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Episode Description

In this webinar recording Third Bridge's Co-founder Joshua Maxey, TMT veteran Scott Kessler, and Mergermarket’s Senior PE specialist, Harriet Matthews unpack the trends reshaping the PE industry and take a deep dive into AI investing.

Episode Transcript


DT: Good morning, good afternoon, good evening, depending on where you’re joining us from but a very warm welcome as always to today’s event. 

On behalf of Third Bridge, I’m thrilled to welcome everybody today where we’ll be doing a deep dive on critical private equity trends including need-to-know AI investing. As some of you will remember back in July we published our US private equity report. This looked at how senior executives within the private equity industry were planning for the year ahead. Questions included fundraising, deployment, debt financing some of the advantages of size and scale, and of course the use of technology which is going to be the subject of much of the discussion today. 

One of the headlines interestingly enough that came out of the report was that despite having the widest bid-ask spread, tech and specifically artificial intelligence is attracting a high level of PE interest. I think we’ve all you’ve all seen that, and as such, you know a webinar was born. So over the next 45 minutes or so we’ll be giving you a whistle-stop tour through said report and also unpacking some of those trends that are impacting the private equity industry today. 

As far as introductions go, my name is Dan Thomas, I’m a sector analyst here at Third Bridge. I’m joined live by Harriet Matthews, Funds Editor at Mergermarket. 

HM: Hi Dan, thank you for having me thank you for hosting, and hello to everyone watching online. 

DT: Joined by Scott Kesler, Global Sector Team Lead for TMT here at Third Bridge. Hi Scott. 

SK: Hi Dan,  thanks for having me today. 

DT: And joining us remotely Joshua Maxey, co-founder and Head of Corporate Development here at Third Bridge. Josh, thanks for joining us.  

JM: Thank you Dan, pleasure to be here. 


DT: Actually we can just jump straight in with our questions. Joshua, Harriet, given your respective vantage points, obviously Harriet, coming from a background at Mergermarket, having reported extensively on secular trends within the private equity industry and you know LP and GP profiling, Joshua Maxey, you’re obviously Head of Corporate Development here at Third Bridge and you speak daily with senior executives at our largest private equity clients.  Joshua, perhaps you could just comment on some of the key takeaways, some of the things that stood out to you most from our report.  


JM: Thank you Dan and very nice to be part of this panel today. I think there are a few interesting trends in the industry right now that I’m certainly hearing from our clients. 

First of all, the deal pipeline is very full, and if you think about Apollo’s May earnings results, they stated that their deal pipeline was 3x on the same time last year. There is there’s an abundance of deals, and the private equity industry is very busy trying to find you know solutions to unlocking some or catalysts that will unlock some of these deals and I think that’s the biggest issue facing this right now. It’s not so much about the absolute interest rate, it’s more about the volatility in interest rates and looking at some level of stability to where people can price risk and that has been one of the biggest issues that the industry has. The debt financing market has certainly gone through a very quiet phase. That said, there are certainly positive signs on the horizon. 

We’ve certainly seen in August a pickup in demand again from clients looking at a lot of transactions especially in the software space something around 70 to 80% of deals at the moment are related to a software angle of course AI plays a big part in that and it’s an area that we’ll be discussing further. But that said, you know if you look at the actual deals that are being that are closing you know we’re at a level which is about 24% off of the height back in 21 but that obviously was a high bar so we’re benchmarking against quite a high number.  

And we’re probably in an environment where things have stabilized quite a bit again and the real interesting side will be you know what we’re going to see now in September as we go into the post-Labor Day run up towards the holiday period. I think this is going to be the really defining moment. I think one other thing I would add that conversations with clients have a very different perspective, and so some clients were very hopeful that post Labor Day we would start to see a lot more deal flow. 

And then on the other side of the range, it was more like 2024 but that is still quite a narrow range and I think that gives me some level of optimism that we should expect to see certainly in the tech space an abundance of deals that will we should expect to see closing between now and the holiday period. Yeah really really interesting. 


HM: Joshua, to kind of complement that, I think I wanted to give our viewers a bit of an update on what Mergermarket data is showing about where private equity is at in terms of activity in the US and in North America as a whole. Obviously, the report was published back in July but we’ve seen quite a few kinds of large cap deals coming through them which I’ll go into in a little bit more detail perhaps later on. 

