How Generative AI Is Changing The Game for Finance Professionals - Featuring Adam Tzagournis

Welcome to the Future Finance show where we talk about the top 10 reasons we hate Paper Legends.

The average accounting or finance person shouldn't need to be an expert in prompt engineering. It's just too much. You wouldn't expect them to become programming experts in order to build their own web browser in order to access Gmail. Long winded way of saying, you know, technology is always interested in me. Generative AI is something that is obviously radically different from what we've had before, and it does enable that step change in getting more out of a tool than what you put it. And that's that key equation there. Generative AI fits the bill really well for being that kind of tool. In the sausage maker where you put in some effort, you enter in some data, that sausage maker crunches the numbers. On the other end of it, you get out more intelligence or more insight than the effort that you put into.

What's the most surprising prediction you've seen about the future of finance that you actually believe in?

Okay, so I have.

Future Finance is brought to you by qflow AI, the strategic finance platform solving the toughest part of financing, Planning and analysis. B2B Revenue align Cells Marketing and finance seamlessly speed up decision making and lock in accountability with Qflow AI.

Researchers from the University of Chicago have demonstrated that OpenAI's GPT4 Turbo can outperform human analysts and specialize machine learning models and in predicting earnings changes from anonymized financial statements. This study, along with PwC's recent partnership with OpenAI, underscores the significant impact AI is having on the financial industry. The study, titled Financial Statement Analysis with Large Language Models, investigated the potential of foundation models in performing complex financial analysis tasks traditionally carried out by human analysts. By employing a chain of thought prompting techniques which mimics the step by step reasoning of financial analysts, the researchers enabled GPT4 Turbo to generate more accurate and contextually relevant outputs, achieving higher accuracy and F1 scores than human analysts. The implications of this study are far reaching for investors. AI models have the potential to provide more accurate and timely insights, enabling better informed decisions and potentially enhancing risk adjusted returns. Financial analysts, on the other hand, will need to adapt and develop new skills in data science and AI literacy to collaborate effectively with these tools. This symbiotic relationship between AI and human expertise allows for more nuanced and insightful analyses, with both parties complementing and enhancing each other. Companies can also benefit greatly from leveraging LLMs, gaining deeper insights into their financial health and market positioning. AI could analyze financial statements, market trends and even social media posts to identify potential risks and opportunities, allowing companies to be more proactive in their decision making. But with the increased speed of information processing brought about by AI, there's also concerns about market volatility and the potential for flash crashes. As AI becomes more prevalent in financial decision making, developing robust risk management strategies and regulations will be crucial to ensure market stability. The study's findings further show the power of AI in areas where even a year ago we thought were untouchable. And this is just the beginning. As these foundation models continue to improve, the potential impact of fine tuning these increasingly powerful models for specific domains could be even more profound. Fine tuning large language models for domain specific tasks is a powerful approach to enhancing the performance of AI in financial analysis. By training these models on specialized data sets like financial news, filings and reports, they could develop a deeper understanding of nuances and complexities in the financial world. The best known example of the power of fine tuning a model for finance is Bloomberg GPT, which is a proprietary model developed last year by Bloomberg. This model was trained using a mixed data set approach combining domain specific financial data with general purpose data sets. The idea being that Bloomberg GPT could excel in financial tasks while maintaining strong performance on general purpose benchmarks as well. The potential benefits of Fine Tuning LLMs for financial expertise are significant. These models can enhance existing financial natural language processing tasks like sentiment analysis, named entity recognition, news classification and question answering. As foundation models like ChatGPT, Gemini and Claude continue to improve, the potential impact of fine tuning these increasingly powerful models for specific domains could be even more profound. Fine tuned foundation models could provide deeper and more precise analysis of financial statements, identifying subtler patterns and trends that might be missed by less powerful models. The implications of fine tuning powerful base models extend beyond traditional financial analysis. These models could be used for a wide range of applications from risk assessment and fraud detection to automated reporting and strategic planning. As the power of these models rapidly increases, more innovative tech forward companies are embracing the technology, recognizing AI driven solutions transformative potential to enhance their operations and service offerings. We're already seeing innovative companies embrace AI. The latest and biggest example is the recent partnership between OpenAI and PwC. OpenAI has signed down 100,000 PwC employees to its ChatGPT Enterprise tier, making PwC its largest customer and first resale partner. This partnership enables PwC to integrate advanced AI technologies into their operations and also allows them to resell ChatGPT Enterprise to other businesses, highlighting a significant shift towards AI driven solutions in the professional services sector. By deeply integrating AI into its operations, PwC is setting a powerful example for other firms, illustrating the tangible benefits of adopting AI driven solutions and financial workflows. As AI becomes more prevalent, financial professionals will need to develop new skills in data science and AI literacy to harness the full potential of these tools. The future of finance lies in the successful integration of human expertise and advanced AI technologies which will unlock unprecedented levels of insight, accuracy and efficiency.

