The AI Coach
AI meets human behavior in these fun and insightful conversations with Danielle Gopen, a top founder coach and advisor, and Paul Fung, an experienced AI founder. We blend AI breakthroughs with real-world insights on business strategy, industry disruptions, leadership, and psychology while cutting through the hype to ask the hard questions.
This is for decision-makers like founders and business leaders who want to harness AI's potential thoughtfully, exploring both the technological edge and human elements that drive long-term success. Join us to challenge the status quo, navigate the shifting landscape of an AI-powered world, and get new information worth sharing.
The AI Coach
AI Industry Disruption: Accounting (w/ Reyes Florez)
Join us for an insightful episode where we explore AI's role in revolutionizing the accounting world with Reyes Florez, the CEO and founder of Platform Accounting Group. We discuss the stark contrast between how larger firms are leveraging AI and the obstacles smaller firms face with adopting new technology. Reyes underscores the pivotal role AI will play in bridging the workforce gap as industry demographics shift.
Today's Guest: Reyes Florez
Reyes Florez is the CEO and Founder of the Platform Accounting Group, a private equity-backed accounting and professional services firm focused on acquiring and operating boutique professional services firms throughout the US. Utah Business named him a 2024 CEO of the Year, and he is a frequent speaker at AICPA and other leading industry conferences. Previously, Reyes was in Investment Banking at Credit Suisse where he focused on M&A and capital markets advisory in the Business Services and Education Technology sectors. Prior to joining Credit Suisse, Reyes was in Corporate Finance at Goldman Sachs. He has an MBA from the University of Chicago Booth School of Business where he was an 1898 scholar, and his BA in Economics from the University of Utah where he received cum laude honors.
More about Platform Accounting Group: The firm has executed an impressive 40 acquisitions in the last nine years, showcasing its streamlined growth strategy. Earlier this year, Platform secured an $85 million minority funding round, led by Cynosure Group with continued participation and support from Swell Capital and Peery Capital. This substantial investment will augment both its current portfolio and future expansion efforts.
Links and Resources:
Death, Taxes, and AI by a16z
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Today we're trying something new. Paul. Do you want to say what it is?
Speaker 1:I believe we have our first guest on the podcast. Is that correct?
Speaker 2:That's correct. Reyes, do you want to say hi?
Speaker 3:Hey everyone. Yeah, excited to be here. This is great, Honored to be the first of what I'm sure will be many yes.
Speaker 2:Well, just to give a little bit of background on you. So, Reyes Flores, we actually all went to Booth together same class and prior to school and for a couple years after you were in investment banking Goldman and then Credit Suisse, and then, about nine years ago, founded Platform Accounting Group, which, for the last nine years, you've now been CEO. And if you could tell us a little bit more about Platform, that'd be awesome.
Speaker 3:Yeah, you bet Again, happy to be here, excited to take part in the conversation. So, platform, essentially, what we do is we will acquire and operate what I would call boutique CPA firms throughout the country, and I would qualify and define boutique as those firms that are very, you know, communally driven, typically somewhere between 10 and 75,. You know, full-time headcount, and you know those firms are facing a number of challenges as the landscape has evolved, as there's been, you know, four or five very distinct, very pervasive issues that they're running up against, and so what we do is we'll provide them capital, operational capacity and expertise, strategic capability to be able to evolve and face those challenges.
Speaker 2:And so part of why we're having you on today is to talk about how AI is really already disrupting and will continue to disrupt the accounting industry, both as an industry and as a function within organizations. And so, as you know, because you sent me the Andreessen article that came out about a week or so ago, aptly named death, taxes and AI. So three things that we now know are certain in life. So three things that we now know are certain in life, they have a lot of interesting ideas and use cases for how AI will disrupt accounting.
Speaker 3:I'd love to hear from you what you're seeing on your end. Yeah, I think the first thing that I would note and really has an overarching theme, is that this is something that is necessary for the industry to continue to thrive. And what that actually means is, you know, one of the most pervasive problems facing the industry is a massive demographic shift happening at the top. So you have 75% of AICPA, which is not artificial intelligence CPAs, but the American Institute of CPAs. Their membership is retiring, is eligible to retire.
Speaker 3:Some people say now, some people say three years ago, some say it's kind of still three years out. Bottom line is it's a massive number of folks who are nearing retirement age and starting to transition out. And then you also have had a significant drop off in new graduates, new entrants. You've also had, you know, one of the latest stats I've seen is close to 300,000 of what I would call kind of middle managers, someone who's, you know, experienced in their career, leave public accounting and choose to do something else. And so there's this dearth of talent that exists, you know, in the industry, a challenge in the industry. I think AI is going to be necessary really to be able to address that change and that issue.