But just to kind of set the scene, year-to-date we’ve seen $181 billion dollar worth of deal volume coming through in North America that’s across 575 deals. That’s actually down by around a third on 2022 in both deal count and deal volume but we all obviously know what a record year 2021 in particular was and 2022 again those are kind of quite outlier years in fact if you look at the kind of overall trend of private equity activity. We’re back at levels that we’ve seen in terms of transaction volume back in 2019. So actually you know even with this kind of suppressed demand we’re still at quite a decent level of or not press demand actually because as you said Joshua, you know that there’s still a lot of of pent up demand there is a big pipeline but we’ve got a kind of you know various issues that I think the report goes into around bid-ask spread for example which I know you probably want to say a bit more about later Joshua but you know even with that happening activity still at quite a kind of decent level if we put it in the overall context. 

Exits are down as well on you know verses 2021 and 2022 which obviously entails some problems for fundraising but again they’re around the level that we’ve seen in 2020. So you know, I would add actually,  this is kind of fairly, it’s understandable and it’s fairly normal in terms of the kind of overall global M&A outlook, where I would kind of compare and contrast is North America versus Europe. Europe’s been hit quite a bit harder by a number of the very well-known macro issues that we’re contending with and actually deal volume there or you know has still not reached the level that we saw in 2020 it’s still down on that at 71 billion US dollars. It’s down 70% since last year. 


DT: Building on some of those indicators you did touch on,  Joshua, maybe one for you, what are your thoughts or how are you feeling about PE deal flow going forwards.

JM: I mean, you know, the report highlighted an interesting trend which is that you know the bid-ask spread is the highest in tech, yet the outlook that our clients have on future demand is also the strongest in tech. So I think that really underpins this discussion. 

Valuations certainly have been fairly buoyant in you know if you look at the NASDAQ it’s up 33% the S&P is up it’s somewhere around 16% right now year-to-date and of course by the way this has a has a very positive impact on the denominator effect you know when we’re thinking about you know GP fundraisings and maybe taking a little bit of pressure out of that that effect but when you look at the sort of valuation angle, 

I do think that you know in tech it’s been you know obviously widely publicized that the tech market is dominated by an AI theme, which is really creating a bit of a halo effect. So the question is really is that if you take the AI piece out,  it does that make the private equity industry more interested in transacting and that bid-ask spread obviously to come down for deals to unlock. 

I think this will be an interesting watch out over the next couple of months to see whether we are going to see some of the software deals close at EV valuation that companies are willing to to sell at. We have seen a lot of interest in pipe deals and the market has been dominated. 

We have a majority of deals that are being done that are take you know take private situations and I would say that I think the outlook is for more of those larger deals to happen but boards you know are you know still not comfortable accepting accepting some of the valuations that the private equity industry is putting forward and when you look at history typically what happens is that by the time boards are comfortable in accepting some of those prices the stock market is rallied and  the pipe deals are off the table, so hopefully you know there will be an abundance of you know further pipe transactions for private equity clients, but you know the timing is going to be an essential part of this. 

HM: That’s really interesting, and actually again, thinking about our data the portion in terms of deal volume that technology has been making up year after year has been rising in recent years. so you know maybe thinking about five years back it was around 23 to 25% of total volume in the US. I think looking at our latest statistics for the year to date it’s around 38% so that appetite is very much still there you know, in spite of this the bid-ask spread difficulties that you’ve mentioned, Joshua, there is quite a lot in the pipeline there as well on the tech side. 

I’ve got a few examples here, from Mergermarkets, recent kind of US deal pipeline that we publish, we’ve got Alteris which is a data and analytics business which does quite a lot in AI which is obviously one of the big topics of today. 

We’ve also got EagleView Technology, sort of a deal there on the horizon potential coming to Market. That company provides kind of geographic information system software kind of geospatial software for aerial views, aerial imagery and that if it was transacting would potentially provide an exit for sponsor owners, Clearlake Capital and Vista Equity Partners, Clearwave as well is an interesting one reportedly exploring a minority stake sale and that’s another huge theme around people looking for you know different creative ways to get deals done and to make realizations that company backed by Magenta Capital, it’s got an enterprise value of eight billion dollars so obviously the minority stake won’t be transacting for quite that much it’ll be a portion of that, but interesting to see that there’s clearly appetite here and on the large-cap deal side actually you know this year also isn’t fairing too badly in the US in terms of activity in the US in terms of activity which kind of gives terms of activity which kind of gives hope for some of these deals coming through. 