So what does all this mean for.

The future of finance? Well, AI isn't going anywhere and as companies and individuals try to figure out how to capitalize on this new technology, it's clear that a wait and see approach is not going to be the winning move here. As the technology evolves and likely even further outperforms human analysts and and specialized machine learning models, the financial industry must adapt by embracing collaboration, developing new skills, and implementing robust risk management strategies.

Welcome to a new section on future finance. Glenn when I were thinking it was time to have a little more fun with the show, so we're replacing the new section with you know your job is safe when as we all know, AI is wonderful. We all love it, but sometimes it goes a little off the rails and sometimes it goes a lot off the rails. The we're going to bring you news clips, stories, things AI has done that reminds us your job is safe for now. If that's the answer AI has given, Google been in the news quite a bit for some of the answers their AI Gemini has given and oh boy, this one's a doozy. Somebody asked it about the health benefits of picking your nose. They wrote the question was health benefits of nose picking. Here is the answer it gave. Some say that picking your nose and eating your mucus, also known as mucophagy, can have health benefits. Nasal mucus contains protective mucus and antiseptic enzymes that can act as a barrier against germs and bacteria. Eating that mucus may help protect, prevent cavities, stomach ulcers and infections and also boost the immune system may boost let me make that clear. However, there isn't much research to support these claims and eating mucus could actually increase infections by introducing more germs. Your job's safe for now, if that's what AI is telling us. My mom never taught me if I didn't want stomach ulcers to eat my boogers. My dentist never taught me I didn't want cavities. Just go ahead and pick in a little bit instead of brushing your teeth. Well, that's all for this new section. On to the next part of the show, but we hope you Enjoyed. You know your job is safe when. And look forward to the next story from Glenn and Paul on Future Finance.

Welcome to Future Finance. I'm Glenn Hopper and I'm here with my bearded co host, Mr. Paul Barnhurst. Our guest this week is Adam Zagornis. Adam is a friend of the show, which it seems weird to say that this is what, like episode three. And I'm already talking about Friends of the show, but Paul and I have both known Adam for a long time. And I guess really what I'm saying when I say he's a friend of the show is I'm kind of an Adam Zagornis fanboy. And the reason is he's the mix. I mean, it says right here, Adam's a CPA and a full stack developer and. And the founder of Flowcog Canvas. Flowcog is a drag and drop no code tool designed to make projections easy.

For finance and accounting teams.

Before Flowcog Canvas, Adam was director of finance at Stack Overflow. And he lives in Austin with his wife and two kids. And we're very excited, Adam, to have you on the show.

Absolutely. It's great to see both of you.

You know, and add this all in talking about the unicorn, I have to add one thing. He has not only a finance degree, but Spanish, so he can code, he can speak multiple languages, and he could talk to accounting nerds. Could we ask for a better guest? Glenn, let's be honest.

It's my zone of competence that. That overlap there.

