How GPs Should Approach AI Right Now - Brandon Rembe - Chief Solutions Officer - Juniper Square

(upbeat music) - You, for your business, focus on what you want to achieve for your LPs. And the way that gets done is gonna fundamentally change, no matter how old school you wanna keep it, how much you wanna put your head in this end. The world's gonna change around you at a faster pace than we've ever seen before. And so, find the right partners, find the right people internally to help you get through that. But really, it's, go back to what you're good at, what you wanna focus on, and then make sure you're finding the right people and partners and technologies to transform the way that you do business to get better outcomes. - Special edition of the distribution by Juniper Square, where I sit down with leaders across private markets. I'm your host, Brandon Siddlov. On today's episode, I sit down with Brandon Rembe, Chief Solutions Officer at Juniper Square. Brandon is the person at Juniper Square on the leading edge of how AI is changing markets. How we're building for it, and how we're communicating with our customers when they ask us where to start. We recorded this conversation in our sales kickoff in Nashville a few weeks ago, and it was too good not to share. Every GPI talk to right now is asking the same question, what do I actually do about AI? The headlines are everywhere. We all see them, the pressure is real, but most of the advice coming at them is from people talking their own book, people who are not well informed, or people who don't understand private markets. I wanted to pull back the curtain on what we're seeing at Juniper Square, straight from the person who spends his days inside of GP offices, helping to figure this stuff out. During our conversation, Brandon and I discuss, why the question of which AI model should I use is the wrong question entirely? How GPs actually should think about getting started and getting started with their data, and what the expert in the loop model means for you and the future of your team. If you're interested in AI adoption and private markets, what the most operationally forward thinking firms are doing right now, or how to cut through the noise, this episode's for you. Let's get into it. Brandon, we're here in Nashville. We just wrapped up sales kickoff. It's a time when we get our whole sales team together. What was your message to the sales team this year as we kind of are really rapidly focusing on AI at Juniper Square, and we're shipping products faster than we've ever shipped them, and really deeply understanding kind of what is important to GPs? What was your message to the team? I think it's two things. It's be excited and be ready. There's so much change going on in the markets, the technology that we're delivering, the way we're delivering that technology, the way that we're delivering services at a faster scale than ever. It's gonna change the way we sale, sell. It's gonna change the way we go to market. It's gonna change private markets and then. So even in private markets for a long time, kind of walk me through like, what is different now than earlier in your career? Why is this such an interesting time? And I often say private markets feel like they're at a structural inflection point, but through your lens, kind of you spent your career in private wealth, and you've been at Juniper Square Building, kind of institutional products, what are you seeing change right now? Well, certainly it's subject to things that are impacting all markets, mainly AI. And I get asked a lot, hey, Brandon, what should I be thinking about from an AI perspective, what models should I be using? And my answer is, you shouldn't be thinking about any of that. You should be focused on what you're good at, finding new deals, getting a higher ROI and higher return for your LPs, finding the next best investment for your firm, and then find the right partners, the thought leaders, to outsource all of that work to someone else. The most common question I get is, what model should I use for this? Well, the model I use today is gonna change a week from now in two weeks after that. And if you're spending your time focused on that, you're not focusing on the thing that you need to, which is delivering for your LPs. So your role at Juniper Square's Chief Solutions Officer, you're on the leading slash bleeding edge of everything AI at Juniper Square, which by default is everything AI, private markets. What does that mean? How do you spend your days? What are you focused on? Because you just said, you know, clients shouldn't focus on what model to use, a GP-Chan care, but what are we doing? So the GP doesn't need to worry about that. Yeah, you know, and the traditional software model, SaaS model, you would think a quarter out, three quarters out, maybe if you're lucky, 18 months out. That's not a luxury we have anymore. Things are moving so quickly that I need to be thinking five years out and in the world of AI where we can write code 100 times faster and deliver software faster to a client, faster than they could ever onboard those things. I have to think about the ways that these markets are going to change, how people want to consume technology, how they want to consume AI. We talk a lot about building trust at Juniper Square. And that's even more important in the world of AI where you're outsourcing not only to a human, but to an AI bot that is doing a lot of these services for you. How do you get comfortable with people comfortable with that? How do you make sure that they can verify and audit everything that's going on to make them feel comfortable? So they can scale along with us. So I would say if anything I've had to shift my thinking from quarters out to years out because what used to take five years is now going to take five months and we have to be thinking that far ahead to be relevant to our customers. So if you're thinking five years out, what is the role of a GP five years from now compared to what it is today in 2026? It's the same thing that we focus on. It's building trust with their clients, knowing what their clients need, what their clients problems are, and delivering those outcomes for their LPs. It's the same thing we focus on here at Juniper Square. Why are you so excited about Juniper Square and our role as an operations partner leading the charge in private markets on the topic of AI right now? Yeah, I think it really comes down to the foundations of where Juniper Square started. We didn't start as a finance company. We didn't start as a services company. We started as a technology company. And when you grow up that way, you start to build those foundations to be able to take advantage of technology when it comes up. We don't need to rethink starting from the bottom up of how to adopt AI. We've been doing that for years now at this point. It's just accelerating from that side. We're not taking a step back and going, oh, there's this new tool tool out there. How do I revamp everything that we're doing? We've already been thinking about that. So some might say it's lucky. I think it was a bit of luck, but a lot of strategic thinking and very purpose-built decisions that we had along the way that get us to a point where we can really take advantage of this moment in time when markets feel chaotic, when technology feels like it's hard to get your arms around, we can be the center kind of normalizing structure and the, what is it, the port in the storm, if you will, for a lot of our customers, where they can come to us, we can build the trust with them, to make them feel comfortable that with all of this change going on around them in markets and technology, they're