Recently we had the Subway deal which gave the company an enterprise value of um I think 9.5 billion US dollars that was acquired by Rock Capital we’ve also seen a couple of recent deals even just in August you know jumping back to what you said Joshua about kind of things getting going even in the last few weeks, we saw Thoma Bravo buying NextGen Healthcare and we also saw Clayton Dubilier & Rice buying Veritiv so the appetite is certainly there.

JM: I would also just follow on, Dan sorry, I would I would just follow on with a couple of other interesting items you know observations is, if you look at the take private market right now,  year-to-date the median EV has been 500 million roughly dollars if you compare that to the same time last year we’re talking about 1.7 billion so the average value of you know transactions happening has certainly decreased and quite significantly. So deal flow itself you know being down is one part of it. But the actual you know transaction size has certainly come down and that’s one of the reasons why growth equity for the first time I think in the last decade has done more deals than large buyouts and so this been interesting trend to watch.


DT: Harriet, perhaps just some observations around the wider fundraising environment, how you see that developing the fundraising environment for GPs how easy it is to convince LPs to you know commit additional capital. Anything you’re seeing there. 

HM: Of course, one of my favourite topics, of course, so thank you, Dan. 

I think you know, Joshua you mentioned this, the denominator effect with public market is kind of adjusting is clearly going to be less of an issue for GPS now which will be a relief to many. But exit activity is still relatively low, especially versus 2021 and 2022 , and sponsors need to make these exits so that they can return capital to their investors actually just to prove their strategy to prove that they can make the returns they need to make in this tough market. 

All these questions we’re kind of posing today around when activity will pick up, where it will pick up, it all kind of comes back to fundraising in my view because people need to make exits. It’s incredibly important. So yes I think the liquidity constraints on the bar of LPs are going to continue, if people can’t make exits,  then they can’t return capital to their LPs. 

And you know the kind of cycle of LPs being increasingly kind of constrained and what they can do in terms of re-ups is continuing but at the same time there’s quite an interesting dynamic in private equity activity and fundraising and deal structuring around co-investments so in the large cap space we’re seeing more LPs you know Sovereign wealth funds for example actually being increasingly interested in co-investments.  

Doing co-investments means that they can put more equity into the deals gets over some of the financing hurdles that we’ve seen so it’s ideal for the GPs and it’s also good for the LPs because as our viewers I’m sure will be aware the economics around a co-investment are better for them than you know having exposure to an asset in a fund. So yeah, I’m very interested to see we’ve had some massive fund closes. 

People like CDC Capital Partners raising 26 billion euros earlier this year that fund targets Europe and North America. We’ll be keeping track of who kind of coming back to market, and if anyone’s going to beat that target next year and then you know the question goes back to where they’re going to deploy and obviously Joshua’s been giving some examples kind of around appetite for take privates, albeit with transaction sizes potentially changing slightly. 


DT: Are there any other sort of I guess sweeteners or concessions that you see GP’s making to continue to attract and retain LPs? 

HM: Definitely, so in terms of actually returning capital to them we’re seeing more people engage in minority stake sales the levels of GP-led activity haven’t necessarily been as high as we might have thought they would be there’s a huge amount of interest around doing GP-led secondaries and continuation funds.  

But again valuation is a question there you kind of you know you need to agree on valuation and that the existing LPs are happy with and the new LPs are happy with, when you’re kind of rolling that over. And then there’s a fair amount that GPs can do in terms of fund terms as well. 

So you know sweeteners sort of you know the the typical 2820 model, 2% management fee that can come down a bit perhaps at a first close. For the LPs that backed the fund early on, and you know reaching a first close, fundraising as a whole is taking longer at the moment for a pretty wide universe of GPs. 

Partly due to these liquidities constraints it’s not necessarily that LPs don’t want to commit, they often can’t, so that’s something that can be kind of offered as well to bring them in to secure a first close and then they can get on with deploying and proving their strategy, proving they have the deal pipeline that they’ve you know claimed they they do when they’re marketing their fund. I mean with some of the obviously the deals in market that you you referred to, do you see any evidence that you know technology in particular is not going to continue to be the focus of of deal activity. 

