Franklin Templeton CEO on SpaceX, Anthropic, Circular Deals & the State of the Market

Your grandfather started in 1947, managing 2.5 million in AUM to now 1.8 trillion in AUM. Done 17 acquisitions in the last 6 years.

I think the Canvas application was about 2.5 billion when we acquired them, and it's now 30 billion.

I found out that you guys had exposure to SpaceX—

We did. We did. Anthropic. I mean, a bunch of them, yes. Well, I think the biggest growth lever is AI. It is such a massive disruptor. There is no person who's had more significant impact on really where we are in the technological advances today than Elon has.

Ken Griffin was just on stage for the Citadel Securities Conference, and of course they asked him about the AI bubble. Maybe this is a bubble. There's almost certainly bubbles within this moment in time.

It happens over and over. New technology. This is the greatest thing ever. It's going to be the greatest thing. It goes all the way up. It's so great, it's so great. Boom. And everybody's disillusioned by it. It's terrible.

And then it comes back up to where it sort of should be. So the question is, where are we on that curve?

Jenny Johnson, welcome to Sourcery.

Thanks for having me. It's great to be here.

Well, thanks for having me in your super fancy, gorgeous new New York City office.

We are very excited. And you're in the Heritage Room, which is all about our history.

I know. You guys like Benjamin Franklin, huh?

We do kind of like him. Kind of. He was a stud. He was a pretty cool guy.

Yeah. So I'm going to ask you a question about him later, but before we begin, I just want to give a nod to Franklin Templeton. You guys have been around for multi-generations. Your grandfather started in 1947. You went from managing 2.5 million in AUM to now 1.8 trillion in AUM, which is crazy.

It's a huge growth. There's a huge growth story behind it. And for your story in particular as well, you started in the mailroom and now you're the CEO. So I want to talk through all of that, but before we get to it, where are we in the state of the market?

We have people saying we're in a hidden bear market. There's also all this fun about AI and the premiums there and the big deals that are happening and the IPOs that are getting pushed back. So how do you kind of consider this?

Yeah. I think you have to kind of break down a couple of things. Look, there is a ton of noise in the AI and the hyperscaler space. There's noise around the circular financing. There's noise around how they're doing revenue recognition,right?

So let's put that aside for a second. You look at the economy. You know, we've managed. I think inflation's probably pretty sticky and rates are probably going to stay higher. But the current rate level is not unusual from a historical standpoint.

It's unusual for the last 25 years, but actually in history, it's not that unusual. You're young, so you don't remember those days of mortgages being much more expensive and, you know, and it still functioned. You know, the rate environment, I think it's definitely higher.

So if you built your business model or have a lot of leverage, that's a concern. But if you're a good cash flowing company, the consumer is still very strong, particularly in the US. Productivity is up, you know, is at 2%.

I don't think any of that productivity story has anything to do with AI. This is all technologies that have been around for a couple of decades. Digitization, cloud servicing, all of those things. It takes a long time for new technology to be adopted in an organization.

I always say, you know, I ran technology at Franklin Templeton and I always tell people, your two biggest challenges in technology, people will tell you it's integration of systems. It's actually the quality of your data being organized. And then the second thing is change management.

Because the fact is, people don't like it to change. They don't want to adopt new things. It's a lot of effort on their side. And so the AI that we have today is going to take a while before you really see it being meaningful to companies' earnings.

So that's the upside that I think we're going to see happen. And so back to kind of the market, if you look outside the hyperscalers, you do see some broadening of markets. You still see strong earnings. I think something like 70% of companies beat their projected earnings.

And so, you know, we're still seeing good tailwinds around that. Now, what are the headwinds? Well, the headwinds are obviously that it looks like it's going to be tough for this war in the Middle East to end anytime soon,right?

You can have a $20,000 drone essentially ground to a halt a tanker. And effectively, if that happens, it's hard to get insurance and it effectively, you know, stops the oil getting through the Strait of Hormuz. Having said that, there's actually a lot more getting through than I think people thought would happen.