Speaker 2:So, in making these acquisitions of these smaller boutique firms, what have you noticed in how they may or may not be using AI before they join up with platform?
Speaker 3:Yeah, I mean, look, when we acquire a firm, it's really not even on the radar for them. I think about the evolution of those firms really in two phases. A lot of these firms, candidly, are still running off of like a green clipboard and gridded paper as their workflow tool. The technology stack is very archaic, it's very fragmented and this has been a business that's really been powered by human capital and intellectual capital for really its whole existence and there's a lot of barriers for these small firms to even keep up with what has evolved in the technology stack over the last 10 years. So we view really the phasing as hey, let's at least get them to par, let's get them modernized, and then you know, phase two is starting to think about more strategic initiatives like AI. So there's a heavy lift, both operationally and from a technology standpoint, just to kind of get them to what you would think a modern business would look like.
Speaker 1:I'd be curious, like do you think that there's disruption and shift in AI? Disrupting accounting is already here or is it something still to come? Like, is it something you're seeing today, day to day, or do you think, because of the slow adoption between traditional accounting firms, that you know this is still kind of five, four or five years off?
Speaker 3:Yeah, this kind of goes back to what I started to say, which is, you know, four or five years off. Yeah, this kind of goes back to what I started to say, which is, you know, the application just isn't evenly distributed across the landscape. So if you look at large, you know big four firms, top 25 firms. They've been using and deploying artificial intelligence and you know their preparation process and some of their audit. You know quality control functions and their intake and onboarding processes for quite some time and so it's been deployed in the industry at the top level. Again, the unique challenges at a boutique level one are just capacity Most of these firm owners are practitioners themselves, so they're not entirely separated to be able to focus on running a business building process, driving strategic initiatives, because they're still ultimately responsible for client engagement and client management. So capital constraint.
Speaker 3:And then the other thing that is really challenging and this will be a challenge for how AI actually gets deployed across what I've called mid-market and boutique firms, which is the technology stack, because it's not proprietary in the way that it might be at a large firm.
Speaker 3:It's very fragmented, and so you have tech software programs, for example, where the code is, you know, 40 years old, and then you have a workflow, you know, management system that's completely different and that might be modern, and to get those two things to talk to each other and even just interact and have you know information flow in both directions is a challenge in and of itself. So you know, and that's where, if you look at kind of the Andreessen roadmap, you do see a lot of these tools being built to perform a very specific task and a very specific function and at some point those are probably features of a larger product. But there's going to be some time before. That is because you do have to, in my opinion, attack the problem at the moment in a more modular way, because of the way that the technology is very disparate and fragmented, especially at mid-market and boutique level. Yeah, so basically there's this giant data wrangling problem that needs to, of the way that the technology is very disparate and fragmented, especially at mid-market and boutique level.
Speaker 1:So basically, there's this giant data wrangling problem that needs to happen first. Where it's like we know, the systems need to be talking to us. The very basic fundamentals need to be laid down before we can throw AI on top of this and have it solve the problem.
Speaker 3:Basically, that's right. Yeah, exactly. So I think about the way that it gets deployed first and the way that we're approaching it really is, at this task level, right. So one of the places that we're hyper-focused is on the intake process, on the tax return, and we're working in conjunction with a third party to build this and they're really brilliant and really great and I think we're going to crack the code on it.
Speaker 3:But what that tool will do is actually go in and will, you know, read the unstructured data of his work papers, which are the, you know, source documents that a tax return preparer will use to prepare a tax return.
Speaker 3:So they'll read that unstructured data, they will look at prior year returns and then they will, you know, issue out kind of a punch list or an organizer to the client that says okay, here's what you've historically had, here's what we kind of expect to see again.
Speaker 3:And as that data comes in, it will actually start to filter, organize, ask questions back and engage with a client in a way which, historically, has had to be very human, capital intensive and, because of the nuanced nature of the forms and understanding what forms do matter and what forms don't, that's actually a task that's had to be completed by someone who's a trained accountant almost, which is very expensive, you know labor, and so to be able to kind of automate that process, organize it into what I would call, you know, kind of a bookmark, work paper binder, and then you know that will then go on to the prepare which will then allow for easier and more seamless data input. Eventually, that data input will then be performed by the tool as well, but you know we're still a little ways off of that as well. So I think, just to give you a flavor of like a very, you know, task oriented specific function within a broader workflow is where we're focused, and I think that's the way that the problem will have to be attacked.
