of companies with a partner that was going to let us get in there, figure it out, give us access to subject matter experts that would be able to teach our engineers about the business, so we could teach them and partner with them on deployment. And with Brookfield, we found all 3 of those things.

And Dave, maybe just to elaborate on that within -- when we think about BBUC, what does the partnership with OpenAI enable within our business that would have maybe been more challenging had we gone about this on a more fragmented kind of business-by-business approach.

Yes, absolutely. So I think the value we saw is we could marry what we were already doing, which is a thoughtful, organized approach. We track use cases, we track value. We track how we're actually driving it. and that kind of more hands-on operator approach that we deploy. But coupling that and learning from a company that is pushing the frontier and is also actually thinking about what is important in the context of deployment, not just creating better models. And so being able to couple that and understanding not just what's happening 6 months from now or 12 months from now, but to understand have a little bit more of a forward-looking view and a seat at the table with the likes of open AI, we think that could accelerate what we're already doing. And I'd say we're already seeing some of that because what may have been a use case that we scrapped a year ago or 1.5 years ago, is now we can come back to the table because we're getting a look at where the models are actually going, where the product capability is actually going -- and I think that's something that would be -- would have been difficult to replicate without the partnership.

So let's talk about those deployments themselves. And Nate, maybe you can just fill us in a little bit on what actually separates a successful deployment or rollout of this AI versus what would be an unsuccessful deployment in your view?

Yes, I'm happy to. And it's something I spend a lot of time on. Now that we've done the deployment company, it's about, to me, finding the right companies and the right lighthouses by industry to really demonstrate adoption, transformation and change. To me, very simply, it starts at the top, whether it is an investor they have to be fully bought in to doing this because it's going to be hard. Like transformation in many cases, and David said it, it is revolutionary. And like this is not a small twist the dial here, change in workflow. In many cases, you're re-architecting how a business operates to enable a capability that was previously impossible to consider. So it starts at the top is the first thing. The second thing, when you have that top like alignment at the top, you want to find both a business owner for the first deployment and use case inside the business and a technology team that is willing to embrace change. They have to feel a little bit like cowboys, like I've never told David this, but like David to me was the Coway of Brookfield. Like I talked to David, he was like, no, no, no, like we're going to do this, like we're going to go adopt it. And when you have those 2 things, -- it actually matters then less kind of what company you start with. It's much more about problem selection, finding a problem that you feel like you can drive value with using AI and demonstrate the power of the technology in kind of a short to middle term, -- and if you do those 3 things right, 1 use case becomes a business transformation side of a company becomes a whole company transformation. And when you're working with an investor -- all it takes are a couple of those transformations inside of the portfolio, and it spreads like wildfire across the entire ecosystem. And so I mean, David, you should talk about it, like Clarios to me is a really good example of getting into the business understanding and messy a couple of problems, really getting the technology in there. And then you see this like snowball effect and kind of stone rolling propagation of use cases across the business.

Yes, absolutely. I think I'll take a step back first and then I can get into Clarios a little bit. I think when we started approaching deploying AI across Brookfield about 2 years ago, -- we also wanted to come at it with like an operator's lens to it. And I said it before, like not just AI or technology for technology's sake, like we had to think about it like capital allocators, and that's why we called it AI Value Creation Office to begin with. So we had to have an operating system in terms of identifying use cases. And so in private equity, we have about 500 use cases but then it's not just about use cases. We track a funnel around like what's the use case, what's a business case, what's in pilot, what's in production -- so in private equity, we have about 150 use cases in pilot or production that we estimate will drive $100 million or more of EBITDA. And frankly, I think that number could be larger in the future. And so we -- what we try to do to make this successful is bringing an operating model to it, not just doing it everywhere all at once. So that's kind of the foundational piece. I think going to Clarios. Clarios is unique because it's a big business. It has forward-thinking leadership around technology and innovation. So both the CEO and then the head of digital and AI in the business, like you have top-down leadership to say hey, we are a great business today, but we can be better, and we can do things differently. And then a key thing at Clarios, I mentioned like you need to define what are the priorities of the business, even like putting AI aside, what is important to the business -- and so there's 2 areas in Clarios we've been focused on the last several years. One was around on-time delivery and 1 was around OEE and productivity in our plants. And so for example, on on-time delivery, it was sitting in the high 70s, low 80s, and that was because we had a static manual process on a monthly basis where we were -- and it's typically a typical problem in industrial companies. So like how do you match demand with where your inventory is, where your operations are. And so we have this static manual process that with AI, we've now been able to make that more real-time dynamic and is kind of always running and the decision-making is not something they dust the spreadsheet off at the end of the month. And so as a result of that, our on-time delivery is now in the mid- to high 90s. And that actually resulted in about $50 million of EBITDA improvements, both in reduced freight costs, but also a reduction of service penalties with customers. So that's 1 example. And then another example, and this is actually a real-time thing that we're doing with the deployment company is we have -- we have a network of a lot of manufacturing plants under invested in prior to our ownership. And so portions of our network are at less than optimal productivity levels. And so -- and if we can get 5 points of OEE 10 points of OE, there's a 9-figure EBITDA opportunity. And so we're working on a real time -- there's actually a component of video and a component of leveraging the traditional generative AI models to think about real-time monitoring of quality issues and maintenance issues in real time to basically assess areas where we could have downtime and a loss of productivity well in advance of our traditional methods. And again, that's the type of thing where 2, 3 years ago, that type of problem even with advancements around industrial kind of robotics, we not was a really hard problem that we now think we can unlock with AI and with the deployment company.

And so Clarios is obviously a really good example of this, and you mentioned some of the kind of tangible, measurable outcomes there. We have a lot of investors in the room here today, elaborate a little bit on what some of those proof points are KPIs that everyone in this room should be thinking about as we see this roll out over the next 1, 2, 3 years?

For sure. Yes, we try to make it tangible. So actually, in our program and our operating model around tracking use cases, if something is in pilot or production, it has to have a we measure revenue opportunity. We measure a cost improvement opportunity or we measure like some type of productivity or efficiency metric. So we -- if something doesn't have that, well, then it shouldn't actually get approval to proceed as a use case, and it should fall out. So that's the type of things that we look at. And I would say, generally, my ambition is like -- we have a pretty systematic way to think about value creation now and Anuj talked a little bit about that capability. My view is in 2 to 3 years from now, -- and we basically have like the 7 critical levers that we look at every company against, like I believe that AI can enable all of them for us to go faster and potentially have bigger impact -- and so that's kind of how we're thinking about it. And I think within that is how do we also create repeatable frameworks and playbooks. And I think this is also the benefit of like the Brookfield scale where we have now visibility to what's happening across AI deployments across all of Brookfield, and we can figure out what worked in 1 company that may be transferable to another company. And given we do own a lot of comparable adjacent assets. There's a lot of ecosystem effect that I think we should be able to unlock in the next 2 to 3 years.

