Leveraging Generative AI within Private Equity: Insights from Alex Chitea, CFA, Founder and Managing Partner of Funston Capital

On this episode of the CFA Society San Francisco Podcast, we had the pleasure of speaking with Alex Chitea, CFA, Founder and Managing Partner of Funston Capital, an entrepreneurial investment fund. 

Prior to founding Funston, Alex led the programs and startup partnerships for cybersecurity and identity at Orange Silicon Valley - a subsidiary of Orange, a French multinational telecommunications company, that collaborates with startups, investors, researchers and other partners to bring innovation to the group’s operations around the world. He started his career as an early employee at Google and also held an intrapreneurial role at The Walt Disney Company. Alex holds both a Bachelor’s and a Master’s degree in Computer Science and an MBA from The University of Chicago Booth School of Business.

Listen to the full interview, where Alex discusses leveraging generative AI within private equity. Our conversation delves into the transformative impact of AI on small and medium-sized businesses within the private equity market, and how it's shaking up traditional approaches to due diligence, operational efficiency, and beyond. Alex shares his experiences and strategies for harnessing AI to drive business growth, enhance investor expertise, and unlock new avenues for value creation. 

If you'd like to learn more about the show, have a topic or speaker to suggest, or would like to leave us a comment, email podcast@cfa-sf.org.


This podcast is produced by CFA Society San Francisco, a not-for-profit professional association, providing professional learning and career resources to over 13,000 investment industry professionals worldwide. To learn more about CFA Society San Francisco, visit our website or connect with us on LinkedIn.

The information contained in this podcast does not constitute financial or investment advice. Please consult your own financial advisor for information concerning your specific situation.

Transcript

Lindsey Helman: 0:06

Hello and welcome to the CFA Society San Francisco podcast, where we interview and discuss trends with leaders from across the investment and finance industry. This month, our host Tanya Suba-Tang, membership Director with CFA Society San Francisco, had the pleasure of speaking with Alex Chitea, founder and managing partner of Funston Capital. Listen in as they discuss leveraging generative AI within private equity.

Tanya Suba-Tang: 0:34

Alex, good morning. Great to see you again. How are you?

Alex Chitea: 0:37

Good morning. I'm great, Tanya, great to see you again.

Tanya Suba-Tang: 0:41

Thank you so much for joining for today's today's podcast. For listeners, I'm so excited to have Alex because he is managing partner for Funston Capital, and Funston Capital is a entrepreneurial investment fund correct, where you source, acquire, and operate a tech company.

Alex Chitea: 0:59

Yes, that's right. Pleasure to be here.

Tanya Suba-Tang: 1:00

Yeah, and you know - such an interesting background you have, Alex, because you've had roles in your career early on at Google and Walt Disney Company. That's so impressive.

Alex Chitea: 1:10

Yes, thank you. Thank you so much.

Tanya Suba-Tang: 1:12

So kind of jumping into our questions, you know, having just mentioned those two companies, you started your career in technology and invested in venture capital and are now focusing on the SMB private equity market. So what is it that interests you most about this market?

Alex Chitea: 1:27

Yeah, as you mentioned, you know, my career spanned both operations and investing roles before I decided to focus on the SMB private equity market and right now I got to a point where I'm looking to bring the two operations and investing capabilities by acquiring and growing a tech or tech-enabled company. So I'm looking at companies that have a history of stable recurring customers and predictable cash flows, and those companies exist in the sort of SMB space in the private equity market and that market has historically had strong returns and robust deal flow within the SMB market and the companies are typically very attractive to private equity for those reasons. They are, generally speaking, companies that are lesser known, less established, so they have the potential for market and valuation inefficiencies that can eventually translate into solid returns for private equity portfolios. So, generally speaking, because we're looking at this, less efficient markets and valuations below those of larger buyout deals and public comparables sponsors can typically acquire SMB companies at relatively lower valuations.

Alex Chitea: 2:37

So, because of that we are able to sometimes employ a more conservative capital structures, so that opens up multiple routes to actual value creation at the end, including organic revenue growth, operational enhancements, add-on acquisitions and managerial improvements, just to name a few. And many of these lower middle market companies, they are quality businesses but oftentimes they've been either neglected or they have underdeveloped IT or quality. You know, management, information systems and those risk reward dynamics have historically contributed to really good, strong returns in the SMB market over the long term for private equity.