It depends on the strategy I think so there’s you know a lot of value investors people talking about distressed deal activity as a driver of activity. But actually there’s a lot of tech kind of in the pipeline in Europe as well. So, no, I think when you think about the LP view, a lot of LPs they kind of consider tech to be on a par with sustainability kind of bordering on impact as a long-term theme, so they are trusting their GPs when they commit capital to them to find the right deals in that sector. 

It is clearly a long-term theme, you know, AI is a huge theme at Mergermarket for us in terms of kind of product development and obviously for you in your research at Third Bridge and what your clients are asking you so no currently you know let’s let’s see the kind of tech bubble from 2021  I think has has gone maybe more sensible valuations but I don’t have the impression appetite is dwindling.


DT: Joshua maybe from some of the conversations you’ve been having with executives, are you getting a sense for you know how they’re thinking about artificial intelligence, whether that be the impact on their portfolio companies, or actually their own sort of internal processes? 

JM: I think there’s a degree of variation between clients. 

One end of the spectrum for example you have firms like Blackstone who’ve been very vocal about their focus on AI. And their data science team is over 50 people large and so you know that really shows you the commitment that they’ve taken to this. 

But I would say generally speaking most private equity firms are looking at AI across their whole portfolio set, and looking at ways that they can add value, you know especially right now in this environment private equity investors are are very focused on value creation work for their businesses and so the AI theme spans across any business that has large data sets where you know the AI angle could be you know enhancing productivity, optimizing workflows, and so, across Supply Chain management, legal profession it’s across all industries. 

So no I think private equity firms are all certainly my conversations with them asking me about AI especially for our business how we are thinking about it and how they could be also taking advantage of you know AI as part of their research process and If you think about private equity as a sort of a three-stage pronged sort of approach of sourcing, due diligence, and portfolio management,  the applicability of AI really spans across all of those three and, summation of content as part of your due diligence process and all the research that private equity firms have done themselves.  

How do you extract that how do you archive it and how you’re able to retain that information in the most structured and organized way these are big topics for a lot of our clients. 


DT: With that in mind, given the the topic of the second half of the discussion today,  I’d like to move on to Scott. Scott, thank you for joining us. Scott, obviously our Head of TMT Research, he’s our global sector team lead here, manages the team. Given all of the sort of the hype, I guess around artificial intelligence at the moment, Scott how do you think about maybe just sizing that opportunity,  from just a market perspective.  

SK: Thanks Dan. I think a lot of people are talking about what the opportunity consists of. I’ve heard estimates of a trillion dollars, multi-trillion dollar type market opportunities indicated for AI more broadly.I think it’s fair to say that there’s a lot of optimism. But I would also mention that this year in particular companies have been thinking about general IT budgets and projects. And so I think there has been somewhat of a conservatism in terms of historical challenges from an ROI perspective. 

I saw PWC survey not all that long ago indicating that AI could bring 17 trillion dollars in value, when it comes to the broader kind of global economy by 2030 so these are clearly some big numbers. They remind me of Amar’s law, which is this notion that folks when it comes to technology can be perhaps overly enthusiastic over the near term and perhaps overly conservative over the longer term. I would submit to you that if you’re thinking about a market opportunity of a trillion or multi-trillion dollars, I don’t think people are being conservative when it comes the overall opportunity at this point. 


DT: I guess with that, with that in mind, if we are anticipating this AI gold rush, how do you think private equity should be thinking about assessing the potential of say pick-and-shovel plays versus in investing in specific and market AI application? 

SK: This is kind of a classic question about investing in infrastructure or investing in applications. 

If you will, so I think that there are good arguments for both as areas of significant focus and investment. I do think a couple things are pretty relevant. I think first is a debate that’s been going on in and around AI I think for the last couple of years which is this notion of closed ecosystems versus open ecosystems. 

The way to think about this is the companies that have been at the forefront of AI, I think Harriet, you mentioned Alter for example that’s a more traditional AI oriented vendor and those companies historically have had some challenges in terms of everything from customer acquisition, to the notion of how quick the sales cycles are to driving return on investment costs have been a significant problem that frankly customers and prospects have been grappling with as they think about working with these companies so I think the pendulum to a large extent has been swinging away from those closed ecosystem more traditional AI software vendors to more open ecosystem type players. 

Now, of course, the next obvious question is okay, well, so we know who the traditional maybe more licensed cloud software players maybe right.  A lot of them some of them are publicly traded. If you think about open ecosystems I think the best example to think of right now is is AWS. 