Perfect. And we just have a minute or 2 left night. I want to give you the final thought here and maybe we can just zoom out and think about the potential of what this could the cut and what this could look like as it continues to scale in the future?

Yes. I think when you think about the impact of this technology, you kind of need to think about it in almost 3 time tables -- the first is that decade-long time table, where we will be solving OpenAI, a deployment company, Brookfield and our partners, the most ambitious problems that exist in the industry today. and we will be solving problems that we haven't even thought or possible to address in those next 10 years. And if you're working towards that 10-year outcome, you're going to build the business and operate in a certain way. When I think about 2 to 3 years from now, my hope is by industry, we've created lighthouses that are really aspirational changes, reduction in incidents on industrial sites. More efficient optimization of energy problems or industrial problems or development problems. You saw this with Halpen, the chip that we did, but it's an analogous problem where you can take out a chip incredibly quickly because you can do closed-loop optimization on design or optimization decisions in a industrial or computer manufacturing context. So to me, the 2- or 3-year time line, it's about creating those lighthouses to show the world the power of this technology when it's deployed deep within the enterprise. And in the heart now, to me, it's about 2 things. One, we have to deploy the models and the harnesses more effectively in the organization. Going back to my first point, like this is about embedding the models inside the business, giving them appropriate context and allowing people to learn how to use them and work -- and if we're successful in the next couple of years in really deploying this technology across a wide range of both companies and industries. To me, the world is just going to see incredible evolution and productivity gains from.

Awesome. I think that's an excellent point to end on. Nate, thank you for being here with us. I know I speak for everyone in the room and I say we're excited to see how this evolves and the value that can be created for BBUC and across Brookfield more broadly. With that, I'm going to welcome Jess Gedale, CFO of the Private Equity Group to the stage. Please welcome Chief Financial Officer of Brookfield Business Corporation, Jaspreet Dale.

Good afternoon, everyone. Thank you for joining us today. I'm going to focus on 3 things. First, talk about the evolution of over the last 10 years, BBUC. I'm probably going to do this a few times. The second thing I'm going to talk about is why we believe we're better positioned today than we've ever been before. And finally, I'm going to talk about what the future holds for us. But before we talk about the future, I want to revisit some of the objectives that we set for ourselves last year during Investor Day. So we had a few things that we laid out that we were looking to accomplish. On capital recycling, we talked about generating $2 billion of proceeds over a 24-month period. And I'm happy to report that we're well on our way in accomplishing that. Over the last 12 months, we've generated $1.4 billion from monetizations and distributions up to BBUC. Earlier this year, we completed our corporate simplification merging our units and shares into 1 corporation. And as a result of that, our trading liquidity has increased about 75% and which is above the 50% that we expected. And finally, we have an active buyback program. We returned $175 million to shareholders and we bought these shares back at very accretive zuffles. And these achievements built on a much longer track record, which has allowed us to grow and scale our business. The result is that we have a much larger business, but also a materially better and stronger business. To put some numbers around it, -- when we were spun out of AM in 2016, the business was generating about $200 million of EBITDA. That has now grown to $2.4 billion. Over the same time period, our EBITDA margins have improved by 2,000 basis points, and EFO per share has increased from $1.50 to $5.50 and that strong operating performance has translated into significant growth in intrinsic value. NAV per share increased from $17 to $56 today up about threefold over the last 10 years. And this growth in intrinsic value has been driven by a simple repeatable formula. We look to invest for value -- we want to improve the businesses that we buy, and we want to recycle the capital to continue to compound. So if we think about those 3 things, -- over the last 10 years, we've invested $10 billion of capital across 40 investments. And we've been disciplined in making these investments. The average EBITDA multiple that we've invested is at less than 10x. And we've been buying market-leading operations -- and this deployment has been supported by our capital recycling engine, which has continued to build momentum over the last number of years. Over the last 10 years, we've generated $12 billion of proceeds, $3 billion through distributions, which continue to grow every year and $9 billion through the monetization of assets generating a 19% IRR and a 2x multiple of capital. And we've never been dependent on these monetizations on 1 particular channel. About 60% of the sales that we've made have been to strategic investors, 30% to financial sponsors and 10% through public markets. And this diversification is really important because it means that you can continue to monetize in any market cycle. And this recycling engine has also allowed us to change what our business looks like. We've sold substantially all of the businesses that we had on our balance sheet when we were spun out from Brookfield. They were generally smaller, lower-margin businesses. On average, those businesses generated $60 million of EBITDA and a 15% margin. We took our capital and redeployed it into larger scale market-leading operations. On average, these operations generate $300 million of EBITDA, 5x higher than our original portfolio. And the EBITDA margin is double at 30%. So we've not simply made BBUC larger, but we've made it more profitable and of a better quality. We've also made BBUC simpler through the corporate simplification that we completed earlier this year as well as -- which resulted in a higher index inclusion as well as better liquidity. And we continue to simplify how investors understand and value our business. Starting the first quarter of 2027, we're going to be transitioning to U.S. GAAP. And as part that transition, based on investor feedback, we're going to be providing quarterly valuation disclosures in our financial statements. So as we look forward, we believe we're very well positioned for the next phase of growth. We've built a larger, higher-quality and simpler business. But much of the growth in the future is going to be driven by the operations that we own today. To put that into context, and Anuj alluded to this earlier, -- we think about our businesses in 3 stages. There's the early-stage businesses. Typically, investments we've just made, we're starting down the value creation path mid-stage businesses, which we've owned for a few years, and we continue to build value. And finally, our mature businesses that are well along the value creation and are approaching monetization. So when we think about our business today, about 80% of our NAV is working through the value creation plans that we have. While 20% of the NAV of the business is in more mature businesses that are ready for monetization. So while we still have a meaningful amount of operational improvement and growth, we also have a strong pipeline of operations and investments that we can -- that are ready for monetization. So to put some numbers around that, we plan over the next 5 years to generate over $6 billion through these monetization -- about half of that $6 billion is going to come to the monetization of the mature businesses. The other half is going to come from distributions that we get from our operations as well as the mid-stage businesses progressing their value creation and being ready to monetize. So we're going to have $6 billion. What do we plan to do with that? We've got a plan to invest $4 billion of it alongside Brookfield's private equity strategies. And our investment criteria is unchanged. We're looking for market-leading businesses that are providers of essential products and services with high barriers to entry and durable cash flows. The most important thing is that we're going to fund this $4 billion of investments that we're going to make over the next 5 years from our existing operations. And we're going to have $2 billion left over. And we're going to use that $2 billion to strengthen our corporate liquidity, maybe make some strategic investments that will continue the growth of BBUC, and we're going to continue to return capital to shareholders. And we've already demonstrated that flexibility around capital allocation. Since the start of 2025, we've returned about $335 million to shareholders by buying back about $12 million -- 12 million shares at about a 50% discount to our NAV. And that intrinsic value or NAV is underscored by our ability to monetize our assets. Anuj talked about the fact that over the last 10 years, we've been able to monetize assets at about a 12% premium. And last year was no different. Over the last 12 months, -- we've sold 3 assets, generated $1 billion and we sold these assets at a 20% premium to where our NAV was disclosed. And this track record highlights the enormous opportunity that's in front of us. Today, BBUC is trading at $25 our largest and most profitable business, Clarios represents about $19 of value. So what that means is that for $6, you get the entire rest of the portfolio a portfolio of 20 market-leading businesses. Anuj talked about some of our industrial businesses, Kemelix, Deco, Poser. In addition, we've got large-scale services businesses like Sage, Lytro, Nielsen and all of that portfolio today is trading at an implied price of $6 per share. And from our perspective, that represents a very compelling value. There continues to be a significant gap between trading price and NAV intrinsic value. And we think there are several reasons that this gap should narrow. First, our realized track record has consistently validated securing value that underpins the NAV. Second, we expect to generate more than $6 billion over the next 5 years which will convert a meaningful amount of that value to cash. Third, it allows us to self-fund our growth and leave $2 billion available for other capital allocation. And finally, our corporate simplification and conversion to U.S. GAAP will make BBUC easier to understand and value. So if I bring that all back together, what do we want to leave you with today. First, BBUC is larger, higher quality and a simpler business. We still have a significant amount of value creation ahead of us and capital recycling is going to continue to build momentum. And finally, we remain focused on compounding intrinsic value and narrowing the gap between our share price and the value within the business. Thanks. I'll now bring a new back up for Q&A.