Speaker 2:To me that seems so obvious because, even as an individual you know, having to send my documents to my accountant for tax season I feel like I can never remember what file was. What. Did I send? Everything that I was supposed to? Am I waiting for anything else? And I generally rely on her to tell me but I guess she also doesn't know because she doesn't know necessarily what happened that year that I might need a K-1 for.
Speaker 3:Yeah for sure. And that's where, hopefully, the learning process of the tool would then know what questions you know they might see correlation between some activity that they know that you've performed historically. And then maybe you know, given a tax law change, you know a you know macro event or that would then trigger, say, hey, folks who look like you that have had these forms in the past have also had this form this year. That's new. And they might ask you that question. Right, I mean, that's we're a long ways from that in my opinion, but that's some of the benefit of like, how do you then actually get an engagement model that's built around the artificial intelligence that would then prompt the taxpayer for new forms and new situations based on you know information that's being fed and its own learning?
Speaker 2:When you say a long ways, so in today's exponential development of AI is a long ways. Three months, six months, four years what's like general time.
Speaker 3:Yeah, I think it's years, I think it's, you know, three to five years, you know. And again, when you start to kind of bring it all together, I think that's where the challenge is. I think that the tools that exist today will perform these very specific tasks very, very well, but to bring it all together again, to build it into an ecosystem, that's going to be very challenging.
Speaker 1:Yeah, I was going to ask a similar question, which is you know when do you think the retiring AI CPAs will be fully replaced by AI CPAs, artificial intelligence CPAs, you know? It seems like that's probably still five, six years out.
Speaker 3:Yeah, and I don't think it's a replacement, I do think it's an augmentation and you know, really a side by side, right. I mean you think it's getting machines to do machine things and humans will continue to do human things right, and the more that we can do that, the more advisory, the more recommendations, right. I think you know, I foresee a day where, given the just sheer amount of data that we have on a client, again through a recommendation engine or you know understanding how, you know what certain client profiles look like and what they might need, it will then push notifications to the advisor and say, hey, look, based on the profile of this client and others who look like them, and again, you know macroeconomic data, microeconomic data, industry specific data if they, you know, own a business in construction, right, it can then push those suggestions that then that advisor, as a human, can go and interact with them in a much richer, much more focused way. And so I think that you know that's kind of the grand vision and I think we'll get there at some point. But I think that's where you know kind of even full circle back to what type of talent is drawn to the industry in the future. I mean it's going to be less about your technical capability, right, and much more about your strategic thinking, your ability to connect and network, your ability to communicate.
Speaker 3:And then you know you think about also, just even at a boutique level, one of our focuses. You know where we are trying really hard to, you know, improve the engagement model to be much more holistic, right. So our core business is tax preparation, but we have the ability to offer, you know, the small and medium-sized business outsource controllership and CFO function. We have a wealth advisory arm outsource controllership and CFO function. We have a wealth advisory arm. We have the ability to convert somebody from a QuickBooks to a Sage or an Acumatica. So an ERP, var and consulting arm, and so the ability to bring a holistic service offering, like many of the large almost all the large firms do, down to your main street business owner and your individual, I think is a very powerful future that will be powered by this technology.
Speaker 2:What you said about it'll be less on the technical skills and more on the critical thinking, and that's something Paul and I talk about all the time is, at the end of the day, with AI, somebody needs to be responsible for understanding that the output is correct and for being creative in how to use the tools. And so actually recently I read that there's been a shift now in the demand for liberal arts degrees over STEM, because people are recognizing okay, it's less about the technical, it's less about the coding, now that they'll have tools to do that. It's more about how do you make sure it's being done correctly and strategically think about it. So I think that's pretty interesting no-transcript.
Speaker 3:That's you know. I think that's an you know, and that's a good illustration of why firms can't play around the fringes on this. They've really got to be fully committed and be prepared to embrace it, because it's going to change the entire business model. You know we talked a little bit on the workflow, training, you know, talent development, recruiting, pricing models right, pricing models that are based on time and materials and input. Now, when, all of a sudden, the time, you know, almost goes to a tenth or nothing, right, depending on how advanced the technology is. Now, how do you think about capturing the value that you're providing to a client? How do you articulate that to them? So, again, that's where you think about disruption. So, I think, disruption in the business model versus this wholesale replacement of the human.
Speaker 1:Yeah, how much? How much of your billing today? I was actually curious about this. So we recently did our business taxes and we actually had kind of a flat fee style billing and so I was curious about time, materials versus flat fee In your experience with the accounting that you see, are you guys? Is it still majority time and material, or is there a lot of flat fee?
Speaker 3:So it's still time and material predominantly, to give you a sense of again how fast paced the industry moves. They've been talking about flat fee. You know kind of what the industry refers to as value pricing for over a decade. Again, that that even that requires a little bit of a more close to a wholesale. You know change in the business model and the business thinking right and you know the way and the way things, who's in charge of pricing and how pricing actually then is determined and sent to the client, communicated to the client, et cetera.