Right, the major business unit, cloud operations of Amazon.  

They’ve building up an operation with a lot of infrastructure but also a lot of interconnectivity across a lot of different areas and so companies can partner with AWS to leverage the past substantial investments that they’ve made and also benefit from kind of their future investments going forward. 

I would argue that one of the best ways for small companies to get involved with and benefit from what’s going on in AI is simply looking to partnerships with these giants, the companies that have made these massive Investments that have platforms and frankly can build for the future, you know, I’m thinking at this point about, you know the notion that we heard from an expert when we did an interview, Forum interview earlier this year related to Google and its search business and how it was going to be impacted by AI and one of the things he said is that Google had already invested hundreds of billions of dollars in AI, and this is really before they even introduced Bard I think the implication there is that a lot of these companies have been investing massively for years and it provides them with a head start and frankly an advantage in a lot of respects. 


DT: We’ve spoken, maybe to some of the potential winners, as far as AI adoption goes, anything that’s come up in your research pertaining to you potential losers, ultimately is this a zero-sum game, how are you seeing those that may lose out as a result of artificial intelligence and it’s widespread adoption? 

SK: I think everyone is trying to look at this is winners only, and that’s clearly not the way it’s going to work out over time. I think there are a couple things to be mindful of what seems most obvious is the question that I get probably more often than any other when it comes to this particular space, and that is – are people looking at AI as cost-saving exercise, a way to essentially become more productive and efficient, or are companies looking at AI as a way to generate more revenue and accelerate growth prospects? 

I would submit to you that the answer to that question is both. I think in terms of maybe the near-term opportunity, the cost and expense side of the discussion probably takes priority. We’ve seen a number of public company executives talking about that. I think IBM comes to mind for example. But in addition to that, in terms of the work that we’ve done at Third Bridge and within Forum one of the takeaways that we’ve gotten is there are certain industries where I don’t know if you’d call them losers but they’re industries that are focused more on the cost opportunity. So I think about ad agencies for example, so I spoke relatively recently with a global head, C-level executive ad agency.One of the things that he said is that he could see AI enabling 30% a third of cost and expenses committed to headcount to be reduced in relatively short order. Why is that?

Because some of the tasks that people are undertaking at an ad agencies can be very kind of rudimentary and repetitive and so things like creating advertising content that’s going to be surfaced on websites for example, that’s something that AI can really do and do extremely well and so you can see these particular types of companies embracing AI in that respect. 

I guess the flip side of the coin is what about revenue opportunities. I think it’s fair to say that a lot of companies see and are seizing upon those. I think about big software companies like Microsoft and Adobe they are in the process of rolling out products that are AI enabled. I think we had an expert talk about how AI alone could add 10 to 12 billion dollars in total addressable market for Adobe. He also talked about this notion that you can suddenly start charging prices that are maybe 50% above where they currently are because of the benefits of AI and the productivity gains that’ll be achieved as a result so there are definitely going to be different types of companies looking at AI differently. I think one of the other things that I wanted to mention is sometimes companies are on the right path when it comes to AI investment and that can take a number of forms right you can invest in the technology, you can buy software, you can hire talent but we have some companies, and this is relevant for this discussion, obviously we have some companies that are acquiring AI companies in the hopes of establishing a foothold in building an AI practice you know and so one company that comes to mind is Real Chemistry, so Real Chemistry is a medical-oriented marketing and advertising and data and analytics firms.  They made a number of these types of acquisitions.  

The expert that we’ve talked to about the company within Forum, and I think we also did some work as a Primer, which is one of our newer products, the expert essentially said they’re on the right path in terms of acquiring in this area but then they didn’t kind of keep the pedal to the metal and continue to invest. And he feels like they lost out on a related opportunity. 


DT: To develop that point a little bit further, are there any industries or sectors where you see artificial intelligence you know providing particularly acute headwinds to build on your creative example, the ad agency had a similar conversation actually, and from a topline perspective?

One of the specialists that we interviewed in the midterm suggested that up to 20% of creative revenues could be at risk, and you know, actually AI in that sense would do advantage of AI. In that sense would be conferred pretty much entirely onto the customer through lower pricing, actually you know they’re dealing with some pretty sophisticated and customers at the end of the day you’re talking about you know global brands that you can sort of know how much these things cost, so is there you know, from your research, are you getting the sense that companies that are implementing these, I guess operational improvements through AI, do they get to keep those benefits and take those benefits to the bottom line or do you just have to give that to the customer through more competitive pricing to stay competitive with the next guy who’s decided they’re going to use those you know those efficiency gains for price?