And as I said, the economies, particularly in the US, we've been pretty well adjusted to oil at this price. But that's probably going to stay there for a while. And frankly, I don't see much, you know, a quick resolution in Russia and Ukraine either.

So we have to sort of look at these as almost business as usual. And then, you know, I think the US and China are much more constructive than we've been in the past. But having said that, I think it's kind of a frenemy type thing.

There's areas that you're just going to not cross the line. Tech, particularly China is going to head their direction. US is going to head our direction. But there's also, we need each other. And we need them for rare earths.

They need our economy and consumers to sell the things that they manufacture. So we'll figure out ways to work well together.

What are the growth levers that you're watching?

Well, I think the biggest growth lever is AI. It is such a massive disruptor. Now, having said that, I'm a student of history and I, you know, I tend to be more optimistic on what this means. Every major new technology that comes in, if you go back and look in history, there's, you know, the prediction of the demise of all the jobs,right?

In 1997, the cover of Business Week said the broker, the internet was going to eliminate the broker. And now today, a financial advisor does more for their clients than ever. They're no longer just an investment advisor. They're a true financial planner.

They're leveraging the internet and these tools to provide more services. So, you know, what happens is that a lot of jobs that you couldn't imagine will come about. And so I think that there's tremendous tailwinds for companies as they start to figure out how to leverage it.

First thing that you tend to do is you make more efficient what you do today. But once you get it in the employee's hands, they start to think of the creativity. There's going to be a lot of things that we never imagined we would need or do that'll come out.

And I

was using Meta glasses recently.

Oh yeah. Did you have the Kylie ones?

Are those the ones with the screen?

I don't know.

You're saying the design ones. No, I got the Ray-Ban basic, whatever. But I was on the golf course and I was like, why can't these Meta glasses find my golf ball? You know,right? So I said to my son, hey, because he's a programmer, could you make it so he's working on an app to say,right?

Now, did I ever know or think about it? And by the way, it would leverage the iPhone, but you couldn't have your iPhone. You need to have the Meta glasses. So suddenly there's it. And I've already come up with three other programs that I told my son he should go,right?

So, you know, we find new things that we can't imagine initially. So I'm not a negative, but there is going to be this transition that we all have to be careful. But I do think there's massive, massive upside.

And so I think that's probably the biggest tailwind. And everybody talks about AI. There's a ton of other innovation going on. What's happening in biosciences?

Oh, it's major.

Major. The pipeline of new drugs, the customization of medicines, you know, material sciences. There's a ton of things that are being done there and innovations. 3D printing. They're now talking about 4D printing where it actually will, you know, when it gets in theright position, it'll move into place.

So, you know, those are all big tailwinds that are the bull case.

Ken Griffin was just on stage for the Citadel Securities Conference, and of course, they asked him about the AI bubble. And one of the biggest positions that he had against this was, we just don't know what's going to happen with the supply and demand, especially with chips.

We're making all these chips now. When are they going to expire? When's that going to fault? And like, how do you make up of this? I'm very curious because I've heard that you are a student of history and you love history.

And so we've been saying we're in a bubble for like two or three years now. So when are we actually in the bubble? Have we been in the bubble the whole time? How do you make of bubbles while you're seeing them throughout all these cycles?

When I was

running the technology group, there was something that Gartner had called the, it was kind of the exuberance curve or something. I can't remember exactly. It happens over and over. New technology. This is the greatest thing ever. It's going to be the greatest thing.

It goes all the way up. It's so great. It's so great. Boom. And everybody's disillusioned by it. It's terrible. And then it comes back up to where it sort of should be. So the question is, where are we on that curve?

It certainly feels like there is a frothiness in some areas. So personally, if you're betting on the needs for energy based on today's technology, both on the manufacturing of chips as well as the production of energy, you're assuming that for the next 20 or 30 years, it doesn't change dramatically.