Tanya Suba-Tang: 3:16

So, with the technological advancements of the last decade, what has surprised you the most about how private equity is adapting?

Alex Chitea: 3:23

Yeah, that's a great question.

Alex Chitea: 3:24

So we've all witnessed generative AI and I think that's the talk of the town these days and that has emerged as a transformative force within the worldwide economy since ChatGPT launched in late 2022.

Alex Chitea: 3:37

We had that initial excitement, but afterwards we really have been able to mine certain consistent depth of content and substance that has actually attracted the attention of private equity investors. So, if I can just take a quick step back and frame generative AI for our listeners, essentially for private equity and for small businesses, generative AI serves as a crucial reasoning engine that's capable of participating in open-ended dialogue with customers. You can create a persuasive marketing material, you can scrutinize vast data repositories that can provide deep insights, and all of these little things are valuable business tasks that can help private equity investors be more efficient in their jobs and help with their portfolio companies at the same time. So I guess what we've seen, you know what's surprising is the speed at which this private equity forward thinking private equity investors are actually starting to already harness generative AI capabilities to revolutionize their portfolio companies on the one hand, enhance their due diligence processes and also augment their expertise as investment professionals and also augment their expertise as investment professionals.

Tanya Suba-Tang: 4:46

Yeah, it's really interesting. So how are investors leveraging generative AI within private equity?

Alex Chitea: 4:54

Yeah, I'd say savvy investors are already using these technologies to sort of transform companies, make better decisions and boost returns. If I were to bucket the way firms are mobilizing this technology, I would say within the portfolio, during the due diligence process and then at the firm level, and I can go into each of these important ways. So, within the portfolio, we see some key questions that private equity firms need to consider when it comes to their companies and specifically, they need to understand how generative AI innovations can disrupt the portfolio company's value chain or business model. There are companies that are going to thrive in this new environment and there are companies that are going to be significantly affected or altered by the generative AI technologies. So is there an opportunity to spearhead change through this technology, right. Will generative AI enable new competitors and how will the competitive modes or barriers to entry be affected to protect against this disruption? So, in general, we see private equity firms must work with their portfolio companies to test and learn how to address these questions and, most importantly, understand sort of what works and what doesn't in a very iterative and very, very fast way. And then, once they do that, they should be able to prioritize investments accordingly. So that's within the portfolio, right? So at the portfolio company level, during the due diligence process, the investment professionals, at private equity terms, they can do quick analyses of any target company, right? So there's, you know, almost like a scorecard-based protocol with respect to generative AI and how generative AI will impact the companies that they would like to invest in. So they need to do that to evaluate the threats and opportunities presented by the technology. So we believe that over time, you know, this assessment is going to be normalized, similar to how we currently have legal or commercial due diligence practices, right so we also see firms that are leveraging these tools, ai tools, to expedite and refine the underwriting process, right. So generative AI offers a distinctive chance to sort of develop these prototypes, due diligence and sort of validate or refute certain hypotheses, prototypes during due diligence and sort of validate or refute certain hypotheses. So we're seeing many firms sort of adopt that during the due diligence process to kind of swift, you know, sift through their companies better and their investment targets better.

Alex Chitea: 7:19

And lastly, I would say, at the firm level, you have generative AI providing numerous avenues for streamlining or automating back office operations, right. So you know, within deal sourcing, there are a lot of menial tasks that can now be easily performed through AI tools. So we're seeing the true potential in significantly broadening the information accessible to these investment decisions. Right? So you have these tools that are ideal for scanning massive data pools, for insights. So the investment professionals are not going to necessarily be turning to robo-advisors or robo-investors, but they will be able to use their time more effectively after dealing with the output of these tools and using screening criteria and so on and so forth. So there will be a sort of supercharging of the investment professional, if you will, across the full value creation cycle, from sourcing, screening diligence all the way through portfolio management and helping the companies all the way to the exit. So I'd say those are the three most important ways. We're seeing technology sort of trickle its way down into private equity firms and eventually in the larger economy.

Tanya Suba-Tang: 8:24

So kind of taking the flip side, what are some pitfalls of deploying generative AI?

Alex Chitea: 8:29

I would say you know the pitfalls are general technology pitfalls. Right, Focus is essential. Right Like you want to direct investments towards select strategic or operational goals. Right Like you can. Ideally you'd like to have some tangible enhancements in profitability. So you have to do that really good match between the investment and your goal.