Speaker 3:So you know the industry views kind of flat fee as the future, but that's been a future we've been talking about for 10 years but it's very hard to do. I do think that, yeah, I think we're a little unique in that we take a blended approach. I think the inputs around time, things like realization rates, the way that the industry has kind of historically measured efficiency and output, are important variables. I don't believe they should be the primary variable to determine a price, but they are one of maybe four or five that should be considered and so we do want that data, even if it's not something that's like a strict time and material billing process.
Speaker 2:Is that another opportunity for AI as a tool to help determine what the flat fee should be for any one client?
Speaker 3:Yes, and there's a name on the map in Andreessen's matrix there that's working on that. That is trying to kind of manage the invoicing process. Again reviewing historical invoices process. Again reviewing historical, you know invoices looking at, you know change and forms, the complexity, the you know the size of the numbers involved, benchmarking across industry data, etc. So you know again, trying to get all the inputs, all the variables. So yeah, absolutely that is a function that would be a massive win for the industry.
Speaker 3:Invoicing in time takes a lot of time and it typically is done by your most expensive talent, right, partner, director, manager level folks. And so if you can eliminate them from having to go through what today is a bit mostly manual process because there's this art to it right, mostly manual process because there's this art to it, right, Even if you are time and material, there's generally an art still to determining the final bill within the industry. That's a great place that AI can be helpful and we're not too far off from something like that. I mean the name on the list there is doing it and continue to improve it.
Speaker 2:Who is it?
Speaker 3:IWIN.
Speaker 2:Okay, it's interesting because some of these things that we're talking about in terms of where AI can be most helpful, are not even for accounting itself right. It's the operational aspect of the role or of the business, and so I feel like that's also something to think about. And the thing I've been thinking as you've been talking about this is just the real divergence in organizations within the accounting industry platform, which is now taking these smaller organizations and getting them up to what we would call table stakes in terms of how they're using technology and then moving forward beyond that, and then these more boutique firms that, if they're not able to get there, they're kind of being left behind in the industry. I don't have a specific question about that, but more just an observation and curious to hear how you think about that. But, paul, I'll also ask yours.
Speaker 1:Yeah, I have a question that does converge with that. I have many questions, but one question that I was going to ask that converges with that is, Reyes, in this world of AI going forward, who wins and who loses? If you had to pick winners and losers, is it like the big four? They will be able to be disrupted by firms like yours, who are able to adopt better technology more easily because AI is becoming easier to adopt. Or is it more like the incumbents, the big four? They're going to throw all these resources at AI and so they'll be able to stay ahead? I'd be curious. If you have more like maybe everyone wins or everyone loses, I'd be curious.
Speaker 3:You know, to give you a sense of just the sheer number of firms out there, something like 40,000 public accounting firms that exist out there, right? So you think about heavy concentration and the top four from terms of kind of total market share, and then you kind of go to the next 200. And then you just have an enormous long tail and I think it's really a small proportion that do lose, but it's those again who don't have the capital resources, aren't willing to kind of change their business model and adapt along with the tools, and those are just going to be, you know, most of the micro-sized firms and smaller firms. And so you know that ultimately still results in the industry winning because those clients are displaced and going back to the title of, you know, death and taxes like this is work that has to get done right and so, as those clients are displaced from them, they'll just kind of go up chain, if you will, to the firms that have adapted, that are evolving and are in a position to be able to continue to serve clients.
Speaker 1:Do you think if I were to ask you and I guess this is our first guest, so this is my style of interviewing guests is trying to get them to give out some hot takes. But, knowing the position, whether or not you're able to give hot takes, if there's 40,000 accounting firms today and we were to say, with AI disrupting accounting in 10 years, how many accounting firms do you think that would be?
Speaker 3:It's a great question. I mean, I think that just in the boutique segment, which is close to, I think that just in the boutique segment, which is close to 35, I'm just going to do kind of some rough math here. Right, if there's 35,000 of those firms and you say, okay, 25,000 of those are kind of a million in revenue or less. I mean, those are the firms who are very ripe to be disrupted, displaced. Many of them are already closing their doors. They're writing letters to their clients saying, hey, I'm a year out from retirement, I'll do your stuff for one more year and then I'm going to be on my way, you know. So that let's say that you know, a 10th of them survive, right? So you've got kind of 2,500 firms and then I think you have four or five winners in the boutique level.
