How Generative AI Is Changing The Game for Finance Professionals
Show Notes
TLDR: These show notes were optimized using Google Gemini after we tried Meta Llama 3 8B and ran into issues. The show notes are designed to make you listen to the full episode thanks to AI.
Below is a poem for the show from Gemini
The numbers whiz by,
a blur in the night,
Financial wizards locked in a fight.
AI swoops in, a tool sharp and bright,
Saving precious hours,
making data take flight.
Future Finance: AI Revolutionizes Financial Planning
Welcome to the exciting world of Future Finance! Today's episode dives into the transformative power of Artificial Intelligence (AI), specifically generative AI, in the financial industry. Our guest, Adam Tzagournis, a CPA, full-stack developer, and the founder of FlowCog Canvas, joins Paul Barnhurst and Glenn Hopper for a thought-provoking discussion.
Here are the key takeaways to whet your appetite for the full episode:
Generative AI for the Win: Researchers are making significant strides in AI, with studies demonstrating its ability to outperform human analysts in tasks like financial statement analysis. This translates to more accurate and timely insights for better decision-making.
AI as a Powerhouse for Productivity: Generative AI automates repetitive tasks such as data analysis and reporting, freeing up valuable time for finance professionals to focus on strategic analysis and decision-making.
Human-AI Collaboration is Key: The future lies in a collaborative approach where AI empowers human expertise. Financial professionals can leverage AI tools to gain deeper financial insights and proactive risk management strategies.
The Rise of the Evolving Workforce: The financial industry is on the cusp of a transformation. While some jobs may be displaced by AI, new roles will emerge, emphasizing the need for data science and AI literacy.
Follow Adam:
LinkedIn: https://www.linkedin.com/in/adam-tzagournis-cpa/
Website: https://canvas.flowcog.com/
Follow Glenn:
LinkedIn: https://www.linkedin.com/in/gbhopperiii
Follow Paul:
LinkedIn: https://www.linkedin.com/in/thefpandaguy
Follow QFlow.AI:
Website: https://qflow.ai/future-finance
Stay tuned for the full episode where you'll learn more about the exciting applications of generative AI in financial projections, the future of financial roles, and much more
Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.
Learn more at Qflow.ai/future-finance.
In today's episode:
[06:54] Introduction
[07:30] AI and Nose-Picking
[08:55] Guest Introduction
[10:10] Early Adoption of AI
[13:28] Generative AI in Financial Projections
[17:00] Pace of AI Advancements
[18:12] AI as a Productivity Tool
[25:39] AI for Small and Medium Businesses
[30:35] Fun rapid-fire Session
[33:40] Future of Finance Predictions
[36:50] Contact information for more learning opportunities
Full Show Transcript:
Host: Paul Barnhurst:: Welcome to the Future Finance show, where we talk about.
Host: Paul Robotic:: Top 10 reasons we hate paper ledgers!
Host: Paul Barnhurst:: Your tool is one of the first ones to add gender to the I. What made you such a big adopter early on?
Guest: Adam Tzagournis:: Is it better to Excel formulas and structure the spreadsheets? Is it a Visual Basic script using macros, or any tool that can help you achieve what you're trying to write, it doesn't matter what flavor or form it comes in. Doesn't matter if it's a tool baked into Excel. It doesn't matter if it's a programming language. It's whatever tool gets the job done. We're heading into Microsoft Build, the Apple Developer Conference, and maybe GPT 5 in the coming months. 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 ten years ago. That's kind of softened the introduction to this radically new world, which is generative AI.
Host: Paul Barnhurst:: Future Finance is brought to you by QFlow.ai, the Strategic Finance platform, solving the toughest part of planning and analysis. B2B revenue-aligned sales, marketing, and finance seamlessly. Speed up decision-making and lock in accountability with QFlow.ai.
Host: Glenn Hopper: Researchers from the University of Chicago have demonstrated that OpenAI's GPT 4 turbo can outperform human analysts and specialized machine learning models 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 technique that mimics the step-by-step reasoning of financial analysts. The researchers enabled GPT 4 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 LMS, 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 are 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.
Host: Glenn Hopper: 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 and 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 dataset 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 LMS for financial expertise are significant. These models can enhance existing financial natural language processing tasks like cinnamon analysis, named entity recognition, news classification, and question answering. As foundation models like ChatGPT, Gemini, and Cloud 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.
Host: Glenn Hopper: As the power of these models rapidly increases, more innovative tech-forward companies are embracing the technology, recognizing AI-driven solutions, and 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. Open AI has signed down 100,000 PwC employees to its ChatGPT enterprise tier, making PwC its largest customer and first retail 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 specialized machine learning models, the financial industry must adapt by embracing collaboration, developing new skills, and implementing robust risk management strategies.
Host: Paul Barnhurst:: Welcome to a new section on Future Finance. Glenn and I were thinking it was time to have a little more fun with the show. So we're replacing the news 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. They are going to bring you news clips, stories, and things AI has done that remind us your job is safe for now. If that's the answer AI has given. Google has 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's 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 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 is 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 it. You know your job is safe when and look forward to the next story from Glenn and Paul on Future Finance.