You know, one of the big things we talk about on this show is obviously technology, future finance. Where are we going? And I know you were one of the early adopters. Your tool was one of the first ones to add generative AI. What made you such a big adopter early on? Why did you jump on the bandwagon kind of from day one, so to speak?

Yeah, it's a good question. I think it goes back to even my days, way before any of this AI talk.

Right.

Sitting as a freshly minted graduate and in the PwC audit room, trying to save the audit team some time and help us go home a little bit early. During busy season, early means midnight instead of 2am and so how can you automate any amount of that work? Is it better Excel formulas and structure to the spreadsheets? Is it a Visual Basic, you know, script and using macros? Any tool that can help you achieve what you're trying to.

Right.

Doesn't matter what flavor or form it comes in, doesn't matter if it's a tool. Baked into Excel doesn't matter if it's a programming language, right? It's whatever tool gets the job done. And it just so happens that now we have access to, you know, what we used to have access to was an abacus. Now we have access to supercomputers, right? To do that, to crunch those numbers for us. So it's a radically different world that we live in these days. So having said all of that, right, even from the early days, I saw that, okay, if there's a problem and there's a bottleneck in the process, that's what it comes down to in the audit room even, right? How do you get through these work papers? How do you make sense of them? How do you confirm that they're legitimate? So being not so much obsessed with the tool or your solution, but really focusing on the problem at hand in the situation, the players in the game at that point, right? You know, to use, to, to use this example, if I were to have given all of the folks in the audit room back in 2011 and a generative AI tool, it wouldn't have helped, right? Folks are not ready for that in 2011. They still may not be ready for it in 2020, 24, but they certainly weren't ready for it back then. And so it comes down to understanding your audience, right? Understanding that the tool that you're giving them, the tool for the job, is the one, the best one to use is the one that actually solves the problem or the pain point at that time for those folks, technology progresses and folks get more and more used to software. You see different automations along the way. I won't give the whole history of, of how much better the world of software is these days compared to 2011, of course, but, you know, we introduced, you know, the, the term, if you're familiar with it, robotic process automation along the way. Other kinds of automations, zapier, for instance, gluing different tools together, wrangling the data and getting it in one place. So folks are more familiar and kind of used to, and acclimated to the idea of using software or using an external tool to help solve a problem as opp, to just being limited to something like Microsoft Excel. And even if we talk about just Excel, they've added plenty of new features over the years where it's a lot more useful now than it was, you know, back 10 years ago. So that's kind of given a. That's kind of softened the introduction to this radically new world, which is generative AI and the Thing that really got me the most interested in it was seeing how much better of a job it can do for getting you value from a tool in the shortest amount of time?

Right.

Everyone is always short on time. Doesn't matter what role you're in. If we're talking accounting and finance especially, right, you're not going to get the big budget at the company to over hire in those departments. That's extremely rare. Most of the time you're really running on a skeleton crew. So any time you can save is that much more valuable.

Right.

So the idea then is okay, we're getting so much better technology wise. Why is it that we have to still put so much time and effort into the tools that we're using and get out on the other end the same, if not less value versus what we put in.

Right.

So the idea then is okay, how do we have this kind of middle step that amplifies or really increases the amount of value that we're getting out of the tool without requiring us to put in 20, 40, 60 hours into this tool?

Right.

So it's that, it's that kind of equation there and the middle part is where the generative AI fits in that.

Really resonates with me because I my own, again, not to the scale that you are, but my own history with, with tech in finance came from when I was in Telcom. I had a team of like 31 people and they were doing, we were doing some really great reporting. This is back in the stone ages. I think we were all working on Commodore 64s back then or whatever it was, but I left that and then I became my first CFO role. I was a CFO and had three people working for me and we were trying to raise money and we had all this. I wanted to have the same level.

Of reporting that I did at the.