But that's pretty unusual. When you get a demand, people innovate and you find, you know, tremendous advances. So my instinct is, if I were to finance, I still, we like the financing on the shorter term because these are still big cash flowing companies.

These are not internet bubbled companies that didn't have revenue. These companies have significant earnings. So they're going to be able to pay their debt. Would I go on the longer term of the financing on things like data centers?

I personally wouldn't because I just think you're betting on today's technology and that we won't inundate quickly. And we see what's happening with AI. It's solving math problems that we've never been able in history to solve. So, you know, I think you have to be a little careful on that.

And so I think Ken's probablyright on that piece of it. On the other hand, and we've talked a little bit about the accounting side, so it's a little unclear on some of these revenue and how is it apples to oranges when you compare companies.

So you have to be really careful. Know your stuff as you're making those investments. That's why I'm a big fan of active management. Having said that, just yourself playing it, probably preparing for this podcast, you probably leveraged AI.

I know when I'm going to go prepare for something, I literally have a conversation back and forth, which opens up new thoughts for me that would be difficult. And usually what I then do is hand it to my team of experts and say, validate these things,right?

Because you can't necessarily just take it for what it is, but it can lead you to how you think about stuff. So I think we all get a sense for how incredible this tool is and the opportunity with it, but it will take time.

And when it happens in companies and sectors, the leaders could leave behind others in those sectors. I mean, I think that's how quickly the stuff is moving.

It seems to be the, you know, quote unquote, whatever kind of metric you want to use for revenue that we're seeing from Anthropic and from OpenAI are unseating a lot of incumbents and people that you'd think would be kind of winning in this day and age.

Now their IPOs are getting delayed and, you know, who knows why and all these kinds of reasons. Maybe it's because they say things they don't mean or maybe they do mean them and we should listen. But I think this was really interesting because this part, I told you, I did a lot of prep going into this.

I listened to a lot of your interviews on podcasts, like on the news, all over the place. And there was one really interesting one that kind of like opened up this other realm of Franklin Templeton I didn't really know, but like I kind of knew,right?

And it was when you were talking about the upcoming SpaceX IPO back in, you know, July or whenever it was. And you were talking about how Franklin Templeton got into late stage investments. And so do you want to tell that story?

I mean, I think it's just like so, it's like a good kind of encapsulation of how Franklin Templeton runs.

Yeah. So we're headquartered in Silicon Valley. So we have a growth equity team there. And honestly, as we all know, companies are waiting much longer to go public. And so, you know, some of the PMs said, boy, these IPO kickers we used to get were not, that were a kicker to our performance, we're not getting those.

We should do some late stage venture because it's really late stage ventures what used to be you were underwriting at the IPO level. And so a mutual fund can open or an ETF can hold up to 15% illiquid assets in there.

You don't tend to run it at 15% because you'd have a breach of the market moves, but you know, you could do six, seven, eight percent. And so we started to invest in late stage venture deals and then actually had some clients seeing the deals that we're in and said, hey, could you set up a fund?

So we actually now have a venture group, but they will often go in an investment both with the venture fund as well as some of the traditional portfolio managers who want to have exposure to late stage venture.

So I found out that you guys had exposure to SpaceX.

We did. We did. Anthropic. I mean, a bunch of them. Yes. Exactly. You know, if you're there and you have connections with the entrepreneurs, with the other venture community and being headquartered there, you know, you got to remember your kids tend to go to school with these people.

They're in the neighborhood. They're community people and you get to know them and that allows you to have access to those deals.

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SpaceX is a particularly interesting name because they came to the market sooner than anyone else and they have quite the diversified strategy. And more often than not, they're trying to label themselves as an AI company. And we were talking about this earlier, the makeup of that revenue, whether it was, you know, getting these data center contracts likeright before the IPO, the Starlink angle to this, getting to the consumer side of things, and then the launch costs that will then kind of bring down the economics of everything else.

