AI, Private Capital, and the Future of Finance

Chicago Booth’s 72nd annual Management Conference in April featured a panel moderated by Yueran Ma, Carhart Family Professor of Finance, with perspectives on investment banking from industry experts.

Panelists included: Scott Adelson, MBA ’87, CEO of Houlihan Lokey; Timothy George, AB ’74, MBA ’75, vice chairman and managing director at RBC Capital Markets; Melissa Knox, MBA ’05, managing director and global head of software investment banking at Morgan Stanley; and Cary Kochman, MBA/JD ’90, recently retired as sole head of the global M&A group and chairman of the Chicago office of Citi.

Read an edited transcript of their conversation below.

Ma: What determines the potential size of the private-credit markets? What are their limits? What can they do? What can they not do?

Kochman: Private-credit funds are going to morph into private equity on the bankruptcies or the restructurings. These small groups of holders will potentially effectuate almost prepackaged-type solutions. They are intimate with these credits and prepared to actually operate these businesses. That is going to be at the cost of traditional private equity. It’s why traditional private equity is now acquiring private lending businesses.

Knox: We saw this happen with one of our clients, a portfolio company of a private equity firm. A downturn affected its ability to service its debt, and the company was eventually turned over to its direct lenders, who are now operating the business. Today, these lenders are running a multibillion-dollar software company, and this isn’t their area of expertise. I’d never seen anything like this, but I assume it will begin to happen more and more as direct credit becomes a larger source of financing.

George: I’ve only been at RBC since the beginning of 2025, and before that I spent 29 years at two different boutique firms. For the past 29 years, and particularly in the last 15 years at Lazard, we were primarily advising clients on M&A transactions and then introducing those clients to the private-credit markets to finance their deals. And now suddenly I’m seeing the various capital markets from the perspective of a significant-balance-sheet bank.

What is clear to me is that there is a robust market for public and private credit, and that there will be certain credits and transactions that go to the syndicated-bank loan market, and others that will go to the private-credit markets. These two markets will coexist, and these two markets are going to continue to grow.

Adelson: Large depository institutions have people who take the CFO out to lunch and build relationships. In private capital, it’s different. It’s opaque. Most of you couldn’t list 20 names in private capital. There are hundreds of providers, and within those there are different pods, each of which behaves differently. Accessing that capital is a different process. It has a much lower cost structure on the lender side than a depository institution. They’re different models. One’s not better or worse. I agree they’re going to coexist. Private capital will continue to grow around the globe. It’s relatively new here and in its infancy in the rest of the world, and there is absolutely demand and need for more flexible capital than depository institutions are able to provide.

Ma: How do you see AI affecting financial services?

Knox: I get asked a lot: Will there be disruption in this industry because of AI? Will we need analysts anymore?

There’s a lot of grunt work in banking, and AI can only make us more productive. We’re using AI at Morgan Stanley in a couple of different ways in private wealth management. It records calls and comes back with the best actions and recommendations for retail clients. We have a ton of research from our analysts, so if you have a question about data, it can bring you their findings. And we will see AI putting comps together and pulling from earnings transcripts—things that should be automated.

AI technology is developing faster than companies can adopt it. Finding the application, the use cases, doing everything you need to do to bring it in—we’re not there. At Morgan Stanley, we have two use cases for OpenAI throughout the entire bank. So it’s going to take a while for the technologies to get implemented. A lot of the funding now is going to infrastructure: training the models and getting the chips. Eventually that will even out. The production costs will come down, the large language models will become more commodified, and it’ll become only a question of how you use it. That’s where the biggest opportunities are in financial services.

Adelson: The advisory side of investment banking has always been about people, not information. It’s a little different in sales and trading. And that, in my mind, is the first piece.

Take Moderna, which started as a large data company. They develop drugs, take an enormous amount of information, and feed it into LLMs—but Moderna was configured to deal with that. None of the businesses on the advisory side were set up for an LLM world. They were set up for a world where important people with tremendous judgment and insight sit down with clients and provide insights. That’s the whole business model. That is going to evolve.

We are in the process of organizing that data and thinking much more like a data company. We’re fortunate that the volume of transactions we do is statistically significant—we have enough deals to be able to make better decisions on behalf of our clients and ourselves. But before you can utilize that in an AI-driven world, it needs to be set up, and it all starts with that foundational data. Realistically, lots of people are looking for ways to use it today to get quick hits that are useful for an analyst. But the meaningful information is when you actually organize significant datasets that help you find things you would never be able to otherwise.

You have an advantage if you’re big—because you have proprietary datasets—or if you’re very small. The people in the middle are in a world of hurt.