Big telecom, but we, there was no way we didn't have enough people so leaned in early to the tech side and it's really necessity is the mother of invention. So that completely resonates with me. Your, your sort of approach to it and how you found solutions there and then, you know, it sort of just as the technology expands, the potential and possibilities expand too. So now we're in this generative AI world and we're just. Before recording this episode, we had OpenAI's announcement about ChatGPT4O. Last week we had the Google I O conference. We're heading into Microsoft Build, the Apple Developer conference. We maybe GPT5 in the coming months. I mean looking back at just say, the past 18 months, the pace of development in generative AI has been wild. It's unlike anything I've seen in my professional career. I'm just, I'm wondering, you know, and we. There's all kinds of disruptions right now with alignment and safety and how close are we to AGI and all that. But I'm. This technology is coming faster than. Like you said, we weren't ready in 2011, a lot of us aren't ready in 2024. Where we are with technology right now, on one hand, there's the getting people, sort of the change management part of it, getting people comfortable using the technology. But then that has to happen quickly because the tech is moving so fast. I mean, do you think right now, are we just going to stay on this exponential rocket ship or do you think it's going to slow and there's going to be some realignment issues? Where do you think we are with.

The tech right now?

Yeah. So there's a couple ways of looking at this, right? If you want to think of it as a layer cake, right? You have the kind of this base layer, the foundation models, the ChatGPT 4 versus 3 and the improvements there. But it's also all of the other layers in that stack, in that cake that have to catch up to that base layer, right. I would argue that even if we stopped right now in terms of AI advancements, there is still so much benefit to be had by actually properly building that technology into the existing software stack to help folks today.

Right?

So I would say that there's, you know, there's a good amount of acceleration left on the base layer of these models and how intelligent they're getting and how quickly we're moving as a society at that base layer. But it's also the implementation and the execution of translating that advancement, that technology, to the problem that's at hand for anyone that would want to use something like this.

Right.

When ChatGPT first came out, a lot of folks thought, well, this is a solution looking for a problem. But the more and more you use it, the more you start to find these kind of small problems or these niches where it actually makes a lot of sense to have something like generative AI, even if it doesn't complete or solve the problem for you entirely. It's. It completes steps, you know, one through four, and then you still have to go in and do four through eight. But what used to take, you know, 10 hours maybe now only takes two hours, right? So for a lot of a Lot of folks when they look at AI, they're like, well, is it going to replace me? Is it going to replace all of my workflows? It's not that black and white. It's this grayscale of. It's a tool that you can use to really save yourself a bunch of time. And there's a lot of benefit in that. You know, it. It doesn't necessarily mean that jobs won't be displaced.

Right.

There might be fewer folks entering in manual. Manual journal entries in the future than they are now, but that's that time is going to be reallocated to. Okay, now we are, and this is kind of a hypothesis or a thesis that I have for the future of the. The direction that the accounting and finance profession is moving in. That just means that the. I like to call it like the humble accountant is going to be elevated at some point.

Makes a lot of sense and. Except you said as I think of it as a productivity. Right. I mean that's really where generative AI is. It helps us be more productive. Are some jobs going to go away? I think I'd be lying if I said I don't believe any jobs will go away. Will jobs be created? Yes. I think overall it'll be a net positive to the economy. Yes, because we'll be more efficient. We'll be able to reallocate time. But yeah, there'll be changes in jobs just like there was with the Internet, just like there was with the telephone, just like there was with the computer. All of those things change industries. And I don't see this being any different. There's no reason that I've gone out there and thought, oh yeah, I'll be different this time. So I get the fear. But what I'm curious, you know, when you talk generative AI is I want to ask you a question. You've been using it a lot. Like I said, I know you adopted it early. So I'm curious, what's the most maybe unique use case you've seen or most interesting thing you've done so far with AI? What's been your kind of oh, wow, it can do this type of moment Ever feel like your go to market teams and finance speak different languages? This misalignment is a breeding ground for failure, impairing the predictive power of forecasts and delaying decisions that drive efficient growth. It's not for lack of trying. But getting all the data in one place doesn't mean you've gotten everyone on the same page. Meet qflow AI, the strategic Finance platform purpose built to solve the toughest part of Planning an analysis. B2B Revenue QFLO quickly integrates key data from your go to market stack and accounting platform, then handles all the data prep and normalization under the hood. It automatically assembles your go to market stats, makes segmented scenario planning a breeze and closes the planning loop. Create airtight alignment, improve decision latency and ensure accountability across the teams.