So for a company like SpaceX, what are you trying to watch out for? Do you think that this one will become, I think Elon tweeted it will become the most profitable company on earth by order of magnitude?

So there's a lot in there. Let me first address one thing. You know, maybe we should in history, every time everybody renames their business based on an AI or a .com. And we just changed our parent company name from Franklin Resources to Franklin Templeton.

And when I said to my dad, why were we ever called Franklin Resources? He said, oh, boy, in the 1970s, you couldn't sell. The stock market was terrible. You couldn't sell anything, but you could do gold investing because there was high inflation.

And so if you had Resources next to your name, that helped you in the stock market. So there you go. Right? So this is a trend that people do all the time. They'll grab it. So what I always say is, you know, stick to your knitting and say what you are.

Having said that, look, I've used Starlink for, I have a place in Montana, and I got to tell you, it was a game changer for me because I could never get good high-speed internet. And the portable Starlink is amazing.

And so I think that everybody I've talked to who uses Starlink is a huge fan. So Starlink's in there. We've seen, and if you read Walter Isaacson's book on Elon, you'd recognize how much he has actually changed space investment and travel and really fought the system that was sort of gumming itself up.

So all about innovation, cost efficiency. I honestly believe that, and Elon seems so focused on getting to Mars. Like the thing is, he makes these statements and we all say, oh, that's ridiculous. And then, and maybe he doesn't get thereright on time, but he often delivers them.

Like flying cars.

Exactly. Exactly. Although I saw a very funny flying car company who said, welcome to the, welcome to the race or whatever. So, you know, and the work he's doing in robotics is amazing. You know, all of which are needed to his vision to colonize Mars.

So, you know, I think it's quite possible. I think your only risk there is you have a lot of key man risk with Elon. We all got to hope he stays healthy and, you know, can continue to innovate.

He's a man of mystery. So I want to shift a little over to more of your career and coming into the seat as CEO. So you came into the seat as CEO and immediately were leading one of the firm's largest deals.

This was the Legg Mason deal for $4.5 billion. And this also doubled your AUM. So walk me through that process and why you had the conviction and what the reasoning was with that. And then I definitely want to talk through your acquisition strategy because I heard and I saw that you guys have done 17 acquisitions in the last six years.

Yeah. So on the Legg Mason deal, there were parts of the market that we just knew we needed to fill out. And Legg Mason filled those things out. So one, they had the largest category is core fixed income.

And they had a huge franchise with core fixed income. We want to get bigger in private markets. We'd bought a private credit manager. They had Clarion Partners, which is an outstanding real estate manager. So that got us into the private markets.

And at the time, Franklin was 75% sort of retail wealth channel, 25% institutional, and Legg Mason was exactly the opposite. So we suddenly became 50% institutional clients, 50% wealth clients. And so that just balances out your business better.

So for all those reasons, it made a ton of sense. The challenge was, so that was announced like five days after, and we'd obviously been working on it for a year, but five days after I became CEO, the problem was three weeks after everything was locked down with COVID.

And of course, the market tanked. And it was really interesting because it never occurred to me to think, well, oh, that's too bad. We got this deal and we locked in this deal. And some of the articles are written up, oh, poor Franklin, they can't get out of it.

If you're getting into the deal because it's a good strategic fit, you're going to roll through those sort of ups and downs. And we knew it was an important strategic fit. And frankly, asset managers in down markets don't tend to transact because they're a great cash flowing business and people know they'll bounceright back with the market.

So we were really happy to do it regardless, but it just meant there was much greater complexity in trying to close that deal. Because what do you do when you do a deal? I mean, part of it is you're just trying to figure out your talent.

You know, you're going to have to reduce some of, you have a lot of overlap in your corporate services, finance, HR, legal. So you're trying to pick, you know, best athlete and put together the best team. And I think a big mistake that people who are acquirers do is they just assume that their team is the best team.