Thank you, everyone. So we'll now take some questions. We are over time. So I'll just take a couple of questions. And again, anyone who spoke is still here in case some of the questions are directed their way. I'll start here. Sorry.

Going back to the earlier discussion that Bruce and Howard had about interest rates, there's eggs in the market today around the rising rates and their impact on private equity. So just curious from your vantage points, how are you thinking about the impact on deployment, monetization -- and could you unpack a bit about the 20% of mature portfolio that you expect to monetize? What companies are in there?

Sure. So I think they said it well that actually we don't think this interest rate environment is so crazy in the long term. We've always built our business and pride ourselves on buying companies that could woodstand the test at times. We've always underwritten higher inflation, higher interest rate environments. The problem before was the rest of the world was when interest rates were 0, it made us sometimes uncompetitive. The great thing today is we actually are finding an ability to buy the kinds of businesses we like at good value. Because people can't bank on low interest rates or an environment that is easy to make money like they could in the past. So we've been busier than normal as you can see on the retentiveness we've made and the pipeline is looking quite healthy as well. So for us, this is actually a good opportunity and a good time to put more money to work. In terms of monetizations, as Jaspreet showed, we did 3 in the last year at a 20% premium to NAV. Even in this kind of a market environment, and so that mature portfolio. There are a few companies in there that we are at a stage where we're probably ready to start exploring all terms of the ones that we've owned a bit longer in the portfolio, I'd say things like well, literal, we sold a bit of already. It's quite mature in terms of our journey, maybe within a little while that 1 might be 1 or BRK or some of these other business have been in the portfolio a long time. And I think that given our track record on the last 12 months, I'm not expecting any surprises there.

Yes. Bill Kass from TD Cowen. So 2-part question. If I looked at your NAV calculation, it's only up 3.7% year-on-year, and I'm really happy to hear you're going to move to quarterly -- when you think about the flight path mirror and open AI discussion, et cetera, into Poco, what's the ramp look like to accelerate the NAV improvement? And then secondarily, related to that, -- how we think about capital allocation? You laid out 3 different paths. Where are you in terms of buyback, given that wide discount to the NAV and the stock price?

Yes. So our -- I'll start with the last question first. I'd say our buyback program has still been quite active. And that's just given where we're trading today. We are still putting new money to work. And of course, we, from time to time, look at our leverage, all those are the 3 areas that we're most focused on. In terms of NAV, I'd say with some puts and takes over the last year, there are some businesses that have -- we've got that we're working on and that we've got some challenges in the portfolio, and there's no secret around that. Where we have adjusted NAV downwards. And that has been offset by some of the other businesses that have been performing quite well, like Clarios, where it's been lifted up. And so on balance, it was a year that NAV didn't increase that much. I do think, though, where we are today based on where we are in every portfolio company, it's a different journey, and it's had a different phase of its cycle. But in many of the companies where there have been challenges through the pandemic and after. We're seeing real green shoots, and we're seeing real positive momentum. And that's before any application or any opportunity that comes from AI, which is more upside beyond the operating plans that we already have in place. So I would believe that it would accelerate further in the coming years.

Gary Ho from Dagan Canfor Markets. So Nate and David kind of talked about how deploy is benefiting some of your existing portfolio companies. Are you adding AI efficiency gains in your underwriting yet? And if not, is that a possibility?

It's a good question. Actually, I'd say right now today, -- we're not modeling in necessarily an additional boost to what we can do in terms of operational improvements with AI in a portfolio company. I think Dave said it well, maybe in the future, this is an actual 1 of our work streams that will factor its way into the actual underwriting. So today, it's kind of -- we believe that we can usually go into these businesses, improve margins and AI is something that we're hoping to do to supercharge to either do the same changes we were always going to make faster or to have more impact or to have a totally separate impact -- but probably, it's going to take us a little bit of time of seeing more outcomes of the application of the technology. We know it's there. We know it's real. And once we see more outcomes, I think it might become a more regular part of our underwriting. [Break]

