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    Home > Investing > Private Equity Needs AI Advocates
    Investing

    Private Equity Needs AI Advocates

    Private Equity Needs AI Advocates

    Published by Wanda Rich

    Posted on December 8, 2025

    Featured image for article about Investing

    This article was written by Rohan Parikh, Co-founder & CEO of Keye, the first AI platform built exclusively for private equity. Keye understands the data, performs real analyses, and mirrors the workflows of top-performing deal teams. For more information, visit https://www.keye.co/


    PE firms have plenty of AI demos and pilots, all promising faster diligence and instant EBITDA lift. In my experience, the problem is most of them fail when people try to use them in their actual daily work. In other words, when an investment team member applies AI and is up against messy data, tight deadlines, auditing requirements (i.e., the messy reality of how deals actually get done) the tools fall apart.

    That gap isn’t purely technical; it’s organizational. I’ve observed that making AI work depends on ownership, incentives, and behavior change—three things models can’t fix. No one is clearly accountable for outcomes across deal, ops, and portfolio finance. Incentives reward speed and heroics, not process changes that pay off next quarter. Workflows live in email and spreadsheets, so context is tribal and brittle. Compliance is treated as a late-stage gate instead of a design constraint. And change management is under-scoped; firms roll out a tool but don’t rewire who decides what, when, and on which signal.

    Closing this gap requires internal champions who can advocate and scrutinize at the same time, and who carry a concrete plan to reshape behaviors across teams. From what I’ve seen, without this role, AI will remain a parade of proofs-of-concept. With it, AI becomes a repeatable capability that improves underwriting discipline and portfolio execution.

    Defining the Right Champions

    After working with over 50 funds at this point—either piloting or using the product—I've come across various types of AI champions. Not everyone works out, and honestly, even PE firms themselves are still figuring out the right profile. But I've seen some common characteristics that matter.

    No doubt they need a deep understanding of the problem. But it takes more than that. In my experience, given how nascent this technology still is, the champion needs to push as hard as the external founders building the company.

    A true AI champion should display all of these capabilities:

    1. They believe in the technology. I mean really believe in what it can deliver and share a similar vision with the founders about its potential. I’ve seen that even one small doubt can poison a pilot. They have to see it.
    2. They understand internal channels of communication. Think about new technology like a B2C app—virality matters. A light-bulb moment really matters. This is where champions come in. Either they create that virality themselves, or they put the platform in the hands of people who can. I've seen this play out many times: one associate or senior associate uses the platform for 20 minutes, saves hours of work, jumps onto the common associate WhatsApp chat and creates natural buzz. And the firm never looks back from that moment. A champion either needs to be that buzz creator, or the one who sets up the channels where people can voice their opinions and share wins.
    3. They can present findings to senior leadership. Ultimately, you might believe in the vision, but you probably don't have final decision-making power. So the same way founders got you on board, you have to get the team—and ultimately the decision makers—on board. No easy feat. I note that someone needs to deeply believe that the change they're about to propose is worth the disruption.
    4. They're heavily motivated—often even incentivized—to manage change. This can't just be a side project. It needs to matter to their role and their success metrics.

    We've seen champions across the board. The enthusiastic, tech-savvy associate. The Partner who still enjoys working through spreadsheets himself and running through questions with associates. We've seen them all. But they share similar traits: understanding the big picture while getting into the nitty-gritty details of the solution, and knowing what's needed for internal execution.

    Empowering the AI Champions

    Finding the right champion is half the battle. The other half is giving them the space and support to actually do the job. Based on what we’ve seen across funds, a few things really matter.

    Make it part of their official job.

    One of the clearest patterns we’ve seen is where the firm literally bakes AI into someone’s mandate. Not “play around with this when you have time,” but: 25% of your time is going to be on testing AI and pushing AI initiatives. That can be fully dedicated, or split—50% on the deal team, 50% on trying out AI and pushing projects internally. The key is that there is a real resource allocation. It becomes official. It’s now their job to go find the right tools and push them through the firm.

    In a lot of funds, that’s hard because associates are swamped and jumping across deals. But when you don’t formalize it, the work becomes a side project and it never really lands.

    Give them real incentives.

    Another thing we’ve seen is tying this work to upside. Some firms literally have a structure where, if you recommend a tool and champion it internally, and it actually gets adopted, you get paid for it. It might be a bonus, it might be a couple of grand, but the point is: it’s not just “nice to have.” In my experience, when the firm says “we’re willing to pay for this,” it changes the way people show up.

    Make it crystal clear this is coming from the top.

    This is one of the biggest hidden blockers. A lot of associates don’t actually know that it’s important for the fund to use tools like this. They worry that if they spend time on AI when a tax memo or model is due, they’re going against the objective of the firm.

    So they hold back.

    What we’ve seen work really well is when it’s obvious this is coming from the top—from MDs and principals who are saying, we want you to go find these tools and we’re backing you. It can’t just come from a CTO sitting on the side. It has to come from someone the champions report to directly or indirectly. Once that happens, the champion isn’t second-guessing whether they’re “allowed” to do this. They know it’s part of the job.

    Use AI as a visibility engine, not just a productivity tool.

    Another underrated piece: AI and tooling have become a topic at Investment Committees and partner meetings. For an associate or analyst, that’s a huge opportunity. If you’re the one championing a tool, you might be the one creating the deck and presenting to the whole partnership.

    We’ve seen this play out. At one fund, the person we work with ended up presenting directly to the co-head of a $100B platform—someone he would otherwise never meet at that stage in his career. From what I’ve observed, that kind of exposure is rare. When firms encourage this, AI champion work becomes a way to get in front of senior leadership, not just a back-office task.

    Wrap it in a structured process.

    Finally, process matters more than people think. One of the best examples we’ve seen was a fund that was so structured we barely had to do anything. They knew exactly how they wanted to run it. They put out an RFP with clear use cases. We responded. They came back with a timeline—here’s when we’ll test, here’s when we’ll decide.

    Once you set that timeline up front, everyone has to adhere to it—principals, IC, the champion, the vendor. The whole thing runs much smoother and decisions happen faster. You’re not stuck in endless “let’s revisit this next quarter” cycles.

    Where PE Goes From Here

    The technology will keep improving. The question is whether firms build the internal muscle to actually use it. In my experience, that muscle is the champion: someone with the role, support, and structure to push AI through all the friction of real workflows. Name that person, back them, and give them a process—and AI becomes a capability instead of a science project.

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