SK: I think it’s a super important question I don’t have a great answer but here’s an example. I’ll provide so we conducted an interview earlier this year focused on the call center and customer service area and the expert essentially indicated to us that AI handles. Let’s say about a third of those inquiries so think about if you want to get in touch with you know your bank or your cable provider your telecom’s company or what have you about a third of those inquiries are already addressed by AI, some people don’t even realize that. In short order that number is going to go to about three quarters, so essentially what that means is exactly what you said so if you are a customer of a company like that, are you going to pay the same rate knowing that they’re substantially reducing the amount of headcount and expenses associated with maintaining that operation? 

I think there’s going to be a lot more pressure on those types of companies and related pricing.  It is an opportunity for no doubt, but it’s something that I think increasingly folks are aware of and it goes back to what I was saying before the near-term opportunity is definitely related to productivity and efficiency. We’re seeing that in a number of different contexts you know I mentioned what Microsoft is doing with Copilot, they’re looking to charge as much for the Copilot capability as they are for the entire Office suite. 

So they’re trying to extract massive benefits associated with what they have invested it remains to be seen whether customers are going to fall in line.  


DT: To point to your experience in the industry, I’ll refer to the dot com era, you have to forgive me but do you see see analogy there with today? 

SK: Absolutely, the short answer is. You know, one of the things and look, as you alluded to, you know I was covering technology stocks as an equity analyst in the late 90s and early 2000s, and I had a front row seat to what was going on. 

I kind of look at what’s going on now is would I say the SQL. It seems very similar in a lot of ways.  Why is that? I remember back those 25 years ago or so where companies were announcing initiatives and investments in kind of the internet and I know it sounds silly almost at this point really just to command more market attention and higher valuations. I do think that there is some of that, we had some companies literally renaming themselves, just to kind of get the market benefit.

It seems a little silly at this point but that actually worked to a large extent. Now we see companies that have named themselves you know I would argue that companies that are doing similar things announcing initiatives, announcing investments, maybe even changing their names getting similar benefits in the market as a result. 

Do I think  that was sustainable? No. 

Do I think it will be sustainable in this case? No. 

But I think there is one very large difference, and the large difference is it seems to me like 25 years ago or so, the whole market kind of got caught up in this. 

And in fact, you could look and say what was going on in terms of bubble getting so big that it brought down the entire market. I don’t know if that’s going to happen in this case or more specifically I don’t see that happening because the scope and scale of the so-called bubble is just not comparable to what we saw 25 years ago. It’s a lot more narrow it’s maybe concentrated in kind of software and maybe services within technology as opposed to across kind of Industries and sectors as well. 


DT: So with some of that in mind, you know what should PE in there? I mean we’ve moved back into equity, but I what should PE investors be you know thinking about or particularly wary of or optimistic of when looking at the space?

SK: I mean, so I think there are a couple of things that I would keep in mind right so I think and I hearken back to the discussion that we were just having I think the investors who are most successful either were tremendously fortuitous with timing and clearly we’re not going to suggest that people just be lucky, because of course that isn’t something that people can determine on their own. 

Nonetheless, I think what it comes down to is this notion of sticking to your core competences. One of the things that we saw during that bubble period is you saw style drift. 

Companies that were dedicated to one area deciding that they were going to invest aggressively in internet companies and that might have worked for some time but like a lot of other investors that ended up hurting and hurting pretty substantially. So I think sticking to core competencies would be kind of the first tenant and probably should be the first tenant of you know investment firms to start off with.


I think you have to kind of consider that AI should fit within kind of the mantra or the investment thesis that a firm is going to have rather than the other way around. That’s kind of the way that I would think about that. 

And then of course it’s about due diligence. How proprietary is the technology or the offerings you know, what’s the competitive landscape look like, right and then what’s going to happen in the future. Due diligence I think is hugely important and so those are the types of things that I think folks need to remember. What it comes down to is everyone likes to say it’s different this time. It isn’t. 

It really starts and ends with fundamentals and the way that you kind of understand those is through sticking to your knitting and do due diligence. 