Yeah, so I would say, you know, again, getting back to what are the everyday problems that accounting and finance comes across and where does this fit into their existing workflow or what does it unlock for them, right? So, you know, a lot of times the solution that AI brings to the table is not necessarily the sexiest one, right? And you know, a good example would be in my tool. It's a financial projections tool. It's very much on the end of trying to give a soft transition to folks that aren't used to using software all the time or are not kind of really dialed into this whole AI world. Giving them a tool that's dead simple to use, that kind of abstracts away a lot of the tech jargon and all that stuff. And you know, for instance, gives them the ability to easily import QuickBooks data, right? That doesn't sound sexy, right? You think, well, there are plenty of tools out there that allow you to import QuickBooks data, but the idea is that if you have something like generative AI now, it can go in and say, okay, let me really look at the QuickBooks data for the user. Let me categorize it all and group it together and present that in a way that's a lot more digestible, right? So again, as the accountant or the, you know, the accounting firm that, that goes and talks to the clients to offer any insight, you still may have to, to add your take on the numbers and kind of add in some explanations there. But you are, from the standpoint of your time, right? You're, you're reallocating your time from that, from the legwork of wrangling all of that data and getting it together and all the kind of error prone processes involved with that to now you're clicking a button and something is going on behind the scenes that it's not really important what is happening back there. The important part is that it's saving you a bunch of time and giving you the categorizations and the groupings and presenting it to you nicely. So now you can have that, that end result to then package to your, to your client, right? Summarize these results in plain English.

Right.

Instead of adding more complexity to the, the process. And okay, now, you know, I'm using Excel and software and generative AI. And your head is spinning from all these different technologies. How can we kind of simplify it and you know, abstract away as much of that, that legwork or those intermediary steps as possible. And so, you know, click a button, get a result in plain English of what my historical data looks like or what it's telling me, what the trends are in it, and then what, how that lines up with the projections that I've entered into this tool as well, how those two things play nicely. If there's something way off, if I'm projecting way more revenue than I, than we had historically, pressing a button and getting an answer and getting a gut check on that is kind of a great use case for AI.

Right.

That's what most folks want, is a simple explanation in plain English to pass on to the decision maker of the company.

Right.

Accounting and finance in its end state. The real kind of job to be done here is serving that internal or sometimes external if you're an accounting firm customer, to help them make better business decisions. Right. So what that looks like is not this complex, you know, 45 tab Excel financial model. A lot of the times it's a plain English explanation that is backed by numbers.

Well, thank you, thank you for that. Adam. We have just another question here and then we're going to move into what we call our fun section. So you'll, you'll like that. So, you know, one question I have for you is you talked a little bit about this, but just like to get your kind of, you know, kind of quick two minute thought of how should the me, the small and medium businesses think about all this? As you know, Glenn and I both know and as you see, there's a ton of worry, we've talked a lot about this, that they're getting left behind. Companies are like, how do I start adopting this? So where do we start? What would you advise smaller small to medium sized companies to be doing today to take advantage of where AI is at and to prepare themselves for the next couple years? Any thoughts there?