Okay. Well, good afternoon, everyone. It's great to see so many familiar faces and good friends. As a son of a Sam, was that the only 1 feeling uncomfortable with Howard's story there? Bruce was looking over at me. So last year, we said that Brookfield Infrastructure was approaching an inflection point in its growth trajectory. And today, I want to pick up where we left off and show you why we believe that's underway. To do that, I'm going to briefly revisit the strategy that we have, walk through what we've accomplished this year. And then I'll finish with what we think the opportunity ahead is why we -- and why we think it's as strong as it's ever been. So to start off with, we've got a slide here that I think -- most of you have seen this before, and that's pretty intentional. Our strategy hasn't changed. And there are 3 parts to it. We maintain a strong financial position deploy capital at attractive risk-adjusted returns, and we crystallize value through capital recycling. And when we execute those 3 things well, -- the result should be 10% or better FFO growth per unit over time. The full cycle approach has been the foundation of the business for almost 2 decades now. And it remains the framework for how we allocate capital today -- and as I just mentioned a second ago, a year ago, we told you we believe the growth rate was at that inflection point. And we had conviction because several things were coming together at once. Our organic backlog had grown. Recent investments were beginning to contribute to our business. Capital recycling is scaled and some of the headwinds that were affecting our per unit growth were starting to minimize. Now this year, rather than repeat that statement, I want to show you some of the evidence. And I think this chart tells the story pretty clearly. From 2023 to 2025, average annual FFO per unit growth was about 7%, which is below our long-term experience. This year, we expect that to be approximately 10%. The important point is the direction of travel. The base business is performing well. Capital from our backlog is coming into earnings and recent investments are contributing more meaningfully. Since inception, we've compounded FFO per unit at roughly 14%. Now we're not suggesting that 1 year will make a trend or gets right back up there. But we believe that business is now moving back toward the growth profile that the investors in this room have come to expect from us. So let me now walk you through the 3 elements of our strategy and where we stand against each of them. The key point is that the improvement in growth is not coming at the expense of financial discipline. We're maintaining a strong balance sheet, investing at attractive returns and continue to monetize mature businesses. So let's start with our financial position. We've generated 10% FFO per unit growth year-to-date, while maintaining approximately $2.6 billion of corporate liquidity and BBB+ investment grade credit ratings and a 65% payout ratio. Those numbers matter in combination. We're growing while retaining financial flexibility. That means that we can be patient when markets are expensive and move quickly when volatility creates opportunity, and that's been a hallmark of our success in the past. The second part of our strategy is deployment. We've secured approximately $1.4 billion of growth investments and expect to deploy more than $2 billion for the full year. Importantly, this isn't dependent on 1 large acquisition. The deployment is diversified across the investments we made into our semiconductor facility. The growth backlog that we have within our other businesses and new investments made through various industrial partnerships. The mix is increasingly representative of our opportunity set involves more organic investments, more strategic partnerships and more opportunities sourced through the Brookfield ecosystem rather than just competing in broad auctions. And the more important point about this year's deployment is the return profile. We expect average returns of 15% or higher on the capital that we're currently deploying which is above our historic target range of about 12% to 15%. And there are a couple of reasons for that. First is the infrastructure super cycle is creating a very large opportunity set for us to invest in. Second, AI infrastructure is adding another capital-intensive growth avenue for us to pursue. And finally, our scale and competitive moat is helping us source opportunities where we can achieve better economics. What I'd emphasize is that we're not targeting higher returns by taking greater risk. We remain focused on high-quality counterparties, strong contractual protections and disciplined underwriting. The other side of the equation, obviously, is capital recycling. So far this year, we've secured approximately $1.4 billion of asset sale proceeds, and that excludes the approximately $1.2 billion of proceeds that we were able to obtain from the Square IPO, which was used to repay debt. We remain well on track to exceed our $2 billion target for capital recycling for the year. The return shown here from the mid-teens to over 40% demonstrate the value that we've created across various businesses and geographies throughout the year. This is how the full-cycle strategy funds itself. We take capital out of mature investments where we've executed the value creation plan and redeploy it into new opportunities at attractive returns. That spread is an important source of long-term per unit growth. So I want to take a second to discuss the simplification that we announced in July. You may recall that we listed BIP in 2008 as a partnership and created BIPC in 2020. And -- we are now proposing to combine these 2 into a single publicly traded corporation called Bit Bank. Nothing changes about the underlying business or the investment strategy. What changes is just the wrapper. We expect 1 corporate security to be easier to own. It will broaden the potential investor base to those who currently can own a partnership and they'll materially improve consolidated trade and liquidity. The security holder vote is scheduled for October 14, and subject to approvals, we expect to close the transaction in the fourth quarter. The result should be a roughly $30 billion company and more than twice the trade and liquidity. So this brings us back to the inflection. Our confidence doesn't come from any single transaction or results from in the quarter. It comes from a combination of having a strong base business on larger organic backlog and more capital going to work at attractive returns. And I'm going to finish up on this slide because demonstrates or these shows why we're optimistic on the deployment front, and it sets out the focus for the remainder of the presentation. We have 3 substantial avenues for capital deployment that we're going to talk about. M&A and corporate partnerships, AI infrastructure, infrastructure and organic growth within our businesses. The point we hope you take away at the end of the presentation is that our strategic advantage is the optionality that we have in the business to allocate capital to whatever opportunities offers the best risk-adjusted returns at that time. So with that, I'm going to turn it over to Scott and he's going to come up and talk about M&A and corporate partnerships.