partnering with Juniper Square. They don't have to worry about those problems. They can focus on what they need to. They can drop their shoulders and get back to work. >> So you spend a lot of time with customers. When you go into their office and you sit in a room like the one we're in right now and they say, "Brand it, you're the AI guy, what should I do? How do I get started? What does this mean for me? What is the advice that you give them in the shroud of secrecy behind those closed doors? What are they really asking? What do you tell them? And maybe we can share more broadly here. >> Yeah, there's a lot of things I wish I could tell them, but frankly, it would be over a lot of their heads and it scares them a little bit. But my job isn't to get out there and scare it's to inform and to help them get from A to B to C. And when I say, "Hey, what are the things you need to be thinking about from AI?" I think the biggest thing that I say is the outcomes you're trying to achieve for your business and the LP isn't going to be different five years from now. The way in which you achieve those outcomes, a hundred percent will be fundamentally different. And if it's not, that's what you should be worried about. So keep your focus on what you want to achieve for your business, focus on what you want to achieve for your LP's. And the way that gets done is going to fundamentally change no matter how old school you want to keep it, how much you want to put your head in this end, the world's going to change around you at a faster pace than we've ever seen before. And so find the right partners, find the right people internally to help you get through that. But really, it's go back to what you're good at, what you want to focus on. And then make sure you're finding the right people and partners and technologies to transform the way that you do business to get better outcomes. So let's say you're a private markets GP, or a private equity firm, or credit shop, maybe a real estate shop, and you really haven't started on your AI journey. You've been thinking about it. You know that it's important. You hear that you see the headlines, the good and the bad. What's one or two kind of tactical, actionable things that you would encourage a GP to do if they want to start right now on their AI journey? Yeah, one of the biggest challenges that people have in their AI journey is for AI to work properly. It needs to have a lot of context. So if I was walking into this conversation, I didn't know what we were talking about. It probably wouldn't be a very good conversation. And the same is true with AI. And the concept of what we're talking about, what context means is data. Data about. private markets, data about LPs, data about the GP itself, the deals that they're doing. So really start to think about how do I provide that context to AI, which means focusing on your data pipelines, focusing on where is that data coming from? How do I get that data normalized in cleanse? Having those firm level discussion about what data is important to us, not data is important to us. Then find the right partners that you can give that data to. Find that context to whatever AI they're talking about. So you have access to that data. You can get insights from that data. You can take action on that data without nearly the same overhead that you would have had. I can't talk to how many firms I go into and they say, "I'm in year seven of my data warehouse journey." And then the CEO says, "We've been working on it for seven years. We probably got another three years to go." And I go, "What are you building out the data warehouse for?" And they said, "Well, our head of IT and our CTO said that we need to have a data warehouse." I go talk to the CTO and they said, "CEO said I need to have a data warehouse." So not only do you have to think about context, you have to think about the end game and work backwards. What are the questions I want to have answered from my data? What can my data do for me? What's important data? What's not important data? So as you're building out these data pipelines, don't just do it for the sake of doing it. Figure out what is the end result? What is the end insight you need to have? What is the end action you want to come out of that? And work backwards from there. So you spend a lot of time with private markets, GPs in their offices. We have one customer constituency, which is the investment manager across all of private markets. We have another customer, which is an internal customer. And those are the teams at Juniper Square that do the fund accounting, the investor servicing, the compliance, the treasury, and you and your team and the engineering worker building tools to automate large parts of that process to make their lives better. So if you're a fund accountant out there doing things the old way, working at a legacy provider, but you're thinking about modern administration and trying to understand what Juniper Square does as a operations partner to private markets, GPs. What would you tell somebody if you were sitting with a candidate in an interview about why they should think about coming to Juniper Square? Yeah. So one thing that AI is doing universally is creating the need, the capacity to outsource into outsource at scale. It's going to create centralization. It's going to create a lot of scale when done correctly. And the way that it has done in the past is I'm going to scale by just hiring the most amount of people that I can and throw as many problems that I can and see how quickly I can get through them without burning them out. And maybe I'll burn some of them out. That's been the historical way this has done in the future when you think about outsourcing in the world of AI. It's keeping those people but using what they're best at, which is being an expert in the loop. Not just a person in a loop, but an expert in the loop. What does an expert in the loop mean? Means they're working with the right technology, the right AI agents, the right data to automate all of the things that AI is better at. There's a lot of things today, a lot of knowledge work that AI is not just a little bit better at than humans, but five, ten, a hundred times better at. And then you layer the right people on top of that to inform the AI, to give AI the context to improve the AI, to verify AI is doing everything the right way. Then they're using what they're good at. They're 20 years of experience dealing with very complex entity structures, dealing with different tax situations, helping to train the AI. Those are the things humans like doing. They also like talking to other humans. So working with our clients directly, figuring out what's the next problem they want us to solve as opposed to spending 20, 30 hours formatting a spreadsheet, that all goes away. So it elevates the person to work on the things that they're good at, to be the human in the loop and the expert in the loop as AI does more and more, but really to focus on that personal person to person connection that everyone will still want to build better outcomes, better scenarios, and better futures for them and the GP. Awesome. Thank you, Brandon. Great. Thanks for listening to the latest episode of the distribution by Juniper Square. If you like today's podcast, please share it with a colleague or a friend. And don't forget to subscribe and rate the distribution on Apple podcasts, Spotify, or wherever you listen to podcasts. You can connect with me on LinkedIn by going to www.linkedin.com/in/becedloff, or you can find me on Twitter @becedloff. You can also find a video recording of this conversation on demand at junipersquare.com/the-distribution. Until next time. (upbeat music)