I have a few different opinions on this. I would say, you know, one of them is it's the onus is not always on the end user to understand all of the technological advancements. Right. That's kind of the benefit of having this highly leveraged mechanism called software, kind of translate those advancements in technology to a better end product for the user. So, you know, on one Hand, I would say that things should just get better for the end user. If developers like myself or startup founders like myself are doing their job properly, they. But I don't think that that's the full picture, right? I don't think you don't want to put your eggs in that basket of, well, everything's just going to get better and all the details and the tech is going to be abstracted away. So I don't need to learn about this at all. I would say get out there, play with ChatGPT. It's free, ask it some questions. If you come across a problem or a bottleneck in your business, you know your first thought, and I've kind of learned this a lot of the times, a great first step to solving any problem is what kind of answer is ChatGPT going to give me? If you can have these AI enabled tools adjacent to the problems and workflows that they're already engaged in trying to solve on a daily basis, that's the area where they can start to see the benefit of those things, right? So I think it was last week or the week before you had on founder of Puzzle, the new accounting system that's AI enabled, right? And when you think about kind of what they're doing in terms of introducing AI and really the benefits of it, right? Not necessarily all of the inner workings of all of the stuff that they need to do on their end in order to make accounting easier for startups and accounting firms, kind of what the end result of those efforts are on their end. And it's pretty amazing, right? Because when you think about it, and you know, I share a lot of Sasha's vision in terms of where the direction of this industry is going, right? And you know, podcast that I listened to that you did with, with Sasha, he, he made a great kind of distinction or had some, some good thoughts on this idea of making that data layer, that base data layer of all the accounting data easier to be consumed by other LLMs or AI models, right? So I last week announced an integration with Puzzle where you can import your accounting data from Puzzle into Flowcog Canvas. And the idea there is the business owner, like I said, already has to solve the problem of bookkeeping behind the scenes. Puzzle is doing that for them, but it's also setting them up for success. They show that result to them within their accounting system, but they also then get the benefit without even knowing it, that now their data looks a lot better and a lot different than it otherwise would and now it's ready for Even further analysis and the next step of that, which is projections and asking these what if questions to try to get a better understanding of, of where your business is going and, and to help you actually make decisions about the future.

Right.

I use this quote all the time, but I think it's so appropriate for what we're doing with AI and where.

The value is added.

It's that Clyfford Stoll quote and Paul's.

Heard me say it a million times.

But it's data is not information.

Information is not knowledge.

Knowledge is not wisdom and wisdom is not understanding. But what we're seeing, I mean, to me that sort of describes the pyramid of, you know, moving up the value that we're getting from AI and where.

Our focus is shifting.

So when AI just seamlessly integrates and you have these, you know, systems like yours and like puzzle that you mentioned that are set up to already be ready to sort of integrate and communicate with it, it just adds that extra layer of value there. So I think that this is, I mean we're, we're really just on the cusp of this whole new world where it's yes, the numbers are down there, but we're more at the, the value level and the interpretation of the numbers and higher up in the pyramid. Okay, so we do want to get to our random section of the show and we've been experimenting with the different LLMs. I'm going to go ahead and say it. I wasn't really happy with the questions that Jim and I created the other week. We did some just through. We built a GPT that's supposed to come up with random questions based on the topic of the show so that we sort of stay in. And then with 4.0 coming out, I just decided this week for mine that I would just ask 4O some questions. So while, while you were talking, I've got a couple of examples here and I'm going to pick one. All right, I'm going to snag this one. All right, so if you could host a finance themed reality TV show, this is going to test your quick thinking. If you could host a finance themed reality TV show, what would it be called and what would it be about?

Let me think about this for a second. So what would it be called? What is it about? Okay. Okay. What it's going to be called is what are we doing here?

Right.

A lot of times finance and accounting folks lose sight of the end goal.

Right.

They think it's all about head down in the spreadsheet, hardcore analysis Modeling all that stuff, which by the way, I love, I love nerding out on that. Happy to talk about that anytime with, with anyone. I put out a lot of content on that as well. But at the end of the day, what are we all doing with that information? What is the problem that we're actually trying to solve?

Right.

And at the end of the day, it is about helping that end user, the business owner, the CEO, whoever, actually make a real business decision to run their business better.

Right.

Like that. That's the whole purpose of accounting and finance. So in this finance themed reality TV show, everyone would be, you'd have, let's say a, a prompt each week from a business owner and you would then watch everyone almost like, you know, great, great British baking show. Everyone take their raw ingredients of Excel, any tools they want, whatever, and at the end of the day they have to produce some sort of report or memo or suggestion to the business of how they can improve.