Thank you. I don't know if anyone else was keeping track of the number of time scale was mentioned today. Every session has referenced it either directly or indirectly. And in fact, Bruce's start at the beginning when he was asked, what gets him most excited about coming to work. He referred to the assets, the relationships the dollars, the people that we have here, which is very different from where he started his career. That's all scale. So with that, that introduced me well. I want to spend the next 10 minutes sharing why scale has become BIP's primary competitive advantage. And it's something that's been built patiently and deliberately business by business over the decades. I'll start with 3 main messages. First is that scale is no longer a nice to have. It's not even simply just important. It is a prerequisite for market relevance for accessing the best opportunities and the best returns. Second, we have differentiated access to the world's largest companies who originate most of the coveted and high-quality market transactions we pursue. And third, the infrastructure landscape is vast and it continues to expand. So we're able to remain highly selective in where we deploy our capital. I'd estimate about 1/3 to 1/2 of the infrastructure we invest in today was nascent or didn't even exist as an investable asset class a decade ago. With that context, it may make more sense that the current forecast for global infrastructure requirements has doubled over the last 10 years to more than $100 trillion today. Now while traditional infrastructure needs have grown, there have been 3 developments over this period that I'd like to mention. The first is that there's been advancements in technology. You heard the OpenAI panel, that's not going to be a surprise to you. Think fiberization, think automation, think AI factories. These weren't prevalent 10 years ago, but each is highly relevant today and will be in the future. The second is previously less understood subsectors are maturing with large capital needs, think residential infrastructure. And last, asset classes previously outside the perimeter of infrastructure, ones that didn't meet the rigorous definitions that we hold them to have been adapting their revenue models, have been adapting their contracts to fit within the perimeter of infrastructure. For example, semiconductor foundries like what we did with Intel. So all this means we have a much broader opportunity set to choose from. However, to capitalize on these opportunities, a few interconnected elements are required. Together, these create a very strong moat for BIP's long-term deployment visibility, and that's very valuable and difficult to replicate. The first is the most quantifiable. You need a big business, big dollars, lots of people and assets and a long track record. The second element is more subjective. You need operating expertise. This can be demonstrated through key performance indicators, a large and experienced team and results over a long measurement period. And third, which can only be earned if you have the first 2 right, our trusted corporate relationships with the leading market participants. Let's remember the leading corporations originate the majority of the large and attractive infrastructure opportunities in the market. Origination from government is infrequent. And because infrastructure assets are critical by definition, the same corporates rely on them both before and after a transaction. And that is why as we move to the middle column on this slide, corporate JVs, corporate partnerships, corporate carve-outs, they're all the most common. These corporate sellers require a counterparty that can operate the business is critical to them safely and reliably. And while price is important to them, it's rarely their primary consideration. And the more complex a transaction is an area where you've seen us excel, the greater the need for every prerequisite to be satisfied and BIP ticks all these boxes. So consequently, a selection from our partnership resume includes some of the leading companies around the world. The structures were varied, carve-out, sale leasebacks, JVs, strategic frameworks, but each required a partner they knew well that brought a big business to bear with relevant operating expertise. And most of these were bilateral, beginning years earlier with a relationship. This snapshot captures the breadth of BIPs infrastructure franchise today, specifically the resources and capabilities that we bring. $200 billion of assets under management, portfolio companies in 15 countries, a track record of over 100 closed transactions, representing over $75 billion of equity deployed with an incremental $20 billion of equity projects currently underway. These credentials more than satisfy the request of corporate boards of regulators and other key stakeholders. But it's important to flag that the corporate leaders of these companies are the ones who ultimately drive counterparty selection. And what they really care about lies beneath the surface of this slide. Corporate leaders regularly engage with our 50 portfolio companies across the globe. They've seen firsthand that BIP is an experienced operator and deeply understands their business. In each sector where we operate, our industry scale rivals the largest strategics. We're not a financial buyer standing outside these industries. We're 1 of the larger operators inside of them. We operate critical and high-profile assets, transmission lines, pipelines, towers, fiber, data centers, rail lines and logistics assets. This translates to deep credibility with corporate leadership. So let's connect what we've talked about. Let's connect our scale our operating expertise and our relationships and connect how that ties to what Sam talked about in terms of our FFO per unit growth plan. It starts with our ability to access and selectively pursue larger acquisitions and do more with these businesses once we own them. And as the size of our acquisitions has increased over time, our average returns on invested capital have to -- we're deploying more capital while generating more FFO per unit of capital. Two reasons why this is occurring. The first is that larger businesses often have fewer credible buyers which can translate to a better entry value point for us. But they typically also accompanied by more levers and more avenues for growth for us to create value very quickly during our ownership. Put simply, we're able to buy better and we're able to create more value with what we buy. Another perspective to share is that bigger deals are not simply a larger version of a small deal. We're not buying a single big thing at the end of the day. These are dynamic businesses with different segments in different regions and different assets included at different stages of maturity. Ultimately, a large business is typically a collection of smaller businesses that have been assembled and accumulated over time. And their integration over this time period is rarely perfect. Accordingly, these big businesses are often rife with duplicate systems burdened by legacy cost structures and constrained by bureaucracy, all serving as ideal opportunities for us to quickly add value. Our toolkit is working. We start by identifying and supporting the right leadership team, then we improve margins in contracting. We imposed capital allocation discipline -- we optimize the capital structure. We support the business through incremental CapEx at accretive returns, and we ultimately ensure long-term optionality for our exit of the business. We're seeing our toolkit translate to enhanced returns. We don't simply acquire businesses. We actively manage them. Triton, Hotwire Colonial, all very different, show the playbook in action. During the first 12 to 24 months, we've now owned them, we've completed bolt-on acquisitions, materially improved margins, monetize stabilized assets. None of this we paid for an acquisition. We underwrite these businesses to a mid-teen return. But through active management, we're already adding roughly 200 to 400 basis points, lifting returns into the high teens. And as larger transactions become more common for us, -- this same value creation playbook can be repeated with greater frequency and greater materiality. The leading businesses within the infrastructure market have grown. So it's natural that the enterprise value of the transactions BIP has done over the years has grown as well. From 2015 to 2020, many of our market-leading transactions had enterprise values in the low single-digit billions. Since 2021, the size has shifted upward with our focus on larger businesses and larger partnerships. Now a conclusion here should not be that we're only doing big deals. An excellent mid-scale transaction won't get past us, I assure you, but we compete and perform best at the upper end of the scale where we tend to achieve the best returns. This trend can also be seen by the average amount of equity we deploy per deal and the average returns on that deployment. From 2015 to 2020, it deployed an average of $300 million per deal and achieved returns between 12% and 15%. And since 2021, however, this number doubled to $600 million, while average cargo returns now exceed 15%. Four key takeaways. Our opportunity set is vast and growing, allowing us to remain highly selective. BIP is a trusted partner and counterparty to the best companies with access to the most attractive transactions. Our established operating toolkit creates significant value beyond what we underwrite at entry, particularly evident in our larger business acquisitions. These advantages, which all ultimately stem from scale, facilitate more capital deployed at higher target returns, supporting higher FFO per unit growth. Next up for you, we have a panel. It's titled building the backbone of AI, a clear example of bipscale in action. I'll now hand the stage back to Sam, who will serve as moderator. Thank you.

All right. Well, it's my pleasure to be on stage here with 2 of my colleagues who are the leaders of our AI strategy. Sikander Rashid is the global head Leaf Williams is 1 of our Senior Managing Directors here in Toronto, who's been leading a lot of the AI factory initiatives that we're going to talk a bit about and that he spoke about last year. The whole AI sector is something, I guess, we've been talking about, I think, for about 2 years now at these sessions. And I recall that when we first threw up the $7 trillion addressable market for AI infrastructure, we all were a little unsure whether or not that was a little high. What we've clearly seen in the last couple of years, but especially this year, is that, that number, if anything, is understated, the amount of capital the opportunity set for us continues to grow at an exponential rate. But what I thought we'd do to start off with is maybe direct the question to both of you about your experience this past year, with what you see changing, what you sort of see things going to in the next year or so. So maybe Sikander. I'll start with you, maybe give your thoughts on what you've seen in the past year.

Well, thank you, Sam. Thanks for having us, both Life and I and it's great to be here and see so many familiar faces. Look, 12 months in AI is a long time. A lot has happened. I would say 12 months ago, investors had 3 big questions. Will the AI models continue to get better. It's a topic Nik touched on earlier. Number two, do we need all of this infrastructure? Do we need all of these GPUs, the power and the compute. And third, will AI actually generate revenue. Fast forward to today, I would say what's really exciting is the markets addressed all 3 of those questions. Number one, last year, U.S. or 20 gigawatts of capacity. This year, we will beat that NVIDIA, who is at the forefront of this, is recording $90 billion per quarter in revenues, up 120% since last year. So yes, we need this infrastructure. The demand is there. AI models continue to get better. We've gone from chat bots to agents hopefully soon to physical AI. So the bottles continue to get better, which is great for the technology and the adoption of it. And lastly, yes, AI is generating revenue. The 2 frontier labs, OpenAI and Anthropic 12 months ago, had $5 billion to $7 billion in annualized revenues. Today, the number is $110 billion. So clearly, AI has got revenue attached to that's all really exciting for AI infrastructure.

So turn to prove out.

