In a candid conversation, EisnerAmper’s Alan Wink breaks down the slowdown in venture capital, the looming $3 trillion IPO pipeline, and why investors are pouring billions into AI, despite the hype.
By Kesav Dama
Alan Wink has seen every side of the capital markets. A classically trained accountant who spent a decade executing deals on Wall Street, he now serves as Managing Director of Capital Markets at EisnerAmper, one of the top 15 accounting firms in the United States. With more than 25 years at the firm, Wink has helped lead its consulting and capital advisory efforts across sectors like tech, life sciences, and private equity. In Part 2 of this wide-ranging interview with Kesav Dama, he discusses why even seasoned founders are struggling to raise money, why the IPO market remains frozen, and whether the surge in AI investing is built on real value or buzzword inflation. (Here is the first part of the series.)
In one of your recent articles, you wrote that first-time founders are having a difficult time raising money this year. Can you tell us why?
Alan Wink: It’s interesting—and I’ll clarify that a bit. It’s not just this year; first-time founders generally have a hard time raising capital. Most VCs and angel investors feel more comfortable backing a team that has done it before. There tends to be less confidence in first-time founders simply because they haven’t proven themselves yet.
That said, it would be remiss to focus solely on first-time founders. The broader fundraising environment is extremely tough right now. A big reason is that VCs are trying to preserve capital because the exit and M&A markets have been so slow. One of the biggest challenges for VCs today is the difficulty in returning capital to their limited partners. It’s a cycle—LPs invest in funds, expect returns, and then reinvest. But right now, funds are struggling to generate those returns, which is leading to a slowdown in new fundraising. So VCs are holding onto capital to support their existing portfolio companies.
It’s not an easy time to be raising money. That said, there’s always one important caveat: regardless of how good or bad the fundraising environment is, strong companies tend to rise to the top and find ways to secure funding. Maybe they don’t get the valuations they were hoping for, but good companies can usually raise capital.
At a macro level, people often talk about interest rates, tariffs, and similar factors. Are those really playing a role in the current funding environment?
Alan Wink: Yes, they are, but maybe not as much as some might think. I’d put interest rates and tariffs under the broader category of market uncertainty. And that’s really what we’re seeing—there’s a tremendous amount of uncertainty right now, both in public and private markets, about where things are headed.
I was listening to the news this morning, and President Trump had made comments about increasing taxes on Japan and Korea, as well as new tariffs on copper. Interestingly, those announcements didn’t have much of an impact on public markets. I think people have learned not to take everything the President says at face value. They know that in a few weeks, he might say, “We’ll extend the timeline,” or, “The tariff won’t be 100%, it’ll be 15%.” Markets have come to expect that kind of walk-back, so they aren’t overreacting.
That said, there is a kind of lull in the markets right now. Investors aren’t sure what direction things are going. And historically, when there’s uncertainty, markets tend to overreact. I think that’s exactly what we’re witnessing at the moment.
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The biggest impact is that this kind of market uncertainty really slows down the IPO market. One of the most interesting statistics right now is that the combined value of all venture-backed unicorns exceeds $3 trillion. That represents an incredible runway for future IPOs.
There are many strong, venture-backed companies that would have gone public already if the market were more stable. Once the uncertainty lifts, I believe we’ll see one of the most vibrant IPO markets in our lifetime. There’s a big backlog building.
Interestingly, many of these unicorns have continued to raise private capital while the IPO window remained closed. As a result, they’re far better prepared for going public than companies were in the past. These are businesses with real revenue, real customers, and a visible path to both profitability and scalability. So once the door opens, I think we’re going to see a very robust IPO market.
Why isn’t private equity stepping in and buying up these companies like they did in years past?
Alan Wink: It’s a good question, and I think the answer ties back to some of the same issues we’ve been discussing. Private equity firms are facing similar challenges: how will those deals be funded? What’s the cost of capital? Where are interest rates headed? Are we heading for a significant economic slowdown? There’s no clear answer to any of these questions right now.
