6 Essential Lessons Fund Managers Can’t Ignore: AI, Private Credit and the New Investment Reality

December 3, 2025

AI, private credit and venture capital may look like separate stories, but they’re part of the same risk cycle. These six takeaways distil what I heard in Miami into practical prompts for fund managers rethinking strategy, liquidity and technology for 2025.

AI trends, venture capital insights and private credit are at the center of a quiet shift in how fund managers think about risk, opportunity and the shape of markets in 2025.

These changes are pivotal for understanding fund managers insights in the context of evolving investment strategies, particularly as they adapt to new challenges and opportunities.

The worlds of technology and finance are often portrayed as a relentless march of progress, a place of straightforward innovation and explosive growth. We read headlines about the AI boom and multi-trillion-dollar private markets, and it’s easy to believe in a simple, upward trajectory.

Behind these buzzwords, however, lies a more complex reality. To uncover it, I recently listened in on two distinct, high-level discussions: one with venture capital insights on the front lines of the AI revolution, and another with specialists managing the colossal, and often misunderstood, world of private credit.

What emerged was a fascinating picture of two interconnected universes, where the problems in one sphere are creating massive opportunities in the other that reflect key fund managers insights as they navigate these changes and seek to leverage them effectively.

This article pulls back the curtain on those conversations. It shares six counter-intuitive takeaways that challenge conventional wisdom, revealing the surprising parallels, hidden dependencies, and historical echoes that truly shape where technology and capital are headed next, providing crucial insights for future investments that are essential to understanding market dynamics.

The current frenzy around Artificial Intelligence feels unprecedented, but for seasoned investors, it’s a familiar story. At a recent venture capital forum, one speaker drew a striking parallel between the AI landscape and the search engine wars of the late 1990s. Back then, billions were poured into early platform companies like Alta Vista, Excite, and Netscape, believing they were the unshakeable foundation of the internet. Most were decimated.

Raju Rishi from  RRE Ventures recalled the moment vividly:

And there’s an article in the paper and I remembered fondly. It said the search engine wars are over. Alta Vista has won. And that was a year before Google came out and Google came out with page rank and an adtech model and decimated everyone.

This historical perspective exposes critical vulnerabilities in the current AI space. Massive valuations—totalling over $600 billion for OpenAI and its competitors—are being assigned without a proven, scalable business model comparable to Google’s revolutionary ad engine. Furthermore, the entire ecosystem is being subsidized with artificially cheap “tokens” used to access the AI models.

fund managers insights at venture capital and private credit events

This is akin to a new factory offering free electricity to its first tenants; the businesses look profitable now, but their models are built on a subsidy destined to disappear. This sobering counter-narrative suggests that while the opportunity in AI is real, a painful shakeout may be inevitable.

Private credit and direct lending are now core components of sophisticated investment portfolios. What’s surprising is that this multi-trillion-dollar industry owes its existence to the last great economic meltdown. It emerged directly from the ashes of the 2008-2009 financial crisis.

As credit professional Alexander Hughes of Vista Credit Partners explained at a recent CFA dinner on alternative investments, sweeping reforms like the Dodd-Frank Act and Basel III required traditional banks to hold more capital and restricted them from making certain types of corporate loans. This created a massive vacuum in the market, leaving many businesses without access to capital.

Direct lenders stepped in to fill this void. By removing the traditional bank intermediary, they created what Hughes called a “farm-to-table” model for corporate lending, connecting capital providers directly with companies. It’s a profound irony that an asset class now prized for its stability and returns was created as a direct consequence of fixing the systemic failures of the previous financial era. 

For an in-depth explanation of how private credit has evolved, the CFA Institute provides a detailed overview

For decades, Silicon Valley was the undisputed centre of the tech universe. But a new playbook has emerged for creating vibrant tech hubs, and it’s less about engineering talent and more about engineering a desirable environment. New York City provides the blueprint. Its rise was fuelled by proximity to customers in fintech and adtech, aggressive programs like “Startup New York” that offered years of tax breaks, and technology shifts like AWS that freed companies from being tied to a specific location.

Miami is now following a similar trajectory, leveraging its own tax advantages and quality-of-life appeal. The next wave of decentralization, however, will be accelerated by AI. This shift is less about “vibe coding” and more about “vibe engineering”—creating an environment where founders want to live. As AI tools handle more routine software development, the need to co-locate large teams of engineers diminishes. The future of tech hubs isn’t about recreating Silicon Valley’s talent density, but about creating a place where leaders can build great companies from anywhere.

While media attention is fixated on venture capitalists (VCs) funding the next billion-dollar idea, the industry’s most pressing problem is far less glamorous: the lack of exits. The pipeline for initial public offerings (IPOs) and major M&A deals has been drying for years, creating what one VC called a “backlog of no exits.”