Yes. One other thing I would add, Sam, is and it's become more prevalent every month of the last year has just been community engagement and just prevailing local sentiment on data centers. So I would say 18 months ago, there was a perception in the race, but the most important thing was just to get massive amounts of power at a site at any cost. Now it's probably no surprise that, that's resulted in some backlash -- we've now seen 4 states and over 300 counties and counting who have implemented data center moratoriums or otherwise delayed permits to get these shovels in the ground and get these sites operational. I think in practice, again, these AI factories, if you do them correctly, they do bring massive benefits, significant investments, large amount of taxable basis employment, both during the construction period and when operational. But you need to articulate these benefits, and you need to effectively ensure that you're doing it the right way. And so this really means bringing your own power, protecting the rate payer and articulating the benefits that come from these projects.

Okay. So I want to come back to a bunch of points there. But First, I want to address 1 of the comments that Sikander was talking about, just the amount of dollars that we're seeing and just the rush into the sector. We're obviously not alone in having capital and we need to differentiate ourselves. Obviously, we have a lot of capital, and we can bring that to bear. But 1 of the things we're doing today to differentiate ourselves in the businesses that we're establishing and buying.

Yes. Look, I think there's a couple of things. Skill obviously matters. Coming back to -- maybe I'll start with the AI factory initiative, which we've touched on. So the way I describe it is, whilst the technology firms are building the brain, we're building the body -- and the components of this body are power, data center or real estate and compute. And 5 years ago, these big technology firms, all the sovereign governments could have worked with multiple vendors and pulled it all together for their cloud computing services. Today, it's a race, not just between the countries, whether it's U.S. and China, but also among all the technology firms. And their preference now is to work with vendors who have the ability to package it all together. And the other element of this is, one, gigawatt or 1 megawatt of power cost or data center cost $10 million with the CPUs 5 years ago, today is $50 million. So the complexity and the size both have increased. And therefore, our competitive advantage as a firm is we are 1 of the largest energy investors. We are 1 of the largest data center investors. And thanks to our partnership with NVIDIA, we've also got compute capabilities. So we have the ability to offer this integrated computing services to some of the largest clients in the world.

Okay. So we've made an investment in Radiant. How did we do it? And why are we going to be able to make money in that lower brands?

Yes. So This was a question you asked us 18 months ago. And I'll give you the same answer. I think there's 3 things. Why are we so excited about this? Why we did this first AI infrastructure will be a $10 trillion. I know Sam said 7, we've already increased the number to 10. It will be a $10 trillion CapEx spend. Now half of that spend will be on compute or the kit that goes inside of a data center, so big dollars. Secondly, every company in every country is going to have its own AI. And that AI will be bespoke customized sovereign, secure catering to the needs of that country or the company. And thirdly, the chip industrialization cycle is 5 years long. So it takes time to manufacture new chips, design them and build them. For all those reasons, we identified this as a sector where we could invest a lot of capital in partnership with NVIDIA, and that's why we formulated Radiant. It's effectively a compute platform that provides GPU as a service which includes data centers and the compute to some of the largest technology firms and solveign governments in the world, and the focus is take-or-pay contracts, IG customers and focusing on a return on and off of capital in the contracts to minimize technology risk, and we're really excited. The momentum is great and is rely exciting.

Okay. So Leif, you were here last year talking about AI factories. And so -- can just kind of described what they're consisted of both the building as well as the compute. Maybe describe for us how the cost in each of those facilities differs a little bit in various margins -- markets. And maybe we can touch on the 2 deals that we are currently working on that we've announced, 1 in the U.S. and 1 here in Canada.

Yes, yes. So the -- look, the recap an AI factory. This is a large-scale campus. It's purpose-built for AI workloads, and it's integrated. And so that means that you're finding the solution to bring power to the site, whether it's grid connected or whether it's behind the meter -- you're building the data center and all of the infrastructure that goes inside that. So generators, batteries, mechanical plant and then the compute in some cases, you would also be bringing in the compute and offering that as a service to your end customers. So we think that this is an important infrastructure asset for a couple of reasons. Number one, it produces attractive risk-adjusted returns. So I would say, to bring a gigawatt of load just as an example, unit. That is a very difficult thing, and there's massive scarcity value in that asset. And so as a result, you can earn attractive risk-adjusted returns of over 10% unlevered on a yield on cost basis. Secondly, as eco described, these are very capital intensive, and so $50 billion, $60 billion per AI factory. And thirdly, these have all the infrastructure characteristics that we look for. So investment-grade counterparties, long-term contracts, inflation protections. Maybe to talk a little bit about 2 of the AI factories that we've announced. If you thought about where should an AI factory be built and yet, we're working from a blank sheet of paper. These 2 projects are exactly what you would come up with. So we've got 1 site in Paducah, Kentucky -- and 1 site in key pills in Alberta. And in both cases, like I said, they're exactly what you would look for it. So massive campuses really well interconnected to the grid, both the electric grid and the gas grid. We've got great partners who are working with us on this. And then there are just opportunities to bring scale or can be expanded over the long term, and we think are kind of examples of doing this in the right way. And so just a couple of anecdotes about each of them, the Paducah campus. This is a former Department of Energy campus. It serves 3 gigawatts of load at its peak. I've not seen any other site anywhere in North America that had that much load in the past. It's just really well connected from that perspective. The Key pill site, this is located really at the heart of Alberta's electric transmission system. The whole grid was built around the power plant in this area. Typically, for an AI factory, you look for 1 or 2 large high-voltage transmission lines. Our site at key pills has 7 high-voltage transmission lines connecting into our interconnection point. So really well situated to protect rate payers and really well situated for our customers.

The only comment I'd add to that is to what Lee described really well is both of these opportunities, unlike a traditional data center investments, and we've leveraged relationships with NextEra or the Department of Energy or TransAlta, 1 of our companies to create opportunities where we've minimized speculative capital outlay, which would be another differentiator of how we're doing things compared to everyone else. Okay. Well, maybe just timing on 2 things you both mentioned. One is the importance of power. And not every site is as well in doubt as Key pills is with interconnections. And so for that, we've identified Bloom Energy as a great partner and some we've built a great relationship with to provide behind-the-meter power solutions for many of these facilities. Sikka, maybe just talk about that relationship and how it works and why has it been so powerful?

Yes, absolutely. So big picture, the U.S. alone will need 100 gigawatts of power in the next 10 years for AI infrastructure alone. That's obviously a big number. The utility utilities throughout the country can only support 30 of that. So we identified a 70 gigawatt gap in power availability in the U.S. and looked at a host of solutions -- we picked Blue approach them with this idea of becoming their capital partner because time to market in this market environment is everything timed to tokens is revenue, as you will hear from some of the Frontier labs. And Bloom has the fuel cells, by definition, don't burn gas, they consume gas. And by virtue of that process, the permitting time lines for this technology are relatively short. And it's been a phenomenal partnership. We're a capital partner. We invest in investment-grade customers, price the contracts such that we get a return on and off of our capital over the contract term, which is only 10 to 15 years. And we started with $5 billion. We've upsized the partnership to $25 billion, and that's fantastic.