DT: I think it’s super interesting that you do mention style drift and sticking to a knitting, because I think one of the key takeaways from the private equity report was that actually you know PE firms would be spending much more time taking a lot more care and attention to to really own that skill set and really exploit their experience within specific Industries.  I think it’s an interesting point you raised. 

I’m keen to take the opportunity now to field some of the questions that we did receive from the the audience, so maybe, Harriet, one for you um one of the questions we did get was around legal and potentially regulatory ramifications around artificial intelligence and its use within private equity. Do you see any? Do you see anything there? 


HM: Yes, obviously this is all at quite an early stage, but some of it is linked to actually what you were saying Scott, I think you identified a couple of ways businesses sometimes use AI. You said sometimes, you know it can be to increase productivity, and it can be also to cut costs right that those that was a kind of distinction you made. I think the private equity approach to the use of AI at management company level so the private equity firm itself, and at portfolio level, it will depend how they are using it. If they’re using it to make decisions or to you know to cut cost at a portfolio company level, that kind of thing. There will just need to be transparency and trust around that. 

Private equity cares about its public image. It needs pension funds, insurance companies, investors that do disclose that they invest in private equity to be able to trust it as a kind of a place to put their their capital reputationally.  So that’s something to bear in mind I think.  

Josh might have a perspective on this as well I think perhaps based on the report and on your your knowledge of how private equity is using AI. I know the report highlighted a few things around use and in due diligence for example.  


JM: Absolutely, private equity firms are increasingly looking at ways, of course, to make sure that they can abide with you know some of the regulatory focus that they expect to see or have seen. I think the area right now that’s under focus is the communication between clients and investors. so we’ve seen the SEC come up with revised guidance around inter broker dealer, and their clients and the way that they communicate and how obviously AI could play a big part in this. So this is already the first step we’ve seen in and I think everyone is expecting to see more focused by the regulators on this. Now when I when I look at our business of content, and that we provide in terms of research to private equity investors, AI plays potentially a large part there as well. 

So you know if you think about it from an MNPI perspective, making sure that our clients are not exposed to MNPI that they do not receive confidential information, all of those have an AI angle potentially to that. If you are you know amalgamating data that is in the public domain like a chat GPT large language model with your own data set, are you potentially you know generating information that could be in a hallucination and deciding on you know on trading on that. so I think you know some of those topics and the last one is maybe a little bit more in the public equity part of the world, but I do think that some of those are our key focus area, and making sure that you know clients are staying protected.


DT: Harriet, have you seen any maybe GPs or the potential for GPs to actively market the use of AI within their investment process as a means or a way to differentiate themselves from other GPs perhaps, or do you anticipate GPs sort of communicating that to potential LPs at some point?

HM: Good question. I think it depends what tools are available because if everyone can use these tools then you know it becomes less of a kind of specialization less marketable but if firms have their own kind of sources of data privately and they’re using AI to kind of comb through those then obviously that is the kind of selling point. I mean obviously AI is the focus of this discussion, but a lot of private equity is actually very kind of human relationships based. I think the report said for example investor relations were one of the areas where private equity is perhaps less interested in using AI versus other areas doesn’t mean to say it can’t make inroads there. 

But there is still quite a big human element it’s a lot about the people and the relationships you know do you trust the the people you’re working with can you do the human due diligence side of of things as well. So I think you know people clearly are incorporating AI into their investment processes and also into their value creation DCs. If people have in-house expertise on that, clearly that that will be a differentiator for sure if they can have you know industry veterans people with expertise who really understand AI and and understand technology and can use that for value creation. Then yes I think that can be a differentiator when it’s used kind of appropriately.  


SK: One of the things that we’ve discovered in talking with experts about certain areas so like accounting and finance software, tax preparation software, executives think that these are areas where you’re going to see corporations embrace AI for the same reasons that I talked about earlier you can become more productive and efficient and maybe it’s more on the accounting side than the finance side. But the companies in the space really see tremendous opportunities not only to kind of upscale their offerings but be a lot more profitable as they’re providing them. So I think companies are already starting to do this in a variety of ways and it’s been interesting to hear repeatedly from experts about how they’re doing that.

I think there are puts and takes do that, it’s one of those things you had accounting firm for example can incorporate AI and become very very effective at preparing reporting and preparing filings, but the customer in the same way they can be equally empowered by an AI tool that enables them to prepare their own. So I’m just curious if you you know see there are puts and takes there what’s kind of the net impact or how are you thinking about the potential net impact on those particular group of companies and types of companies which you know we know are near and dear to private equity? Any kind of take there? I don’t know. The word I thought of when you were saying that is ‘disintermediation,’ you know.

