00:21:11 · Zeynep Yavuz-Willson, Sebastian Johnson
[00:21:11] S1: all about the network effects, right? Yeah. This is where you end up having network effects. Like, Legora was a good example where it's the law firm and the legal customer, right? Because then... The in house effectively, let's say. Then if you are on Legora as a law firm and you say... You tell your customers, I want all of you to be communicating through Legora. Or... [00:21:31] S0: Why haven't we seen the same thing in accountancy? Or have we? Are there companies like that? You know, we've got Legora, we've got Harvey, but we, especially in The UK, we have this huge, history with the big four accountancy We've got these amazing accountancies for... We haven't... There doesn't seem to be a player in that space that has grown to the level of a Legora or a Harvey. Yeah. Why do you think that hasn't worked so well?
00:21:31 · Sebastian Johnson, Zeynep Yavuz-Willson
[00:21:31] S0: Why haven't we seen the same thing in accountancy? Or have we? Are there companies like that? You know, we've got Legora, we've got Harvey, but we, especially in The UK, we have this huge, history with the big four accountancy We've got these amazing accountancies for... We haven't... There doesn't seem to be a player in that space that has grown to the level of a Legora or a Harvey. Yeah. Why do you think that hasn't worked so well? [00:21:53] S1: So I would say some industries definitely had faster escape velocity compared to others in the AI adoption, and we've definitely had that in Eagle, but a lot of the workflows are text based. Mhmm. We've had that in customer support where a lot of the workflows are voice based. Yeah. Then you look at something like accounting and there are... And I've, like, studied this in each European country pretty deeply, and then obviously we invested in Integral that is doing this transformation in Germany. Yeah. And you've got a few things that make your AI transformation job quite difficult. One, you need to work with the local accounting platforms. So, you could attempt to rebuild the ledger. In Germany, for example, you have DATEV that has pretty much 100% market share. Yeah. But that's like building another business to try to disrupt DATEV. And also DATEV has a lot of trust. It's actually owned by the accounting firms themselves. So, the accounting firms themselves own this accounting technology. Imagine that you don't want to replace that. [00:22:52] S0: Yeah, yeah. That's interesting.
00:22:53 · Zeynep Yavuz-Willson
[00:22:53] S1: So, you want to partner with DATEV, which means that you needed to build an automation layer that's on top of effectively a system of record that already exists and used by everyone. By the way, those integrations that you have and the depth of those integrations, I believe will be another moat in this AI diffusion. Then the second thing is that in accounting, you've got so many edge cases, and this is not just text based workflows. So, there is quite a lot that you need to do from a quantitative side as well. So, the automating that is actually a lot trickier, and there is literally no room for error because you are doing something legal, you're doing a legal filing and there cannot be any room for error. So, and the other thing is that again, I'm coming back to this, the level of fragmentation in a market slows down adoption of AI. The more concentrated the market, the AI adoption happens faster. Why? Because the decisions are actually driven top down. If you think about how a lot of these customer support solutions or legal solutions that are bought, it's boardroom decisions. When people use it, obviously, they're happy with the tooling, but so much of that is happening. And I think this is why diffusion of AI has been super fast in some of the verticals is because the decisions are happening at the board level and it's being pushed down by the CEO and the chief. There's always an AI strategy that's being discussed in the boardroom. Yeah. And that makes sense. Therefore, particularly in house functions like customer support, legal has had such high adoption. If you think about SME accounting, like who's driving that change? We need to do that change bottom up, and that's much harder to do.
00:24:29 · Sebastian Johnson, Zeynep Yavuz-Willson
[00:24:29] S0: Yeah. That's really interesting. Okay. So let's... If we look at the European market more broadly and we look at this this idea that... Or this is varying degrees of diffusion or adoption across Europe, What do you think is unique about the European market where maybe we have an opportunity to adopt or diffuse AI faster than Americans? Maybe it's because we have... Faster. Yeah, maybe because we have particularly concentrated industries. We have different industries Or even, like, the the Dwelly example is interesting because because it's fragmented Yeah. The opportunity to go bottom up Yeah. Is present in a way that actually maybe if it was not really concentrated but not really sort of, like, fragmented, there wouldn't be the same opportunity. Are there other industries like that in Europe where we think, okay, that's a really interesting opportunity? [00:25:13] S1: Yeah. So, I mean, we think about this very actively, right? And therefore, in investing in driving this AI transformation in some industries need a bit more of a push, we had the roll up strategy. So, saying, let's go acquire... We're going to be a real estate agent anyway. We're going to be an accounting firm. So, what don't we think of... A payroll services company. So, let's think about capital in terms of acquiring our customers. So, think about CAC not as we spend and then we acquire customers organically, but let's think about CAC as acquisition spend for companies. So, that's one way of thinking about it. Then, for example, we've set up an initiative called EU AI Champions.
00:25:13 · Zeynep Yavuz-Willson, Sebastian Johnson
[00:25:13] S1: Yeah. So, I mean, we think about this very actively, right? And therefore, in investing in driving this AI transformation in some industries need a bit more of a push, we had the roll up strategy. So, saying, let's go acquire... We're going to be a real estate agent anyway. We're going to be an accounting firm. So, what don't we think of... A payroll services company. So, let's think about capital in terms of acquiring our customers. So, think about CAC not as we spend and then we acquire customers organically, but let's think about CAC as acquisition spend for companies. So, that's one way of thinking about it. Then, for example, we've set up an initiative called EU AI Champions. [00:25:54] S0: What [00:25:55] S1: we did there was we brought together the established European businesses who want to adopt AI and have that boardroom discussion, but they have no idea how to do it. So, we've established this initiative so that we are connecting these established businesses, the CIOs and the CTOs of these companies, like Heineken and Miele, and a few other companies are part of it, and then we will connect them with AI companies of Europe. So, we make them meet, for example, do workshops three, four times year. [00:26:30] S0: The capital model is changing, right? You've mentioned this, right? The way that GC is thinking about the role at play and capitalizing and giving capital to companies. [00:26:38] S1: Yeah. CVF is a strategy where we help companies scale their go to market spend with no dilution. [00:26:46] S0: Yep.
00:26:46 · Sebastian Johnson, Zeynep Yavuz-Willson
[00:26:46] S0: Yep. [00:26:47] S1: And I think this is so important, especially now at the age of AI, for all the reasons that I have explained kind of earlier in our conversation, where the go to market, the brand building, the customer relationship is ultimately the only mode. So, your capabilities to invest in go to market are becoming so important. And if you have predictable returns on your go to market, meaning if you know when you spend this much, this is how much you get paid, and you get paid in two years, Why would you use equity for that? Equity is for things where you have high risk. You it's when you don't know if it's going work or not. That's when you should be using equity for new product investments. [00:27:31] S0: Yeah, I was going to say it's more for like R and D and products. Exactly. Not so much go to market, right? Yeah.