Speaker 3:We were certainly one of the first, if not the first, to focus on the boutique firms and really drive evolution through consolidation and becoming a platform. But there are now four or five of us and I think the space is big enough that there'll be four or five winners. So you have four or five winners at the boutique level. You have a lot, you know, four or five winners at the mid-market level, and then you have kind of your top 200 and your big four right. So roughly, I don't know, I mean again, this is kind of a guess of maybe there's only 3,500 or 4,000 or 5,000 in the future. But you know, even in the top 25, I think now you know now six of those are private equity owned. Again, those are probably big enough that they say distinct and separate. I don't see a lot of further consolidation of them, but in short, the number is going to be drastically less.
Speaker 1:It seems not crazy to say that a firm like yours could be 10x more productive in less than 10 years I mean five years, three years than you are today. So for the number to shrink from 40,000 firms to 4,000 firms just as napkin math doesn't shock me right, because you'll be able to soak up so much more additional work through the added productivity using AI for all these different tasks. That's right.
Speaker 3:Yeah, absolutely, absolutely.
Speaker 1:I'd be curious. I have one other question, actually, and then I'll hand it back to you, danielle but of the names on the map you know in that entries article we're talking about, are there any names on there that you're excited about? Are there any names on there that you think are really doing something interesting or working on a problem that you would love to see solved? I know you already mentioned one, but are there any other ones that kind of come to mind? Or even if they're not even on the Andreessen map, just other you know, ai companies in accounting that you think are doing interesting work?
Speaker 3:So one of the ones that we're most intimately familiar with is Carbon. I think you know they've been a strategic partner for us. We have a deep relationship with them and they're really attacking the whole practice management avenue and really thinking again, trying to think holistic about the challenges. They have some interesting things around automation with the client engagement Again kind of on that upfront intake, interesting data analytics that are coming out of their tools. So Carbon is certainly a winner. One of their direct competitors is in our backyard so I'm very close with the CEO there and Canopy. They're also doing very interesting things.
Speaker 3:They've deployed recently an AI tool around communication with the IRS. So in certain situations it's required to draft letters communicating to the IRS. You know certain issues that have very specific code. You know IRS code, references, form references etc. And so you know thinking about kind of a generative tool like chat, gpt, but then putting it in the context of communication with the IRS, which is a tax that is, you know, 80, 90%, the same for every client, and then there's kind of this 10% nuance there. They've deployed some interesting tools around that.
Speaker 3:So I think the practice management, you know, section is really interesting. You know we work with a company called Cinch AI was founded by Nigel Duffy who was and this maybe gives you a sense of what people see as the opportunity specifically even within kind of this boutique segment. He was a very senior person at EY, leading their AI initiatives for a long time, had the ability and did create, you know, into the hundreds of millions of margin you know through utilization of the tools. He recently stepped out and has now founded a very interesting company called Cinch AI who's doing really interesting things again on that front end process with us and then a number of things with other practices as well.
Speaker 2:So, as you're talking about these different firms and platforms, what's the value for, I guess, platform no pun intended for a free platform.
Speaker 3:I always say capital P or lowercase Okay. I didn't get very creative with the naming.
Speaker 2:So, as your for you platform uppercase P, what is the value for a company of your size to either partner with these tools as third parties versus developing in-house?
Speaker 3:your own tools. Yeah, I think some of the initial thing is just, you know, focusing on what you're good at. Right, we're very good at the acquisition. We've built a phenomenal acquisition engine. We've done over 40 acquisitions in the nine years and you know that comes with a whole host of specific skills around transitioning technology stacks, obviously the human capital element. So we're very it was hey, let's find people who are really good at this and a lot smarter than us on it, and just deeply embed ourselves with them, and so at some point we may develop some of our own. Sure, I don't see that in the near term, just because the acquisition opportunity is so large Again, sheer number of firms.
Speaker 3:You think about what percentage of those are facing some type of transition or evolution challenge that would drive them to merge. We've got our hands full on that front. The other benefit is that we're evolving with them, right? So again, going back to this idea of like you have to really restructure and think about your entire business model. That's something that can happen overnight, and so if you're deeply embedded with a partner as they're building and you're you know they're building the software you're also able to start to think about okay, operationally, what do we have to do to be able to utilize this tool and this technology, and we're doing that in a much more of a again. I've used this word a lot, but it's a core theme for us. We're evolving alongside with them, versus having to think about that at the time that the tool is like ready to be fully deployed, and try to turn things around quickly, which is nearly impossible.
Speaker 2:An industry or two industries that have adopted more AI than you would expect are financial services and healthcare, and a big part of that is because of the regulatory nature of those industries. They already have a lot of processes in place for consumer privacy and data privacy and compliance and whatnot, and so I'm curious when people think about taxes, obviously, all the information that goes into preparing a tax return is pretty sensitive, and so, within the accounting industry, what is already in place to help move this along and help integrate with these third party platforms that make sure that they have data security and privacy and all the things that people would be concerned about for themselves or for their company?
