Artificial intelligence tools are revolutionizing the way managers collect and use data. Juniper Square’s Brandon Rembe describes how.
As innovation in the artificial intelligence space—both in technology and how it’s used—continues apace, we caught up with Brandon Rembe, chief solutions officer at Juniper Square, to ask how private fund managers specifically are placed to adopt this new technology and where they might need to catch up.
Q. AI is reshaping all industries. Focusing on the private markets, how is it impacting managers and changing the way they work?
Brandon Rembe: AI is having an outsized impact on the private markets because segments like private equity, venture capital, and commercial real estate are all incredibly data-heavy asset classes that rely on analytics. Managers are handling information flowing in and out from several sources, including investments, interactions with LPs, and the market in general.
For most clients, data sits in a number of disconnected point solutions, excel files, emails, or PDFs. Very rarely is data held in something accessible like an application programming interface. Many of our clients have voiced how frustrating it is without a way to quickly access increasing amounts of data and easily structure it. This is an area where AI can have a meaningful impact.
AI is phenomenal at helping GPs move from collecting ambiguous, unstructured data to generating highly accurate, structured data that they can easily interrogate. In particular, the evolution of agentic AI, which is able to make decisions and take action to achieve goals with minimal human interaction, offers private fund managers the opportunity to offload basic tasks that don’t add immediate value. This allows the GP to focus on what really matters: building LP relationships, creating value in their investment portfolios, and generating returns.
Q. What’s an example of how managers are implementing AI?
Rembe: AI can create workflows from a variety of data sources, including unstructured sources like emails and other documents. A very common use case is ‘email-to-action’. For instance, an LP emails a basic request or question, and an AI agent reads that email, determines what is being asked, follows up if not enough information is provided, and then responds. Our internal analysis shows that AI can act on about 60 percent of requests. And, in those instances when it’s a complex question that requires some human interaction, processes are improving to make that human hand-off more interoperable. AI is not operating in a vacuum.
Q. AI innovation is accelerating—what’s on the horizon?
Rembe: The rapid change we are seeing in AI will have significant implications for how private fund managers are operating just two to three years from now. We see a world in which private fund CFOs, as well as other roles within a GP’s enterprise, will have a family of AI agents working alongside them to complete routine tasks while their focus shifts to more strategic topics. This will span any and every GP function—from fund administration to investor relations and reporting. Currently, only a few firms are positioned to adopt the level of innovation on the horizon. Those managers that are taking advantage of AI now will outperform those that aren’t. The gap is already
widening.
Q. What trends are driving AI adoption across private markets?
Rembe: A key one is the rise of the retail investor. Many of our clients are raising capital from different sources, including high-net-worth and ultra-high-net-worth individuals, forcing them to think about how they scale efficiently. How do you move from onboarding 50 LPs to 5,000? How do you turn a PDF subscription document into structured data to conduct efficient anti-money laundering and know your customer validation? AI can support this level of onboarding. In an environment where fundraising is challenging and will likely continue to get tougher, GPs are having to do more with less, and an AI assistant can help across the board.
Q: With such potential, what’s hindering AI implementation?
Rembe: We see that adoption differs across asset classes and depends on the size of a firm. For example, VC funds, many of which are investing in AI native tech companies, tend to be at the forefront of AI adoption compared to commercial real estate. And larger firms with the scale and IT capacity to embrace and implement AI in many areas of their enterprise are leading in adoption when compared to smaller firms.
Like with any new technology, there can be skepticism, fear, compliance, and security concerns, which are all valid issues. And rapid advances in technology make keeping up with the pace of innovation even more challenging. That’s why finding a partner is key. Many firms are unsure what questions to ask, what models to use, or what strategy to implement.
A partner with deep expertise in both AI and the private markets can help establish clear security guidelines and controls around the use of data, using very structured permission sets that determine access rights and roles, and evolve with private models that keep data siloed and inaccessible to public models.
Q: How does a manager go about finding such a partner to guide them?
They should look for a partner that is a thought leader in both the private markets and AI. Juniper Square is unique because we’re AI-focused and have been building a robust, trusted infrastructure of workflows and data for more than a decade—one where AI can be applied and trained to the nuance of the private markets and specific asset classes. Different AI models are better suited for certain use cases, and we spend a lot of time evaluating and fine-tuning models, including from a data security and privacy perspective.
We have found that generic AI can do a lot of things, but as you’re looking at specific use cases within fund administration or investor relations, for example, the models need to be trained very tightly and with a focus on accuracy. A partner that can work with you to not only personalize your AI strategy to the asset class you operate in—for instance, private equity, venture capital, or commercial real estate—but also to your firm, is critical.
A significant part of adopting AI also involves change management as businesses transform their workflows. Managers should pick a partner who can help them navigate that change and future-proof their technology while they get on with the business of investing and generating returns.
This interview was originally published in the PFCFO's 2025 Automation, Systems & Technology report.