Alex Chitea: 8:52

Like any technology, generative AI is a tool and it's best deployed in service of strategy and not vice versa, and doesn't create value by itself. So you have to explicitly link it to measurable business objectives. So these objectives, you know, we've heard them, they're sort of everywhere in the press things like better serving our customers. You know understanding the metrics that we're trying to move, understanding the processes that we're trying to improve and then sort of the people that we're trying to make more efficient. You know customer service is thrown around a lot, so you need to sort of understand, you know the business objectives and then deploy the technology accordingly. You know the business objectives and then deploy the technology accordingly.

Alex Chitea: 9:33

A lot of investors are asking themselves already what the ROI on generative AI is right so they can understand intuitively that there's the potential for productivity gains. Right, there's, you can determine a clear return on investment. Determining a clear return on investment is actually pretty difficult because there are many benefits that have some indirect or non-financial impact. So, although you kind of understand the productivity gains, it's really hard to understand sort of the future financial outcomes. I'll give you just a quick example like utilizing generative AI to automate code generation, which is pretty. One of the first use cases could enhance software developers' productivity, allowing more time for innovation and potentially speeding up the time to market for new features. However, ultimately and ultimately this would lead to improved customer satisfaction. But quantifying these benefits in financial terms and actual bottom line is a challenge and remains a challenge.

Tanya Suba-Tang: 10:26

So, Alex, I know you have a busy day, but before you leave me I have to ask given your background in technology, what are trends or disruptions can we expect over the next decade?

Alex Chitea: 10:37

Yeah, it's really hard to venture an answer for the entire decade, as technology is developing at ever increasing speeds.

Alex Chitea: 10:45

I would also say that you know, when experts and people in general try to forecast the future, we tend to extrapolate the past, whereas we've seen with entrepreneurs, they invent the future that they personally envision. So there's usually a disconnect between the two. But with that caveat out of the way, I would say that AI in general and you know, here we can include the current generation of large language models, deep learning, et cetera, but also other paradigms that might actually emerge in the next decade. So AI in general will continue to shape businesses and, more broadly, society at large, and that will have an impact on the private equities bottom line. We are at the beginning of the S-curve for this new technology and we still have quite a long way to go until it's fully deployed and implemented, until it sort of works its way through all the processes in society. So what's already apparent is that we have this sort of marginal cost of knowledge that continues to drop and perhaps in the near future we'll reach a point where expertise will be nearly free. So you know that the proverbial intern like we all hear this phrase over and over again how generative AI is like an intern that never tires, so that that cost of knowledge, you know, will continue to drop and I do believe at some point expertise will be free. So it's going to be interesting what you know knowledge worker is going to do in that scenario.

Alex Chitea: 12:04

We're also seeing a really interesting intersection of AI and generative AI, specifically with robotics. That speaks to the marginal cost of labor that might eventually move towards zero as robotics and AI come together. We are seeing some, you know, demos online and in some Amazon warehouses where you know they're sort of using certain robots for certain tasks like packaging, et cetera. So, yeah, so I would say the marginal cost of knowledge and marginal cost of labor moving towards zero are going to have a great impact on, you know, businesses and society and eventually, you know, by extension to our discussion, they will have an impact on private equity as an asset class. So, yeah, I would say we're still in the early days. There's definitely a lot of time left to start adopting these AI-enabled tools.

Alex Chitea: 12:53

So, I hope that people are not going to be afraid and they're going to sort of try to start testing and learning and harnessing data and information in powerful new ways.

Tanya Suba-Tang: 13:03

Wow, I mean that's exciting, exciting things happening in our future, right?

Alex Chitea: 13:07

Yeah, absolutely, I'm super excited about the future.

Tanya Suba-Tang: 13:10

Yeah Well, Alex, thank you. Thank you so much for your time today. I know our listeners probably gained a wealth of knowledge on generative AI and how it impacts private equity, so thank you so much for your time, and I hope you'll join us again for maybe an update on what's happening in the industry.

Alex Chitea: 13:27

Absolutely, it would be my pleasure, thank you, Tanya.

Lindsey Helman: 13:32

Thank you for listening to this month's episode of the CFA Society San Francisco podcast. We hope you enjoyed the engaging discussion. Join us next month for another new episode. This podcast is produced by CFA Society San Francisco, a not-for-profit professional association providing professional learning and career resources to over 13,000 investment industry professionals worldwide. To learn more about CFA Society San Francisco, visit our website at cfa-sf. org or connect with us on LinkedIn.