Right.

And the reason that it would be focused on that kind of improvement metric, I guess, is because that will help train all of the folks in it and all the folks watching our new amazing finance themed reality TV show to orient themselves toward helping solve real problems that business owners or clients have with their business.

Right.

They don't care how fancy your Excel spreadsheet is. They don't care how great your xlookup does and how great of a spreadsheet structure you have or even how fancy the software tools you're using are. They care about actually making their business better. That's why they hire you, that's why you're on the payroll. And so I already forgot the name of our new reality TV show. What are we, what are we doing here? Exactly. Really thinking about the end in mind.

I love it. In secret show twist, one of the contestants is an AI.

One of the. Yes, exactly. That's, that's the, that's the ringer there.

All right, I'm going to go back to last week's questions because I'm old fashioned. Glenn's on the cutting edge of everything and I'm just a little slow in this whole AI thing. That's why I'm, you know, here to balance them. So we're going to use a random number generator. Last week we had 29 questions. I'm going to generate a random question and that's what we're going to ask you. So you ready?

Yep.

It gave question number three. All right, number three is what's the most surprising prediction you've seen about the future of finance that you actually believe in.

Okay, so I have, I don't know that I've seen so many wild predictions that I, that I believe, right? I mean, there's some out there that are saying, well, the entire finance and accounting industry is going to be axed. We'll, we'll just have AIs doing that for us fully. I don't buy into that. I, I think that that's throwing the baby out with the bath water. I, I ultimately think that, you know, human judgment plays a massive role in, again, the end result or the end goal of accounting and finance, which is helping businesses make better decisions. I can come up with my own prediction that I have about the future of finance that I actually believe, which is that I do think ultimately that finance orgs in bigger companies, they wear different hats, right? It's not just FP and A. They, they do treasury management and all, all sorts of other things, right? They have other responsibilities. I do think this idea of accounting and finance data and spending a lot of time wrangling it and analyzing it, I do think that's going to be squeezed out to the point where you're gonna see that again, coming back to the humble accountant, you're gonna see the accounting role kind of eat into the finance role or they're really gonna blend together, right? So the finance role is not gonna go away. It's just that they're going to get a lot more competition from the accountants in the world that are now enabled or elevated to this, to this kind of higher purpose of being able to really provide insight about the numbers as opposed to just being the, you know, keeping track of yesterday's newspaper, right, to, to, to take a jab at accounts. I'm a CPA as well, so I, I have only the utmost respect for, for my fellow accountants. Um, but I do think that eventually they will kind of get folded into this, this more of a, a kind of hybrid role. And so the idea then is, okay, how to get ahead of that and not get lost in that transition. And it really comes down to leveling yourself up and being able to be a better kind of business partner to the rest of the, the company, your client, to the CEO, whoever you work with. And understand that a lot of the base layer of accounting that's going to be abstracted away at some point, right? So maybe not a too wild of a prediction, but I would say that, you know, the, the more interesting part of this is the timeline on which it's going to happen. I'm thinking more on the, in the call it five year range. This is not a 20 year time horizon. This is going to happen in the next five years. Pretty confident in that. So it's, it's more of a, I would say the transition then is getting folks comfortable with either a set of tools or going deep on some of these things. Now they have a little bit of a head start. But understanding that eventually, yes, that the accounting and finance roles as we know them today are going to look very different in the next few years.

I, I could agree with that. We're definitely going to see some change. So we appreciate you sharing that and I think we're right at about time. So we'll call it there for today. We appreciate appreciate you joining us with with us, Adam, and sharing some of your wisdom. We'll put your contact information in the show notes so people can get a get a hold of you. We know you're on LinkedIn so people can reach out to you there. And we really appreciate you taking some time and chatting with us about how AI is changing the future of finance. So thanks for being with us, Adam.

Absolutely. Thanks Paul and Glenn, really appreciate it.

All right. Thanks Adam.

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