Speaker 3:Yeah, I think first is just an awareness and a prioritization of that right. So when you think about some of the names that I just mentioned, I mean those are some of our first questions to them hey, what's happening with our client data? And so, culturally, the industry already is saying, hey, this is of utmost importance, and so they're building it in day one. It's not a hey, let's just go as fast as we can, let's break stuff and we'll figure this out after. No, they know they have to address it up front, and so I think that that's important and that's again something that's top of mind and at the top of the list for us in terms of consideration.
Speaker 3:I think also, anytime you have again kind of defined code like an IRS code or a GAP code, right, you have, you know, just more guardrails and more specificity in the way data should be treated and what the outcome should be. And that also doesn't involve overly like a rapid pace, right, while there's been exponential growth over a long period of time of, like, the tax code, it's generally updated at a regular cadence versus like real time, and it's a very controlled way that it is updated. You can kind of generally see it coming so you can start to program that, I'd imagine. Again, I'm not very technical on the AI side, but I imagine you can feed that into the models for them to learn in a fairly steady cadence and in a structure kind of organized way, versus something that doesn't have. That, I think, would be much more challenging.
Speaker 2:And I'm thinking, wow, there's so many components of the ecosystem to really break down. So even just now, talking about the IRS, I'm thinking, well, what are they doing with AI? And somehow the IRS always knows what we owe in taxes, and then they make us figure it out ourselves.
Speaker 3:For sure, and if you get it wrong, they'll send you a notice, yeah, for sure For sure, which still baffles me.
Speaker 3:There's lots of funny memes about that for sure. Yeah, but I do think your point is right and I think when people hear, okay, ai is going to disrupt accounting, there's kind of two assumptions One, that it's on the actual accounting right, the actual function of preparing a tax return or preparing a financial statement, and that it is going to fully wholesale replace the human and as we talked about today. Right, you can see how. No, even just in the business model and the workflow management tools and you know the some of the output and productivity tools. Yes, but it really is a wholesale disruption that's happening not just on kind of the actual function of accounting.
Speaker 1:Yeah, if I had to ask you. I think I know my answer to this, but I'm kind of a futurist. It's like if we were to look 10 years in the future. Does an accounting firm like yours look more like a software company or like an accounting firm? I think about accounting firms being typically very human capital heavy, with a set of tools that they have at their disposal. And then I think about you know, even personal accounting. Right, people use TurboTax these days instead of like using a personal accountant. So does the accounting firm of the future look a lot more like a software company than like a traditional accounting firm?
Speaker 3:Yeah, I do, I do think so.
Speaker 3:Again, I think that you know I wouldn't put that even beyond the three to five-year time horizon right, but I do think it looks much more like a traditional software company and I do think that the value that is ascribed to the winners is probably much more like a software company Because, again, you think about not just this production function of preparation of financial statements and tax returns, but being able to leverage the vast amount of data that you have to serve the client better and give them a much, you know, more seamless, much richer, much more specific client experience, and so that's going to reward, you know, the client themselves with a better experience.
Speaker 3:I mean, you know, the biggest complaint across the industry is like, hey, my accountant does my accounting but they're not actually advising me, they're not giving me direction, they're not connecting me in a way that I want to be connected, and I think that that is eventually what we can get to. Again, massive challenges to be able to do that now, given all the things that we talked about in terms of the way that you know, the nature of the technology today, the talent shortage, et cetera, but eventually, you know, firms will win, staff will win. You think about the major complaint on staffing side. It's how many hours and how much input and the condensed timelines. You know what that creates in terms of burnout, doing lots of very like arduous, mundane tasks and work that eventually goes away right. So firms win, professionals win and ultimately the client wins, and I do think that then you start to look much more like a software company that then you start to look much more like a software company.
Speaker 2:What you're saying about clients' desire to be advised makes me think also of something that we hear a lot in the wealth management industry, and you mentioned even having a wealth management arm, and it's making me think. At some point does the role of accountant and wealth manager and financial planner kind of all become one because you have people who really just want to know not so much the tactical how do you do this thing? And especially as AI comes and does more and more of the tactical but more the strategic? What does this mean for how I invest? What is this for what I should be investing in? What does this mean for how I run my business? What does this mean for how I set up my business to optimize on the tax side or on the return on investment side, or whatever it might be? And so I'm curious your thoughts on that.
