Brookfield Business Corporation (BBUC) Earnings Call Transcript & Summary

For some things, it's an excellent opportunity because they're getting punished in the capital markets because the common trend thread out there is an inflation here forever, and it's going to be high forever rates are going up forever, and they're not.

And what are those things?

BBU, BIP and Bell since we're here to talk about those 3 today.

Okay. Can you share that...

Look, Katherine, -- just to wrap up, I think that in real life, things fluctuate between pretty good and not so high. But in the minds of investors, they go from flawless to hopeless. And you would rather buy when most people are depressed and think it's hopeless. And we're closer to that now than we were 2 months ago. So I think it's -- in general, it's a much better buying time and that the view that everything is flawless is certainly not prevalent today.

And that's actually -- Catherine, that's actually a good point to be because we were heading possibly to a point where things were going to get high -- and then everyone knows what happens. And having governors in the system like what's going on right now is probably a good thing for the longer term of business.

So final question to wrap up because I think we're pretty much out of time. What are you most excited about for Brookfield and Oaktree PAUSE looking out onto the horizon?

From our standpoint, I would just say we have from when -- where you started, you asked how did we start? When we started, we had no idea what we were doing. We didn't have that much money, and we had no relationships, didn't start off so well. But today, we have 1 of the best fund rising franchises in the world. We're in 30 countries. We have highly trained people, 5,000 investment people, 300,000 operating people. We have access to almost anyone in the world that we want access to. It gives us an incredible opportunity as long as we're prudent about what we do to keep building the business and do amazing things. So it's -- I'd say that's what I get excited about every day.

Well, I'll just say that people ask me what keeps me up at night, the opposite of your question. And my answer is I worry that everybody is going to be so sanguine that there won't be any great opportunities to invest. I think that in the environment as it exists today and the environment we're heading towards, confident there will be a lot of interesting things to buy and not everybody will be eager to buy them.

Thank you both. [Break]

Through deep operational turnaround or activity in the companies. Now all of this is before AI. This is everything thing we're doing, if there was no open AI, if there was no technology shift in the world today. And we're thrilled to have partnered with open AI as a lead founding partner in the open AI development company to accelerate deployment in enterprise -- our belief is the technology, of course, is already transformative. It's only getting better. You're going to hear more about it from the panel we have coming up. But the technology is not really the bottleneck -- the bottleneck is deployment of that technology in enterprise at scale. We need to see real productivity gains in businesses. That's how it's -- how all of this investment in the technology makes sense. And that's going to happen because people are deploying it better. We made this investment in BUC, both because we genuinely believe it's going to be an incredible investment that will generate tremendous profits for us, of course. But more than that, we saw an opportunity to partner with open AI across our entire portfolio, and we already have real live use cases of things we're doing on the ground that are already going to hit the financials, and we just haven't seen the full impact of it yet.. Now -- the best part is with all of everything I've described and everything we have in the portfolio today, we're truly set up today to continue to compound our business and grow. First is when you look back to when BBU was spun out of Brookfield. The businesses we own are very different than the ones that are in the portfolio today. Our businesses today are higher margin -- they're larger, they're bigger scale. They have larger market share and their overall higher quality than we had 10 years ago. We've also started to build the next generation of industrial leaders. That's a great part of our business. Josh Reed will talk about how some of our portfolio is early. Some of it is evolving and some of it is mature. What we often talk about is things like Clarios that are already mature and are already leaders. But that next generation of leaders is coming, businesses like Chemilex or businesses like Fosburgh, Greg, they are going to be the next cleriosis of our portfolio, and we've started that work already, but we've been able to buy these companies at 9x EBITDA. When we acquired them, they were already 25% EBITDA margin businesses. That means that they were high-quality businesses to begin with. But our base case operational plan sees us increasing margins by about 500 basis points. Now if you take that forward, -- that means on just those 4 companies alone that we bought in the last year, it adds about $300 million of EBITDA to those businesses simply with the operational initiatives we already have on flight at a 10x multiple, that's a $3 billion additional equity value for the portfolio. And at BUCs share, it's about $4 a share. And that's without us making another acquisition, and that's only taking the last 4 companies we invested in. Now as we do this, as we improve these businesses and we make them better, the next most powerful thing we can do is when they get to the right scale, size, and maturity level is recycle those businesses and sell them. And we've significantly increased our rate at which we recycle capital -- if you look back in our first 5 years, we did about $800 million a year. And today, we're averaging about $1.6 billion today. That's almost 2x the recycling that we used to do in the past. We take that capital and we put it back to work buying other great businesses that we know we can transform. On that note, we talked about a $2 billion recycling program last year that we thought we'd do over many years, and we're already about $1.4 billion through it. So we're doing quite well on our way to achieving our target -- now that coming full circle gets to the flywheel that we've developed. We buy great businesses. We make them better with our operational improvements and our capabilities. And then we exit them at the right time, and we put the money back to work with the same team that has been doing this for decades that knows how to do it. That's 30 monetizations that we've done -- generating a 19% IRR to date on $9 billion of cumulative proceeds and those sales were, on average, done at a 12% premium to the NAV that we are -- that we have on our books. So we're selling businesses higher than we've even got them in our books. And we put that money back to work again and again and again. And that flywheel is really what you're investing in, what you're getting in BBUC is access to this market-leading industrial and heavy asset services, private equity group that knows how to make money and do this again and again, using the access and the opportunities we have across Brookfield. So I'll leave you with 3 things before I hand it over to my colleagues and to net the market is paying up for businesses just like the ones we own, businesses that can't be tipped over and will withstand the test of time. We have the scale, we have the capability, and we have the track record to do this and keep doing it and to actually make enormous amounts of profits in this environment. This is the right time for us and our flywheel of buying great businesses, improving them, selling them and putting it back to work has been proven, and we've demonstrated those returns for investors to see. And so with that, I would like to pass it over to Katie, Nate and David.

Please welcome our panel moderated by Katie Orbis with panelists Nate Harbors and David Bonacia.

Good afternoon, everyone. I'm Katie orbits, and I'm a managing partner in the private equity group. I'm pleased to be joined here today by my colleague, David Bonacia managing partner out of our New York office and Head of our Business Operations group within private equity for the Americas region and also leads our AI value creation office across Brookfield. And we're very lucky to be joined by Nate Harvestec who is Head of Global Business at OpenAI and Co-Founder of the OpenAI deployment company. So we're incredibly proud to have recently announced the closing of this newly formed partnership with Nate and OpenAI, the deployment company which is, as Anuj mentioned, a newly formed platform to actually roll out AI at scale into enterprise on a large-scale basis. And so we were 1 of the founding sponsors of this platform. We invested alongside a consortium of investors investing over $4 billion into this endeavor, and we're happy to dig into that opportunity today. So Nate, why don't we start with the problem that leads to the opportunity you sit -- where you sit in open AI today, you see AI adoption play out across a broad range of industries. Capabilities are obviously advancing incredibly quickly. What are you seeing? Where are companies struggling to actually deploy the AI and roll this out into their business?

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.