Until there’s greater certainty and stability in the markets, I think deal activity—including private equity transactions—is going to remain slow.
And I’ll be honest with you, Kesav—I thought 2025 was going to be the year of the IPO. But that hasn’t materialized, and I don’t think it’s going to turn around dramatically in the second half of the year. Best-case scenario, we’ll see a vibrant IPO market in 2026.
In the startup world, AI is clearly a hot area…
Just one more factoid before we go forward. I think, so far this year, 33% or 35% of the deals that VCs invested in were AI and approximately 67% or 70% of the dollars went to AI-related companies. AI and machine learning. So if that gives you an idea of what they’re thinking about, it’s a very hot area.
There are a lot of investors who think that there’s a lot of AI hype these days. Do you share that opinion?
I do to a certain extent. I think everybody calls themselves an AI company today. And that’s a misnomer. I think VCs are starting to understand that they want to deploy capital in AI, but they want to make sure they’re investing in true AI companies, that they see a clear path to scale.
So how do you define a true AI company?
It’s not one thing—it depends on application. In drug discovery, AI can replace manual data collection and pattern recognition. In business, it can perform repetitive tasks currently handled by large teams. As a research tool, it’s incredibly powerful.
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But even with all that, we’re still in the early stages. From a VC’s perspective, they’re looking at AI companies the same way they look at SaaS businesses: Can it scale? Who are the customers? What’s the competition? What real-world problem does it solve—and is that problem big enough to build a company around?
Let me give you two examples: Glean and Notion. Glean was just a basic workspace tool, but after rebranding as “Glean AI,” its valuation jumped to more than $5 billion. Notion is now valued at $10 billion. These companies seemed to go nowhere until they added “AI” to their identity. How are those really AI companies?
It depends on how AI is actually being used. If you’re using AI to automate tasks, process vast amounts of data, or make intelligent decisions based on training models, that’s real AI.
AI can now sift through billions of data points and simulate the work of thousands of researchers. That’s powerful—but again, it has to be applied meaningfully. VCs aren’t investing in every startup claiming to use AI. They’re focusing on those where the tech is truly implementable and commercially viable.
A partner at a top law firm told me AI now lets him draft an S-1 filing in an hour—something that used to take a dozen attorneys. He’s actually scared for the next generation of lawyers. Another title attorney told me he can now process 100 title reports in a day with AI instead of one per hour. These are real productivity gains. So the question becomes: do fees go down, or do margins just go up?
That’s the million-dollar question, especially in professions that charge by the hour. If it used to take 30 hours to generate a contract and now it takes three, what happens to your billing structure?
AI is going to force a rethink of value-based pricing models in law, accounting, and other professional services. It’s no longer just about time—it’s about outcomes and insight.
Not AI-related exactly, but I recently looked at an investment in micro-GEO satellites. The old tech cost a billion dollars—these cost $80 million and can do the same job. With CapEx dropping while subscription fees remain the same, it creates a high-ROI opportunity. It made me think: if costs drop dramatically, are companies expected to pass on those savings—or just enjoy massive profits?
That’s a great parallel. And it’s the same in many industries—if you’re reducing costs by that much, what happens to pricing?
Look at the medical field. A doctor’s experience is usually limited to the patients they’ve personally treated. But with AI, they can access data from tens of thousands of similar cases. That leads to better diagnosis and treatment decisions—closer to “perfect information.”
I’m sure the life insurance industry is watching this closely. If AI increases life expectancy, their risk models could collapse.
Absolutely. It’s going to change every industry we touch on a daily basis. AI has that kind of disruptive potential.
If the lifespan increases, life insurance companies are going to do very well because people are living longer. However, the annuity portion of it, they’re going to say “Oh, I have to keep on paying these people, and they were supposed to die 10 years ago.”
You just better hope the stock market continues to perform so their investment portfolios grow at the same time.