You really want to try to decide that you can pick the best athletes across the board. And so suddenly we weren't really able to travel and go meet the people. And so you had to do everything over video.

Fortunately for us, we, because we're so global, we had already adopted an environment where you often had people on video in meetings. Now that's standard, but back then that was something that people were really skeptical and they didn't really believe in, but it was already part of how we operated.

And so we ended up closing the deal 60 days early, which was, you know, kind of amazing at the time. And I don't think we ever lost faith in, you know, that it was theright deal for us. And it turned out to be an amazing deal for us.

Of the 17 acquisitions you've done in the last six years, what are the themes for that? What are the reasons? I know you're on this growth trajectory and that kind of thing. So maybe talk through that and then the higher goal.

Sure. So first and foremost, it was about making sure we had the capabilities that we needed to compete. A big trend in the industry is that clients are saying they want to work with fewer managers. And so the managers have to have a broader breadth of capability to be one of those fewer managers and be able to offer more things.

And that's where scale is really important. And so, as I mentioned, we had those categories that we wanted to fill in. The other acquisitions were all about either product capability. And again, the only thing I've said we feel like we don't have completely today is infrastructure, but otherwise we're probably the broadest breadth of capability of any asset manager.

And then the second thing was usually to enhance distribution. So maybe it was a technology tool, Canvas, Oceanicy, Asset Manager,right? So they had a quant shop, but what was really interesting to us was this direct indexing technology platform that they had created that allows separately managed accounts to be taxed efficient.

And because it was such an excellent technology, we can now use that as an overlay on active strategies, which was pretty new. So that was, you know, I'd call it both the capability and a distribution because there are clients who want these separately managed accounts.

They don't want an ETF or they don't want a mutual fund. They want it in an SMA. So that's an example of kind of that distribution capabilities. We bought a couple of wealth managers to bolt on to Fiduciary Trust, our wealth manager, and, you know, Lexington Partners.

So that brought us additional capabilities in the private market. So they're secondary private equity. And we bought, I think, three bolt-on transactions to our private credit manager to ensure that we have global scale, global reach, and capability. Crazy thing is happening in private credit is everybody talks about private credit like it's one big, you know, asset class.

But you talk about fixed income, you'd say, I got high yield, I got mortgage-backed, asset-backed, you know, investment grade. Well, private credit's the same. You have to have those capabilities, which means you have to be able to originate.

Our most recent announcement was buying a team that does asset-backed,right? Because that was an area that there's a lot of clients, pretty good spreads there, a lot of clients interested in it, and we just didn't have the origination capability until we acquired those.

And so how do they grow once you acquire them? You mentioned with OSAM, Patrick Oceanices, asset management. What happened with that after you acquired it?

So I think the Canvas application was about $2.5 billion when we acquired them, and it's now $30 billion. I think that's probably four years later.

Wow.

And so that one's done very well. The Lexington is more than doubled since we acquired them. Clarion Partners, the real estate manager, has more than doubled. The private credit, I think when we bought BSP, they were $26 billion.

Again, we bought a couple other ones, but we have just under $100 billion in private credit now. So they've been successful. A lot of people are skeptical about traditional asset managers' ability to have a cultural fit with the private markets folks.

There's obviously very different compensation structures and things. But that has actually worked really well for us. And our expertise in the wealth channel, as these guys are looking to expand into that wealth channel, has been really helpful because that is a very different sale than an institutional sale.

And so are most of these deals all cash? How do you structure them? Because if they're getting enormous benefits after the transaction, growing quadruple, even more, how do you incentivize that?

Well, first of all, you're buying these at multiples. So you're assuming a good growth. If you don't get growth, you're really in trouble because believe me, they're pretty good multiples, especially in the private markets. Although I have to say, because we were really early, we got them at very good prices.

I would argue that Lexington, we definitely paid full price at the time, but we hit the absolute sweet spot for secondary PE, which meant that they actually grew faster than even our models. So that ended up being a really tremendous deal for us.