Speaker 3:Yeah, I don't know that the advisor themselves becomes a single person, because I think the domain expertise is important. You know, if I'm a client, I wanna know that there is important. If I'm a client, I want to know that there is a tax expert I'm talking to.
Speaker 2:I do want to know that there is a wealth advisor expert I'm talking to.
Speaker 3:I think of a again. There's a company in Utah called Homey and they set out to kind of just create a fully digital marketplace for home transactions. Eventually they hired a thousand agents or something like that. Because these are high stakes transactions, you want a human, you know, next to you in those and so maybe again down the line, when we as humans are comfortable not having a human intermediary or a human advisor that you know, that could kind of dissipate or lessen. But I think for the time being, and at least for me, in a foreseeable future, we want those human experts in those domains.
Speaker 3:What has already started to arise is much more of a client management coordinator role, right?
Speaker 3:Is you know, utilizing the technology, the information, the data and then having someone be a full kind of liaison, you know, through these different segments and offerings that a firm you know has. And I think that that becomes a really interesting and engaging role that started to emerge. And the nice thing is is it takes the burden off of the client to be the coordinator of all their advisors, right, I mean, even me still like I have to kind of connect my CPA with my advisor at Morgan Stanley, with my trusted estate lawyer right, and that burden is on me to like make the email introductions to you know, make the advisor aware of the tax you know events that have happened and make the CPA aware of the taxable events that have happened on the wealth management side. And so eventually I think that burden comes off of the client and is much more on the firm and is then facilitated both through kind of this evolution of a role as well as the evolution of the technology.
Speaker 2:I want to go back to what you said about humans getting comfortable with not interacting with humans. Do you think that happens, paul, for both of you?
Speaker 3:Yeah, I mean I heard Paul's version on. He feels safer in the Waymo and that actually surprised me. So maybe I mean, you know, paul, you're yeah, you're a futurist, you're a technologist, so you're kind of probably bleeding edge on most of this stuff. It made me pause and think like, would I feel safer? And there's probably some elements I would of this stuff. It made me pause and think like would I feel safer and there's probably some elements I would, and maybe with enough conditioning I would. I'd almost defer to Paul on this one of like how soon do you think that we would be willing to, you know, interact with the IRS if you know they say, hey, we're going to place a judgment on your home and you owe us, you know, $120,000 because you missed this tax filing, to just kind of go it alone with the machines.
Speaker 1:Yeah, there's a lot of concepts at play here, you know. One of them is just the idea of, like human in the loop and so, as you were talking about earlier, taxes are really ripe for disruption because there's a lot of repetitive processes and codified kind of rules in place, something that we need to follow. On the other hand, the thing that makes it a little bit less ripe for disruption is the idea that it's very high stakes, right. So you know you can't totally automate it away. You want to have some human loop process to say, okay, a human has actually checked this as a backstop to make sure that you know that situation doesn't happen. The IRS comes after you says you've totally missed up your return, you owe us a million dollars, we're going to take your house from you.
Speaker 1:But I do think there's ways to design these processes such that the first draft, if you will, gpt is the best first draft machine ever, right?
Speaker 1:The first draft of these taxes will often be totally automated and I think we'll find pretty high accuracy on those things, probably 90, 95% accuracy or something like that. And then for the remaining 5%, hopefully there's kind of this, you know, secondary human loop check where we say, like, actually, before the IRS comes after you, they're going to make sure that they go through with a fine tooth comb to make sure everything's fine, and so in that way we get the best of both worlds, right. You get the automation where it's working for 90% of the cases, and then only the special cases have to be handled by hand, and then that way we get this huge benefit. The other thing I would say is one of my takes on AI is that we underestimate the extent to which humans make mistakes, and so, when it comes to the driverless curse thing, right, we use human driving as a baseline and in our mind, for some reason, human driving is baseline safe, and in reality, human driving is actually baseline, not very safe, right.
Speaker 1:There's like 50 or 60,000 people a year who are injured or harmed in car accidents, it. But I think if we were to actually look at the numbers and then say, okay, if we take the assumption that human driving is not baseline safe, then it changes the way we think about AI autonomous driving, because the stats are actually much better on autonomous driving. So, yeah, a long-winded way of saying yeah, I'm obviously I'm more bullish that with AI firms like Platform and other accountants, will you know, and the IRS will hopefully find a way to be 10x more efficient, and then we'll have this kind of secondary human process to catch, you know, the ones that really need to be thought through carefully.
Speaker 3:Yeah, I think that's exactly right. I think there's also, you know, as you were talking about the cars. The other kind of thought that came to mind is this like control factor, control factor, right, like we have kind of this illusion of control when we're the one behind the wheel when, again, there's lots of different things around us that you know that we, we don't have control over, and so it is interesting that we use kind of a not safe, you know, baseline, yeah yeah, my autonomous driver is never hung over.