That's great. Okay. So we have a little time left. And in true Brookfield fashion, we always talk about the downside. And so what I wanted us to cover to end off was just -- and you both have worked with us in our traditional infrastructure business for many years. What's different about these assets versus what you've historically been involved with? And how are we mitigating risk? So maybe we'll start with Leaf and then seek you can fish off.

Yes. So what I would say, I feel in a lot of ways, it's returning to infrastructure's routes as concession assets. We're underwriting a DCF that effectively has a stream of cash flows, and we're assuming very little or 0 terminal value in a lot of cases. And so again, I think it's really the underwriting approach where we're taking a very infrastructure-centric focus.

Okay. As much as I would love to tell you, we've used to come up with a new underwriting formula. We haven't unfortunately. It's still the same formula. You learned from you over the year, Sam, and it's basically focusing on take-or-pay contracts, investment-grade counterparties. And more importantly, I think this is very important for AI infrastructure pricing the contracts, whether it's power, data centers or compute or silicon pricing them such that we target to get a return on and off of capital over the initial contract term and ensuring that term is commensurate with the useful life of the asset is very, very critical, and that's our focus.

Yes. And the only thing I would add is counterparties and documentation are critical. So our attention to detail has to be razor sharp to ensure that we're not entering any agreements that people can somehow get out of because these are long-term agreements that we're entering into. So that concludes what we want to talk about AI infrastructure. Next up, we have David Krant, who's going to talk about organic growth and tie together all the different deployment opportunities that we've been talking about. Please welcome Chief Financial Officer of Brookfield Infrastructure Partners, David Krant.

All right. Thank you, Simon, and good afternoon, everyone. I'm going to spend the next few minutes on 1 straightforward idea. And that is that BIP has more ways to grow today, and that gives us more ability to choose where we put our capital. The result is a broader opportunity set, which will allow us to invest capital at better risk-adjusted returns and further drive FFO per unit growth. Let me start by laying out the 3 channels available to us. As you saw earlier, -- the first is traditional M&A. This is buying businesses that we've done for the last 17 years, utilities, transportation, midstream, digital infrastructure. It's driven our growth for many years, and it will for years to come. The second, you just heard of is AI infrastructure. And the third is organic growth capital. This is investing inside the 50 portfolio companies we already own today. Now each of these channels differ in terms of their timing, the risks and the return profiles. And that's exactly the point. We do not need all channels to be open at the same time in order for us to grow. Rather, we can choose where we invest that capital to earn the best risk-adjusted returns. Let's go through each of these, starting with the 1 that's done the majority of our growth to date, and that's traditional M&A. Across the period shown, we have averaged about $2.2 billion of investment into growth initiatives. If we focus in on where that's come from, while almost 80% of it has come from this traditional M&A. And because of our scale today, the size of these investments have trended larger and as a result, have provided us with very strong risk-adjusted returns. Traditional M&A will remain a very important part of what we do. But as you heard, the opportunity set is now more broad. And that's most notable in AI infrastructure. As you've heard, AI infrastructure is not just 1 single asset class, rather a set of connected opportunities across 3 channels so far. Today, it's been power and transmission, AI factories and compute infrastructure. Each of these opportunities are similar in that they are a large scale and have highly contracted revenue profiles, which is something we love. But what may differ is the deployment cycle or the time it converts to earnings. And so as we look out over the next 5 years, which is the time it may take to contribute -- to fully contribute -- we expect to invest upwards of $2.5 billion at our share over that 5-year period. So that simple math, that's about $500 million per year that we expect to deploy into this new growth channel. And because these opportunities are large, we will invest alongside partners, allowing BIP to concentrate its investment into those highest returning projects. And finally, the third channel, which I'll spend a little bit more time on today is our organic growth. Looking at our deployment this year, as Sam highlighted earlier, you can see we've deployed nearly $1.5 billion into growth. The majority of that has come from internally sourced organic growth projects. If you add on top of that, the funding of our Intel joint venture in Arizona, while we've deployed nearly $1 billion into assets we own today, building high-quality new businesses. And said differently, the majority of this year's growth has been organic. That doesn't mean traditional M&A won't be coming, but it does mean that we have focused on internally sourced projects. And that is a good thing. There's a few reasons we like organic growth projects. The first is that it's lower risk. We know the business, the team, the customer, and we've got a 15-year track record of building these types of projects on scope, schedule and budget. And the second is less competition. As the incumbent owner and operator of these businesses, we are uniquely positioned to win on these mandates. And so when you combine lower risk with less competition, well, that gives you excellent risk-adjusted returns -- what we don't underwrite in these projects is the fact that we're building them at several turns discount to what they would go for in the prevailing market. That value will be captured through capital recycling, something we talked about last year. And because these projects are now at scale, we've built our backlog into a record level. In fact, 5 years ago, at this event, we had set a pretty ambitious target for ourselves to grow our backlog to $3 billion. Well, by 2024, we'd achieved that and more. We did $4 billion, 1/3 above our target. Fast forward to today, our backlog stands at $6 billion, and that excludes any capital for the Intel joint venture. And so the important part here is not just the numbers, but it's the trajectory. As our portfolio of companies have grown as the businesses we've acquired have grown, so has our ability to source extremely attractive projects from within them. And if we dive a bit more into the backlog, we'd like to think of it as a funnel. At the bottom of the funnel is the $6 billion of approved projects that we have underway today. This provides highly visible earnings over the next 2 to 3 years as we've already secured the customer, the financing, and we're well underway. If we work our way up, say, the layer at the planning and commercialization phase. Well, we have another $3 billion of projects at our share that were in active discussions and final negotiations with customers on. This is really where the relative ranking and prioritization of projects gets done to find the best opportunities within our portfolio. And taking 1 step further back there's $6 billion or more of projects that are in the early stage of opportunities. And this is where we may be looking at sites, having initial discussions with our customers to help unlock the growth within their business. And the point here is really around the depth of the funnel gives us good visibility, not just into the earnings in the next 2 to 3 years, but it gives us the confidence that we will replenish this backlog with a significant amount of capital as well as grow it over time. And so if we combine our scale with the fact that we have a broadening opportunity set in front of us, it gives us the conviction to believe that we can deploy a significant amount of capital at really attractive risk-adjusted returns and therefore, drive further FFO per unit growth. And so if we pull it all together, starting with the deployment channel, you can see we've invested -- or as you recall, we invested about $2.2 billion annually over the last 3 years. Well, going forward, we expect that number to be anywhere between $2 billion and $3 billion per year. Based on our historical deployment, which was traditionally M&A, you can see that ranges between $1 billion and $2 billion per year. Again, we'll vary because, again, we are value-based investors, and so we will choose where we put that capital. On top of that, you have the AI infrastructure opportunity set of about $500 million per year and funding our backlog between $500 million and $1 billion in a given year. And so looking at that in totality, it's important to note these aren't quotas. The mix will inevitably be different -- but what's important here is that we have the choice to invest capital where we see the best returns. And the choice won't just come through in the deployment figures. It will really come through in the returns that we generate. Across each of these 3 channels, whether it be traditional M&A, AI infrastructure or our organic growth backlog, we're targeting a minimum of 15% equity returns. And so to help frame what does that mean for per unit growth in the years to come? Well, we thought we'd show a few scenarios. On the conservative end, let's assume we invest a low amount, $2 billion per year and we deploy it only at 15%. While that will drive 5% per unit growth that year. Now if we are able to flex our investment amount up to $3 billion or generate returns above the 15% well, that's going to translate into higher pre unit growth. And at the higher end of the range, you'll see upwards of 8% per year growth from the business. And the point here is that the broader opportunity set improves both the amount we can deploy, but also the returns we can generate. And that combination gives us good visibility into today into 2026 earnings being at 10% per unit or higher or in the next 2 to 3 years. And so as we look out, the numbers are quite attractive. As a reminder, the base business grows from inflation indexation and volume surplus. That's 4% to 6% per year without investing a single dollar into growth. Now if you use the low end of our target range of $2 billion of 15%, well, that's roughly 5% per unit growth, making a very visible path to our 10% long-term target. But as I said, there is upside here if we're able to deploy more capital, which we hope we do, and we're able to do so at better returns while we have a business plan that can get us to 12% per year growth or higher. That will allow us to continue to inflect in our growth rates and support long-term distribution growth as well. As a reminder, since 2009, we've grown our distribution for 17 consecutive years at a 9% average rate. As we look ahead, as our growth rate continues to accelerate, we hope that our distribution track record will as well. And so I'll wrap up today with 4 key takeaways as every Brookfield presentation has seemed to do. First, organic growth is at record levels, and that is a good thing for our business. Second, our scale has made us a partner of choice, leading to bigger investment opportunities at higher attractive returns. Third, AI infrastructure is an evolving asset class that's allowing us to deploy more capital at really good risk-adjusted returns. And finally, all this results in our growth rate being at the early stages of an inflection point. And so with that, I'll now invite Sam back up for closing remarks and Q&A.