But at the time, it was certainly fully priced for the size of assets that they were. You know, I think that what has lost sense of people is that the mechanism of paying somebody in the private markets would carry.

And carry is embedded and doesn't get paid for years is you have an unbelievably good natural retention that you don't have in traditional, when you buy a traditional asset manager. You don't have a natural retention where they have multiple years that they're waiting to get paid out for investments they made, you know, five years earlier or 10 years earlier.

To answer the question, we, in most cases, we did cash, maybe cash with debt. And then in the case of the Putnam deal, we actually did a bunch of Franklin stock. They wanted Franklin stock. The Great West Life had realized this trend of needing to be scale, big scale manager in order to get on these platforms, that they could see the consolidation.

And the problem was Putnam had great performance, but they were just subscale. And so, you know, I think we've taken the equity team or the total assets there from like $136 billion to over $220 billion. And it's really because we're able to bring this high-performing team onto platforms that they just were too subscale to get on those platforms.

And so we did most of that deal. They were looking to diversify. They wanted to hold stock in an asset management company. They were looking to diversify how to do that. Instead of having just Putnam, they wanted to own a broader asset manager.

And so we did that with stock.

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Let's talk about the modernization of asset management. So one of these, I think a key part was Lexington. I don't know if you remember, but I certainly remember when the markets were down and I was working at a VC fund and no one had a DPI and we were all trying to make ourselves feel better.

Lexington had swooped in and bought up like 10% of our portfolio and gave liquidity to our LPs, which was fantastic. And they did a good job, and I'm sure they're happy about it. Another part of that is tokenization.

We haven't talked about tokenization yet. I know you've talked about this a bunch. So what did you see with tokenization?

Again, having run technology and operations, I think I had an advantage in the seat on understanding why blockchain was so important. And I genuinely believe it will replace the rails in financial services. It'll be slow because it forces the change of a bunch of business models and the toll takers who take a fee on a transaction.

But it basically does three things really well. It has a source of truth. And anybody who runs a back office or tech department understands we're still running what we're not, but a lot of big financial services firms still run mainframes, which means you have batch processing at night, which means your data is not updated until sometime in the middle of the night.

With blockchain, it's immediate. And so there's a huge cost in firms to reconcile data between systems, and then you have to go reconcile the transaction with your counterparty. That all goes away with blockchain. There's just one source of truth updated immediately that everybody goes to.

The second thing, it has the ability to program these smart contracts. So whatever terms you and I agree, if this threshold meets you have to pay me collateral, or this one I have to pay you collateral, all of that gets programmed in.

Whereas pre-blockchain, that is sitting in a document somewhere, or you have to go and, you know, try to build it into the transaction, but it's really hard to do. So it tends to be in a document somebody's following, and they'll say, "Oh, let me go collect collateral you owe to me."

That goes away. It immediately is paid. And the third thing is the ability to make a payment. So I looked at that and said, "Well, this is a no-brainer. This is what we do in this business in the back office."

And so this is hugely efficient. And when we came out with the first tokenized natively on-chain tokenized money market fund that the SEC approved, they had us parallel process on our old transfer agency system, our old shareholder record keeping system, and our blockchain system.

And a couple of things, we were still one of the few firms, I think there were only two of us still running the old system in-house. And so we were able to look at the parallel processing, and we were astonished by how much more cost-effective it was to run it on-chain.

And we looked at that, like, if you open one of our traditional money market funds, you need $500 to open an account because anything below that, the other shareholders are subsidizing your servicing fees. Whereas we did it on the blockchain system, and you can open an account for $20.

We probably can go down to $5 because it's just that much more efficient to run. So we look at it and think that the financial innovation that's going to happen is going to be really interesting and significant. One is you're going to have 24 by 7 trading.

It's going to be atomic settlement. And you're going to have a lot of innovation that's going to happen because of the ability to program and now add AI to that. And you can build your logic of a trading pattern in there.