The notion that folks can suddenly gain access to these platforms and applications and start taking on these responsibilities on their own. But I think the wrinkle there is the associated risk.  I would argue a lot of companies don’t want to take on that risk so I would imagine that there’s going to be a meeting of the mind somewhere in the middle. But to go back to kind of some of the things we were talking about I think one of the biggest risks when you think about barriers to entry when it comes to what we’re talking about in terms of AI, it it’s got to be a combination of data privacy, which we alluded to and kind of some of the legal and ethical aspects to what is going on here. 

And so for example imagine a situation where a company says all right we’re going to use AI to help us prepare you know our corporate tax filing and let’s say for some reason there was an error well, who’s going to be culpable for that error? Is the person who chose the software? Is it how it was implemented? Is it how the software was actually working? Did you not have someone checking the filing before it was made? 

I think all of those things are super important and that’s obviously just a hypothetical example, but you could see how there are a lot of potential pitfalls and so I think a lot of companies like I said before see massive opportunity, but the path to realizing that opportunity I think is going to have more pitfalls than people recognize at this point.


DT: Understood. Joshua, one for you perhaps, are there any real-world examples or any conversations you’ve had with PEs where they have implemented artificial intelligence, be that in their own processes or be that as part of ongoing work with their portfolio companies? 


JM: I would point to the summation and search of content I think that’s an area that plays large part the intersection of what we do. Our clients have certainly already built ways to subate the, or you know, provide a summation of the content. For them it’s really about the information that they sit on the data being able to draw upon and get an answer to your question as quickly as possible. So this is an area where I think we’re going to continue to see more innovation but it is definitely also an area where I think some large steps have already been made. So I think that certainly is one where I would say that um this is something that we see quite a bit from our clients. 


DT: I’ll come to you with a follow-up. It’s you know slightly different to the the the flavor of the questions that have gone before, but I know you have some thoughts here around, at what size does a private equity fund, potentially become uncompetitive for you know less competitive relative to public markets? 

JM: It’s an interesting question and obviously a lot of debate in the past around, does private equity beat the returns of the public market. It’s not surprising that smaller firms typically you would expect to have a larger gap and a high propensity to beat public market returns, but there’s been a lot of research done on this topic and I can’t give you an answer for sure that you know it says exactly what that point is. I don’t think anyone can do that in an easy way. 

But you do have to look at geographic variation for certainly and then also you know different sectors. I think the work that Professor Phalippou has done for example, I’m happy to share after this webinar, his work. It’s been very interesting, one of the big issues that he draws upon is that the IRR return calculations are fraught with a lot of issues. One of them is of course the distributions when they come back because a private equity firm deploys cash and gets the distributions back at different times, and what internal rate of return you assume in those IRR calculations with the distributions coming back is typically been pegged to the internal rate of return that these funds have have had in the past. And so what you do is you create this cascade effect of an overinflated IRR number. If you take that out we are talking about IR numbers that are typically sort of in the 11 to 13% range which basically matches what the indices in the US have been generating. So you know one can argue that over the last decade the returns on private equity has been somewhat similar to the public markets and of course you have a very different risk adjusted return profile with private equity than you do with public equity. 

These are things that I would say that the the the viewers of this webinar should really consider us part of the question being asked. But I think it’s a very very fascinating topic and one that I will continue certainly to watch myself but yeah it’s one to watch. 


DT: Folks, I think we’re we’re at time, but just before we do wrap up a quick thank you, Joshua to you joining us remotely, and obviously Scott and Harriet, for joining me in person. 

A quick reminder as well for our viewers Third Bridge provides the best suite of integrated primary research products on the market. 

If anybody watching wants to get in touch with our leading AI experts or read some of our industry-leading AI content, please do reach out and get in touch either to myself at or anybody from the organization and we’d be happy to help. 

With that said, thanks again all, thanks again Joshua, thanks again for everyone who joined us.

Episode Guests

Joshua Maxey

Third Bridge’s co-founder and head of corporate development and communications

Harriet Matthews

Funds editor, Mergermarket

Scott Kessler

Third Bridge’s Global Sector Lead for TMT