This has serious consequences. Limited Partners (LPs)—the institutions that invest in VC funds—haven’t gotten their money back from investments made a decade ago. The numbers are stark: according to data from Carta, 26,000 entities made a VC investment in 2021. Last year, that number plummeted by 60% to just 10,000. This capital logjam makes it harder for VCs to raise new funds, which means less capital is available for startups. The central challenge in venture today isn’t a shortage of innovation, but a shortage of liquidity.

This logjam in venture capital isn’t just a problem for startups; it’s a key reason why institutional investors are increasingly turning their attention to an entirely different part of the market—one born from the ashes of the last financial crisis.

Beyond the pitch deck and financials, early-stage investors are scrutinizing something much more immediate: a founder’s speed of execution. This evaluation begins the moment an interaction starts, serving as a critical proxy for their ability to lead a fast-moving company.

According to Mark Volchek from Las Olas VC, if a founder takes three days to respond to an email, it’s considered “too slow.” He shared an anecdote about moving to Miami from New York: after asking for something by Friday, he was asked, “which Friday?” It was a stark illustration of differing paces. For VCs operating at the speed of the tech world, the expectation is absolute. As the investor put it: “we don’t measure things in days.”

This focus on responsiveness isn’t about impatience; it’s a form of real-time due diligence. For investors, observing a founder’s work ethic and ability to execute quickly on small tasks is a powerful indicator of how they will perform when the stakes are much higher.

In investing, liquidity—the ability to sell an asset quickly—is almost universally seen as a positive. But in the world of private markets, a lack of liquidity is considered a feature, not a bug. Investors are compensated for giving up the ability to sell instantly with an “illiquidity premium,” which translates to higher potential returns.
This structure provides a powerful, built-in discipline that prevents panic selling. As one expert noted, the premium “pays the highest when the market drops” because it forces investors to hold on through volatility. Duy Nguyen from CAIS Advisors drove this point home at the CFA dinner when describing his duty to clients:

…if you want it when everybody else wants it, it’s probably my fiduciary responsibility to not give it to you because when you’re in these private credit instruments, what you’re doing is you’re harvesting a liquidity premium.

This perspective fundamentally challenges the conventional wisdom that more liquidity is always better. By locking up capital, investors are protected from their own worst impulses, allowing them to ride out market cycles and fully capture the long-term returns they were promised.

The overarching lesson from these discussions is clear: the worlds of venture capital and private credit are deeply intertwined. Looking past the hype reveals a more nuanced picture, where the VC industry’s liquidity crisis fuels the private credit boom, and where lessons from the dot-com bust provide a critical lens for today’s AI gold rush. Real insight isn’t found in the headlines, but in understanding the hidden machinery of the entire capital ecosystem.

As technology and markets continue to evolve, the most valuable skill will be the ability to see the connections that others miss. So, as you look at your own assumptions, which two seemingly separate worlds might be more connected than you think?

If you’re exploring how these themes translate into systems and vendor choices, our Systems Selection page walks through the typical decision process for fund managers.

At FinTech4Funds, we specialize in helping fund managers make sense of an increasingly noisy Technology landscape. Whether you’re considering an off-the-shelf platform or a more bespoke stack, we act as an independent guide — steering you through the crowded market of vendors and system providers to the solutions that truly fit your needs.

Our work always starts with understanding your firm: your investment style, operating model, regulatory footprint, and growth plans. From there, we map out the requirements, shortlist credible providers, and pressure-test each option against real fund-management use cases. The goal is simple: to help you choose technology that boosts operational resilience, supports investor confidence, and stands up to regulatory and institutional due diligence—not just this year, but over the next market cycle.

Because we’ve seen what can go wrong with poorly chosen or poorly implemented systems, we put a lot of emphasis on helping clients avoid the usual traps: hidden complexity, misaligned features, weak data foundations, and “demo-ware” that doesn’t hold up in production.

To support fund managers beyond 1:1 engagements, we also share our thinking openly through our blog—covering practical frameworks, vendor landscapes, and lessons learned from real projects.

If you’d like to go deeper, you can access our free publication, Fund Managers’ Guide to Asset Management Systems, via the blog. It’s designed as a practical companion for fund managers who want to navigate systems selection with more structure, more confidence, and far fewer costly mistakes.

Our approach involves a detailed assessment of your specific needs, followed by the identification and vetting of suitable technologies. Whether it’s enhancing operational efficiency, improving investor relations, or ensuring compliance with regulatory standards, FinTech4Funds is equipped to assist you. Check out our free guide on how to find the right solution for your Fund that not only meets your current needs but also positions you for future success.

Elena Aono
Founder & CEO, FinTech4Funds
Helping fund managers navigate the noise of FinTech and find systems that actually fit.

  • Investment Management
  • private credit
  • venture capital insights
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