And so we just, we're big fans. Our tokenized money market fund, to give you an idea, it calculates interest every second. If you're a hedge fund and you use it as collateral and you hold it for four hours, 22 minutes, and 32 seconds, we'll pay you that interest.

Your cash that you earn that day is paid in your account at the end of the day. On a traditional money market fund, it's accrued all month, but you can't get to that cash until the end of the month.

And, you know, if you're a corporate treasurer, that's kind of significant. The ability to access that cash, or even an investor, like a portfolio manager, and you're using that as sitting there at cash, and as the cash comes in, you can actually move it and use it in a portfolio.

So it just gives you a little glimpse in the innovation that's going to come because of tokenization.

I mean, you embraced this super early and like really embraced it. I know you're also embracing AI and AI agents. You have over 1,000 AI agents for 800 plus investment professionals. Are there any areas where you're looking for AI to create more efficiencies internally?

Like, where are the pain points for you?

So I bucket AI in a few places. So first of all, on the investment side, like the real win is making us better investors,right? So analysts more efficient, so they're not spending as much time on admin, so they're actually spending time talking to companies, doing more research, maybe even covering more companies.

And so it is all about improving investment performance. Any cost savings there is insignificant to the benefit of just improving investment performance. With respect to distribution, it is actually about growth,right? So we had a partnership with Microsoft that they were excited to do.

They actually gave us free resources because it was such a sophisticated challenge and solution from a technical standpoint. Simple problem,right? What is your issue in sales? I want to meet theright clients and have theright conversations. That's essentially what you're trying to achieve.

But it's actually a really difficult technical solution because it requires you to have multiple AI agents that talk to each other and are coordinating with each other. And then it requires you to go out and get a bunch of different systems to pull in data.

So you might need your product system. You might want a system that shows you a holding of, say, a financial advisor. So that firm may give us a feed on that. So I'll look at what the holdings are.

I'll view our products. I might go to social media just to make sure that I can talk to that client about whatever's important to them. So I'm updated on it. I'm going to go to some of the rating agencies on there, the Morningstars and others, to understand as part of the products, what are the best opportunities.

And so Microsoft was excited about it. And what we've seen in the early results is 23% uplift in number of clients that one of our market leaders is visiting and an 11% uptake or increase in sales. So we think that's just going to get better and better.

So that's distribution. Now, where's the cost savings part? The cost savings part comes in the back office. It doesn't necessarily mean you have that much less people. I think you just do more. And in the case of technology, what's exciting is you have AI writing the code.

I've never talked to a CIO who runs a technology department that doesn't say, "Yeah, we got all the projects the business wanted done this year." It's all about prioritization. So if you can get more through the pipeline, that's an amazing thing.

You're not trying to save money. You're just trying to get more things through the pipeline. And so that's kind of how we bucket the various, you know, how we bucket our approach to AI. And then back to the initial question on what do you think about all these hyperscalers and their revenue models?

I think there's a couple of things that we haven't yet seen. Number one, the first thing you do is you give your employees the tool, the AI tool. Go run, go do these things, write agents. That's all good.

And then over time, it starts to cost you money,right? And so now you go, "You know what? Do all these agents need to run? And do they need to run as frequently as you set them up to run?"

And that governance of the discipline, we don't know what that ultimately impacts these hyperscalers. And then the second thing is there are probably a whole bunch of queries that an employee needs to do leveraging AI that probably could be achieved with these free models,right?

And so that governance layer of evaluating the requests and saying, "You know what? This is a request that we're going to pay for the top model. This is what we're just going to send to the free model." All of those things will impact ultimately what the revenue looks like with these hyperscalers.

I'm seeing that in a lot of our conversations with these emerging companies. They would rely on the frontier models, and then they'd have 14 trillion tokens, and they'd be overloaded. And then they've shifted their model. Now they're totally efficient, and they're running 99% on these open weight, open source models.