All right. Well, thank you for your time today. And before we take questions, I thought I would just close a few thoughts on why we think this is an attractive entry point for investors to come into the BIP units. Now first, our bit but offer a dividend yield of more than 5% today providing investors with a meaningful current return while participating in the growth of the business. And then second, as Dave just highlighted, the growth rate in our FFO has begun to accelerate and that should support an attractive dividend growth rate in the future. And hopefully, we can get back up to that 9%. And lastly, we're hoping that the simplification of our corporate structure, which should take place by end of the year will help re-rate the stock a bit by making it easier to own, increase liquidity and broaden the potential for new investors to come into the stock. So with that, I'll conclude and take any questions that there are. Cherilyn upfront here.

Cherilyn Radbourne from TD Cowen. So One of the themes in your presentation was that scale brings you into better opportunities. The corollary of that is that you end up with a bigger business, so you need more sort of optionality on the exit side to fully monetize that. Can you sort of close the loop for us there?

Sure. No, it's a great question, and it's 1 that we get a lot because the -- the natural reaction to when you say you buy something that's bigger is that as you add value and look to sell 10 years from now, it's even bigger. And if you got it because there are very few people who can get in, well, then how do you expect to sell it. And what I'd say, I think this what Scott said in his remarks a bit is that these businesses typically aren't just 1 business. Often what happens when we buy a large enterprise is it's a agglomeration of many different businesses. And 1 of the things that we tend to do is examine opportunities where we can split the business either by geography or different business lines and make that available to a more mid-market type buyer. And a good example of that would be a business we bought a number of years ago in the U.S. railroad, a short line railroad, which was a business that had been rolled up over many years. What we saw as an opportunity to split that business into 3 different sections by region. And our plan will be in a couple of years' time once we finish optimizing the business to sell that company in those 3 different pieces. But if someone saw that as a public company, initially, they weren't thinking of it as 3 different businesses. They just thought of as 1 company. I hope that answered your question.

Frederic Bastien at Raymond James. Sam, I'd like to touch on the Canada Investment Summit that was held a couple of weeks ago of the federal initiatives announced, including the new investment types write-off, proposed airport privatization and the national secure digital network which do you expect will have -- will create the strongest opportunities for Brookfield Infrastructure.

Well, look, I think there's opportunities and all of the above. I think for us, we've been advocating for a change to tax code for a while, and I think that's going to spur a lot of new investment into the country. So I think that's very positive. Obviously, 1 of the things Canada hasn't been doing as well in some other countries has been monetizing mature assets to generate proceeds that they can then invest in new infrastructure. We've seen that done in Australia. We've seen it done in the U.K. We've seen done many other places, and we're seeing right now taking place in the Middle East. Canada should be taking advantage of all the capital that's available and that's interested in mature assets. And so I think the airports should they proceed with that, we'll find a lot of interested buyers, including ourselves. And I think, obviously, the other important factor is just streamlining the consultation and approval processes will make a big, big difference in encouraging developers to take risk with new projects. I think that's something that hasn't taken place over the last decade, and I think that will have a big impact on the future of Canada.

Maurice Choy from RBC Capital Markets. Just 1 question for me. I wanted to unpack the comment earlier made in the Bruce and Howard session that inflation today is caused by 2 ongoing wars and inflation and the rest of the system is not that much. You said earlier that the AI opportunity has now increased to $10 trillion and because of the war, likely global energy infrastructure CapEx is also likely to increase. All of this suggests that there is likely a persistent supply chain-driven inflation in the years ahead. Even if the war ends. So I wonder if you had any thoughts on that? And as a quick follow-up on 1 of the slides that David presented on Slide 48. I think the first bucket for your FFO growth was inflation indexation of 3% or 4%. I wonder if you could possibly see that increasing higher if inflation does persist.

Okay. Well, the first thing I would say, it's never wise to disagree your boss. So if he says inflation is not going up, then I agree with them I think the -- look, his point was that there are obviously inflationary pressures from the war and from going into various industries. And so obviously, what you said is correct. At the same time, there are other factors that are deflationary. There's overcapacity in certain sectors -- there's demographic factors taking place. And so how all those weigh in over a longer period of time, it's hard to say. But I do think that, generally speaking, once some of these near-term factors dissipate. And look, the war should end at some point relatively soon. And I think the investment boom will moderate as it always does. So I think longer term, you will see inflation taper down. The benefit, though, is that if it doesn't, there's no better asset class, no better stock to own than BIP because almost all our revenues are indexed to inflation and will be big beneficiaries of that. So thank you for that lot, Paul so I think that's all we have time wise. So thank you very much. Appreciate your time and be happy to speak to anyone outside.