Buyers and Builders
00:18:49 · Cyrus Hessabi
[00:18:49] S1: I think there is everything in the trade off, right? There's some advantages and some disadvantages. So if we keep it on the advantages, I think the main advantage is probably, and probably will be allowed unconsciously every day, but it's probably just like a broader set of references that you can draw from when you think about how, you know, what how to execute on a great deal, you know, or what are the different value creation areas when we're considering backing an opportunity and, you know, looking through its growth avenues, looking through its transformation avenues, basically looking at a SWOT, you know, look at a SWOT matrix, right? Strength, weakness, opportunities, threat. I think it just helps you cover more points in that matrix overall. You know, I think for a lot of the businesses I'm looking at today, the AI risk is significant for some of them, right? And I think it helps to have had some experience thinking about, you know, what exactly is the bridge from, you know, narrative to reality, either if someone is pitching an AI value creation path or if someone... Or if we're trying to assess the true threat that AI might might pose. Like, for example, you look at a health care staffing business, and you might think, oh, AI is gonna come tomorrow because AI is so good at matching people. But then you have other considerations, right? Like, do people really wanna adopt it? Net of all things. Does it integrate with kind of existing software suites and the difficulty around that? Or, you know, what what would... How much data do you actually need to train this to have a proper matching? What are the consequences if your matching doesn't work? I mean, I'm kind of giving you an example on the fly here. My point is it helps to have had, like, this sort of background for that situation, given its relevance. Right? And then for example, I think the other thing I'd say is, I think a lot about sales, and like how to build a winning sales organization, how to, you know, what drives people to buy. You know, think you generate your IRR every time one of the company's salespeople is in a room and select, right? That's literally how you generate your top line. So just thinking about that, but I think there's also disadvantages, right?
00:20:59 · Cyrus Hessabi, Mikk
Because sometimes it means you're over complexifying thinking about many things that might be too far out of scope or, you know, I think at some point depth triumphs over breadth on some things. So I think it's it's kind of a balanced stick, but I certainly like having that bridge background because I think it's defying you for so long now. [00:21:18] S0: You mentioned this AI risk. I think it's interesting. Maybe we can go more specific, because thanks to your experience, you see things which many other investors who back searches don't see. So what else? You mentioned one thing is the healthcare staffing industry. What else? What do you see? You look at different companies, different industries. You see like, okay, here is a big, like, could be a red flag in the future. [00:21:44] S1: Yeah, for sure. So you're thinking about what, where is the biggest AI risk in terms of job growth? [00:21:50] S0: You have people coming to you with with deals, some things under LOI, for example, and you immediately see that, okay. It's too risky. And you go back to your team saying, okay, guys. We should maybe skip this one and and move forward because of x, y, and z. Maybe you can give some examples, or how do you think, how do you view these opportunities?
00:22:09 · Cyrus Hessabi
[00:22:09] S1: But, you know, I'll tell you this. I don't know that many examples where we said no because of AI risk per se. AI is usually... I don't mean to be cheesy or kind of, you know, setting a narrative, but the I think in many cases, it's more a consideration and an opportunity set versus a risk per se. It's more, okay, this is how... This is what we should probably implement in this business to keep it competitive and and even do better versus, okay, okay, don't go there because we're asking to replace everyone, you know? Unless you go into some specific businesses, but they have already underlying poor economics, right? I don't know, you look at a low margin call center, we might think, okay, labor's in, you know, there's too much labor intensity, or some people have tried automating their call centers like Klarna, and then they have to bring back humans. So I have some, you know, there's maybe these types of considerations, but more often than not, the AI piece, we're looking at something like, I don't know, I was looking at some, like marketing automation services. I think there you have a lot of AI opportunity as well, right? Matchmaking, campaign generation, Copilot for creativity. I think more often than not, it's can you easily leverage a solution that exists off the shelf and bring it to the business? Much like in the past, PE firms might think, you know, what's kind of the best ERP or the best CRM I should implement in my business? Here's kind of what is the best AI strategy I should bring in versus saying completely backing out of industry just because of that. Yeah. That's just from my my own experience, my memory today. I'm sure I'm sure there's industries that missing in my examples.
00:23:46 · Mikk
[00:23:46] S0: But what else when it comes to it's interesting that you said that you see those opportunities, many maybe won't again, because based on your experience, has there been any deals or, yeah, deals coming to you where you see immediately that, Okay, this is it's like screaming how good of an opportunity it is if we implement AI in what they do on day to day basis. And that will be the value add.
00:24:15 · Cyrus Hessabi
[00:24:15] S1: That for sure. So I looked at a few definitely, right? And I think some of the, I mean, of course, the companies that we backed, right, in various industries, think those were definitely kind of in that realm. I think there's other industries that I'm excited about from the AI perspective. You know, I think you can see online there's quite a few businesses that have raised in the insurance space, insurance TPAs and back office. I think that's very interesting. I think the main reason those businesses would be interesting is because of two things: high share of labor as a total cost, right, and repetitive, therefore automatable work, and work that also fits what AI can reliably do today. So processing documents, summarizing documents, being able to parse information, being able to synthesize and find gaps in information in long streams of data. So I think typically, those are jobs that I think also, I don't want speak on behalf of everyone, but I think these are maybe jobs that I think create burnout as well, right? Or work pieces where, I guess, people wish they didn't have to do that, previously. So I think these are also opportunities where you can say, I'm going to make my employee base way more fulfilled. I'm going to be able to keep them focused on things that matter the most. And then we can use AI to automate the pieces that are of low cognitive load perhaps for them or less less fulfilling. You know? I think I think that's kind of the main the main point here. I'm trying to find an example because I'm trying to find examples where, like, software changed the way that we work. You know, how how we as just everyone works, right? Like, with every kind of new productivity tool or software tool, you know, a whole piece of people's jobs changed, and then we focused on a higher value piece of that job, right? I think that applies to, you know, when you start using software in a company or when new technology comes for engineering design or whatever. Just think about how people used to do things forty years ago and what you do now for a given job. You know, it just let's say we're we're recording this this podcast. Right? It took a few messages and now a video call on on the laptop. Right? But the podcast is still happening. It's not being replaced by AI per se.
00:26:33 · Cyrus Hessabi, Mikk
I think it's a similar example where the core value of the workflow is being kept, but the menial work around it is being removed over time. [00:26:42] S0: And when you joined Shore Capital, did they give you their current portfolio companies? Hey, now we have this guy, Cyrus, joined us. He has this excellent background, as you have. And now please go through the portfolio companies and please find opportunities where we can implement AI. Like, did you did you have to do a work like this as well, or it was all about those new opportunities, new companies, new new searchers? [00:27:06] S1: I think new new for now. I think, like many fans, you know, we think a lot about AI and AI for the portfolio companies, right? If you see on Shore's website, and there's a lot said, and Shore is very famous, in fact, for having all these different centers of excellence and pods, right, that are kind of unique in bridging actually. Another theme for bridging between Fortune 500 and kind of accomplished large scale businesses and the management practices they're in, connecting those with emerging roll ups and roll up platforms of SME businesses in those industries. And I think in the same way, I think our approach with AI is going to be thinking deeply what is the bottoms up way to create operational value and improve companies, improve people's lives with that. Where can AI fit? Basically, much like we have these centers of excellence in other areas, other functional areas of the business. [00:28:01] S0: Was there anything you had to unlearn when joining Shore?