And so I think that was probably going to make a big difference. But maybe we continue to use these frontier models for the biosciences and for these actual frontier kind of projects. So I know at the beginning, I wanted to tie this back to kind of the multi-generational nod to, I was going to say Benjamin Franklin Templeton, but Franklin Templeton.

So your grandfather started the firm.

Well, since we're Ben is our stock, you can say that Ben Franklin Templeton.

Ben Franklin Templeton. Hashtag. Well, it's not hashtag. It's Cashtag,right?

Your ticker is Ben.

Yes.

B-E-N on New York Stock Exchange. We love that. So I'd love to go through a little bit of the history of the firm to today.

My grandfather actually had a brokerage business, and

he was a huge fan of Ben Franklin, and he decided to create a subsidiary. So he decided to name it after Ben Franklin. And so it was Franklin Funds. My father served some time in the military, came out.

He was 24, 25 years old. And his older brother took over the brokerage business, and he said, "You know, I really want to do my own thing. Can I talk to my grandfather?" And said, "I'd like to take over this subsidiary."

So it was $2.5 million in assets, AUM, and $10,000 in revenue. And he said, "You know, I was making $200 to $300, I think it was a month." He goes, "But that wasn't a bad salary for a new," you know, he kind of looked at himself, even though he'd done four years in the army.

He goes, "But that wasn't a bad salary coming out." So that was 1955. I was in college. I think it was probably 1983 or '84 that I attended our first billion-dollar party. So it took that long to get to a billion dollars.

We acquired a company in California. That's why we moved out in California. And I think Franklin was like $60 million in AUM in 1973, and the company that we acquired was maybe $120 million or something like that. And then the market tanked the next year.

And so I think that we eked out a $5,000 profit for the entire year, and I think 1973 or 1974. But, you know, it's still a good business, and you just keep at it. And I actually think a lot of things as to why my grandfather set up the business, which was at the time, the average person couldn't get access to the excess returns of the equity markets.

And so this innovation was created. Why don't we pool people's money? We'll give them expert advice. We'll make it at a reasonable price, and they'll get diversification that they could never get if they were on their own. And that was kind of the concept.

And I do think we're at a similar thing on the private markets now. Companies waiting so much longer, you know, credit being a lot of the debt goes into private credit. We got to make sure it's fair and democratized for people to get access while recognizing these are absolutely illiquid vehicles, but they can get an excess return because of the illiquidity.

We've been seeing that publicly listed closed funds, all of that kind of thing. VCX is one of my sponsors, and they created a vehicle of all these pre-IPO companies so you can get democratized access to these assets. As we wrap up, I have one final question.

This is the hardest question I'll ask you today. Are you ready?

Yeah, I'm ready.

Who is the modern day Benjamin Franklin?

I have to say, and this is because I one time asked my team to do a because our logo, everybody thinks it looks so old. And I was like, "Oh, are you kidding me? Ben Franklin was a rock star.

You got to understand." This guy was like, I mean, not only was he an inventor, a politician, a philanthropist, you know,

such an amazing, really, really well-liked. The ladies loved him in France kind of thing,right? So I said, "So we should do something like who would Ben Franklin be today?" And I have to say, the one I'd say most comes closest is Elon Musk.

And what comes back, people say, "Oh, but Elon isn't as much of a philanthropist or Elon isn't this or that, whatever." I mean, look, there's no perfect match. A lot of times, a person is made a little bit by their time.

But I think that there is no person who's had more significant impact on really where we are in the technological advances today than Elon has.

He did say he's going to give one SpaceX share to all of the children in America.

I love that.

Around $20,000, which isn't good.

Like, there you go. See, he's getting that. Ben Franklin probably had to make his money too before he actually was able to do the philanthropy side. So I'm going with Elon.

Great answer. Allright. Well, Jenny Johnson, thank you so much. I really appreciate it.

Thank you. No, thank you. It was great.

So much fun.

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