"The Cognitive Revolution"
00:19:56 · Nathan Labenz
[00:19:56] S0: Hey. We'll continue our interview in a moment after a word from our sponsors. The story of doing more with the same and embracing that or even wanting to scale it up because who wouldn't want more if it's better does make sense to me in some areas. I mean, the the things that I always point to as like, you know, every organization would want to be doing more. You know, every founder would say, yeah, I ought I ought to be doing more cold outreach. You know, I ought to be doing more lead gen. I ought to be doing, you know, a better job of nurturing my funnel and, you know, similarly on recruiting. Right? Like, I ought to be reaching out to top engineers 10 times a day or, you know, as basically as much as I can. How many are doing? Actually, zero because I don't have time for it. Okay. So sure. If we could get AI to do that, you know, it seems like for a company like Ramp, you know, you're entering into an infinite market and just, like, grow as fast as you can makes total sense. It's a little harder for me to wrap my head around some of those things when it comes to, for example, let's say, accountancy. At least the way I've always approached accountancy, I'm like, I want to do as little as I can to be compliant and satisfy my board. And it's not like I have a sort of wish list of things that I would be doing if it was only... You know, if I only had more bandwidth or if I could only get more bang for my buck. Like, that to me does seem like much more of a just like... I I should be able to do it for less. Right? Like, that seems like it's where... It's what most people would want.
00:21:23 · Marc Bhargava, Nathan Labenz
[00:21:23] S1: So I'll give you... [00:21:23] S0: How do you segment that?
00:21:25 · Marc Bhargava
[00:21:25] S1: Yeah. Two thoughts on accounting. One is there's this huge shortage of accountants. So it's a industry fewer people wanna get into. There's a generation of baby boomers retiring. Many of the top accounting firms, if they could could take on easily 50 or a 100% more clients because... But their constraint is there are a shortage of accountants. And so if you buy an accounting firm and you AI enable it, you might no longer have that shortage because a lot of the more basic tasks closer to for example, bookkeeping can now be automated. And so if you AI enable an accounting workforce, that accounting firm has two or three times as many clients they could go out and they could get because there's actually a shortage of accountants there. And so that's how a lot of value can be created by going in. In terms of the end client and what they might wanna use it for, suddenly your accounting could be giving you proactive recommendations. So today it might be around building out three statements and filing your taxes. You know, you can easily see how once you have that data, you can actually start making recommendations on where you can save money, how you're spending. You can have tools that turn that into financial models that can help you think about your capital needs, should you be getting debt funding. So suddenly a lot of the tools, which maybe today are very stagnant, can actually be really diagnostic, very proactive. And so I do think that the kind of even as if it might be considered a boring industry, the suite of products can drastically change with AI. And perhaps more near term and more importantly, the same accounting firm can do a lot more work with the same cost basis, the same workforce basis if it's AI enabled. And we're really in the current phase going after that first opportunity, which is how can accounting firm AI enabled do two or three times as much work that obviously really increases the margin profile because it's a similar cost basis but obviously much higher revenue and that's the focus. But certainly to your question to the end client, maybe things get delivered more quickly, they're more accurate, all of those things are pluses. But even how you visualize the product certainly will change over time with AI as it...
00:23:20 · Marc Bhargava
We're seeing in things like legal being a great example of this where lawyers can also compare all the contracts and then recommend pricing changes because there's inconsistencies. So how does the law firm or the legal department go from just a cost center to also making recommendations and maybe being even a business plus center and AI can make that change. So you have those two opportunities. One is just taking out more work with the kind of same group of AI enabled folks that obviously increases margin and is a huge opportunity in services. And the second is to change the output of these services businesses and things like accounting or legal start to be more diagnostic, more prescriptive, more insightful, and become departments that aren't just thought of as a cost center or a check the box, but can actually help you in running your business.
00:24:04 · Nathan Labenz, Marc Bhargava
[00:24:04] S0: Can you take me through sort of the playbook of how you develop these companies? I mean, the general sketch that I have is your, first of all, assembling a founding team that has the mix of technical and m and a roll up experience. How do you decide what it is you want to focus on building? And how does that differ from maybe a more traditional SaaS strategy? Like, I guess I'm I'm particularly thinking about how much of it is going after what you might think of as core tasks versus sort of auxiliary tasks. I mean, couple examples of core tasks versus auxiliary. It might be like, I just did an episode with Ambience Healthcare. No. You know, that they're not trying to do, at least not yet. We'll see. They're not trying to do a patient facing doctor that would actually interact with you and make the diagnosis. That's the core task that the, for now, the human doctor continues to own. But they do have the AI scribe in the room, which is transcribing and then translating the notes to medical coding, yada yada yada. And that's all the stuff that the doctor currently has to do in their pajama time after hours. [00:25:18] S1: Yeah.
00:25:18 · Marc Bhargava, Nathan Labenz
[00:25:18] S1: Yeah. [00:25:18] S0: And so they're happy to offload that. And that's like, so far, everybody's everybody's pleased with that arrangement. I might contrast that though to, like, a customer service call center type of scenario where I assume that the AI is, like, taking the calls and that would seem to be, like, the core task. And so, you know, whoever the person was that used to take those calls maybe can take other calls or may... You know, but it seems like there is some... Again, this sort of, like, complement versus substitute notion seems to come into play. So how do you think about, like, as you begin... And, Megan, maybe it varies by vertical. We've all the time in the world for you to go vertical by vertical. How do you think about... Do we enter here with auxiliary? Do we try to take burden off? Do we try to empower? Or do we just, like, go right at the heart of the core task? How how do decisions get made?