Speaker 1:They never have a bad day. They're never distracted. I mean, I guess they can be distracted by data, but like there's just so many things that don't happen there. And so the same is true for for accounting, right Accounting. Autonomous accounting agents of the future can work 24 seven. You know they don't. Ideally they don't miss details. I mean they will, but we'll have guardrails for things like that. You know they didn't accidentally spill coffee on a piece of paper. That was important or something. You know. Just all sorts of human things that happen go away when you start to move things towards autonomous agents that are interesting.
Speaker 2:Yeah yeah, I feel like we we're now getting into the really interesting side of things, and who knew this much time would fly talking about accounting.
Speaker 3:Right, no offense to anybody. I think it's awesome.
Speaker 1:One thing I do want to say this, I think one thing that's interesting because I know we got to wrap up soon here One thing, one dynamic I find interesting about the idea of AI disrupting accounting is in a lot of industries, we're talking about the fear that we have of AI taking people's jobs and, you know, going way back to the beginning, this one seems different because you're saying, no, people are retiring, we're not going to have enough people to do these jobs, and so, rather than there being this fear of, oh my God, ai is going to take our jobs, it's like no, no, no, we actually need AI because those, the people who are doing those jobs, are going away and there's just not enough human pipeline filling that back up, and so I think that's a slightly different dynamic here that I find pretty interesting.
Speaker 3:Yeah, and the tone is hey, it's welcome, right, I mean, it's viewed as a element that is necessary and going to be one of the things that kind of saves the industry, if you will. So it's arriving just in time, if you will, to be able to address what is a very deep, very pervasive challenge across the entire landscape.
Speaker 2:That's similar to the question I wanted to end on and I'm feeling like maybe we even need a part two at some point, so we can really get into this. But, this one question is for the 35,000 firms that we're talking about being displaced over the next, say, five to 10 years. Somebody who's at one of those firms and is listening to this what is your advice to them?
Speaker 3:I think it's embrace change, you know, and be willing to try new things and be willing to be uncomfortable. You know, one of the things that's interesting about transition is that it's, in the beginning, not always about efficiency. Right, you're coming in and you are breaking stuff, and so when a firm comes, you know, into platform, there is a transition period of time where we're being disruptive. I mean you'd be, despite the lack of kind of technology adoption, you would be really, I think, shocked to see how these firms do still run very efficiently because it's a tight group of people who have used shared language and shared process for sometimes 20 years.
Speaker 3:And we talk a lot about how the technology evolution that we're trying to institute isn't always just about efficiency. It might be about distribution of information, it might be about visibility of information, distribution of relationships, scaled management capability. Right, that change management can be hard and there's going to be learning curves and there's going to be, you know, kind of bumps along the way, for sure, and in an industry that values accuracy and who values time, because of the time crunches and those types of things, that can be very, very uncomfortable. And so I think you know, the first thing is embrace that change. And then the second thing is yeah, be very cognizant about how are you, especially a young professional, developing adjacent skill sets around again strategic thinking, communication, networking, to make you valuable when the time comes where most of the technical load is kind of being done by the machines.
Speaker 2:That was a great answer. I thought you were going to say call me.
Speaker 1:I was going to say if you need help with disruption, you can call Platform Accounting.
Speaker 3:Yeah, yeah, we welcome that. We welcome that too.
Speaker 2:Fantastic. Thank you so much for being here today, reyes. Really appreciate hearing your insights. I do see another part two coming at some point. I feel like we're just scratching the surface, paul, anything you want to add?
Speaker 1:I thought that was great. I thought that was a great last answer and it's really interesting, I would say. I guess one thing to add is, you know, when we talk to investors, we have been hearing, you know, a lot of investors have been really excited about verticalized AI apps. So, instead of kind of general AI apps, like, what verticals specifically are they going to be disrupting? And I know that accounting is definitely one.
Speaker 1:So it's really interesting to hear from somebody on the inside of it and some of the companies that you're working with and some of the companies you're talking to, and hearing kind of where it can disrupt things. And the reality is it's going to disrupt every piece of the accounting stack, just at different times. Right, Like there's lower, you know there's lower fruit to what's the phrase? That's a terrible phrase. There's a Low hanging fruit, lower hanging fruit to work on, which is some of the process stuff first, and then eventually working its way up to the more complex reasoning tasks of being more strategic with your accounting which complex reasoning tasks of being more strategic with your accounting, which is interesting, awesome, great chat.
Speaker 2:Thank you, thanks, arias, Thank you, thank you, bye.