Host: Glenn Hopper: 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 Tzagournis. Adam is a friend of the show, which I. It seems weird to say that we're. 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's fanboy, and it's. The reason is he's the mix. I mean, it says right here, that Adam's a CPA a full-stack developer, 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.
Guest: Adam Tzagournis:: Absolutely. It's great to see both of you.
Host: Paul Barnhurst:: 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 also Spanish. So he can code, he can speak multiple languages and he can talk to accounting nerds. Could we ask for a better? Yes, Glenn? let's be honest.
Guest: Adam Tzagournis:: It's my zone of competence that overlaps there.
Host: Paul Barnhurst:: 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 gender to the 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?
Guest: Adam Tzagournis:: Yeah, it's it's a good question. I think it goes back to even my days way before any of this AI talk. Sitting as a freshly minted graduate in the PwC audit room, trying to to save the audit team some time and help us go home a little bit early during during busy season, early means, you know, midnight instead of 2 a.m. and so, you know, how can you automate? Any amount of that work. Is it better Excel formulas and structure to the spreadsheets? Is it a Visual Basic? Script and using Macros? Any tool that can help you achieve what you're trying to. It doesn't matter what flavor or form it comes in, doesn't matter if it's a tool baked into Excel. It doesn't matter if it's a programming language. It's whatever tool gets the job done. And it just so happens that now we have access to, what we used to have access to was an abacus. Now we have access to supercomputers. To do that to 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, even from the the early days, I saw that, okay, if there's a problem and there's a bottleneck in the process. Because that's what it comes down to in the audit room, even. 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.
Guest: Adam Tzagournis:: You know, to use this example, if I were to have given all of the folks in the audit room back in 2011 a generative AI tool, it wouldn't have helped. Folks are not ready for that in 2011. They still may not be ready for it in 2024, but they certainly weren't ready for it back then. And so it comes down to understanding your audience. 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 automation along the way. I won't give the whole history of how much better the world of software is these days compared to 2011, of course. But we introduced, the term if you're familiar with it, robotic process automation along the way. other kinds of automation, Zapier, for instance, gluing different tools together, and 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 opposed to just being limited to something like Microsoft Excel. 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 ten years ago.
Guest: Adam Tzagournis:: So that's kind of given a that's kind of softened the introduction to this radically new world, which is generative AI. 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. Everyone is always short on time. Doesn't matter what role you're in. If we're talking accounting and finance especially, 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, is that much more valuable. 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. 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? So it's that it's that kind of equation there. The middle part is where the generative AI fits in.
Host: Glenn Hopper: That really resonates with me because my own again, not to this scale that you are, but my own history with tech in finance came from when I was in telecom. I had a team of like 31 people and they were doing some really great reporting. This is back in the Stone ages, I think we were all working on Commodore 64 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 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 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 ChatGPT 4.0.
Host: Glenn Hopper: Last week we had the Google IO conference. We're heading into Microsoft Build, the Apple Developer Conference, and maybe GPT 5, in the coming months. I mean, looking back at just the, say, the past 1 and 8 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 wondering, you know, and 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?
Guest: Adam Tzagournis:: So there are a couple of ways of looking at this. If you want to think of it as a layer cake. You have the kind of base layer, the foundation models, the chat GPT 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. 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. 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 who would want to use something like this. 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.
Guest: Adam Tzagournis:: Even if it doesn't complete or solve the problem for you entirely, it's it completes steps, one through four, and then you still have to go in and do four through eight. But what used to take, ten hours may now only take two hours. So for a lot of folks, when they look at AI, they're like, well, is it going to replace me as it can 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 doesn't necessarily mean that jobs won't be displaced. There might be fewer folks entering 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 direction that the accounting and finance profession is moving in. That just means that what I like to call the humble accountant is going to be elevated at some point.
Host: Paul Barnhurst:: Makes a lot of sense, something you said is I think of it as a productivity tool. 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, it'll be different this time. So I get the fear. But what I'm curious about when you talk generative AI. I want to ask you a question. You've been using it a lot. I 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 the 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-togo-to-market 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 and analysis of B2B revenue. QFlow quickly integrates key data from your go-to-market stack an accounting platform, then handle all the data prep and normalization. Under the hood, it automatically assembles your go-to-market stacks, makes segmented scenario planning a breeze, closes the planning loop, creates air-tight alignment, improves decision latency, and ensures accountability across the teams.
Guest: Adam Tzagournis:: I would say, 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. So you know, a lot of times the solution that AI brings to the table is not necessarily the sexiest one, a good example would be in, in my tool to 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, you know, tech jargon and all that stuff, for instance, gives them the ability to easily import QuickBooks data, that doesn't sound sexy. 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.
Guest: Adam Tzagournis:: Let me categorize it all and group it together and present that in a way that's a lot more digestible. So again, as the accountant, or 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. 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 end result to then package to your client. Summarize these results in plain English. Instead of adding more complexity to the to the process. And okay, now I'm using Excel and software and generative AI and your head is spinning from all of these different technologies.
Guest: Adam Tzagournis:: How can we kind of simplify it and, you know, abstract away as much of that, that legwork or those intermediary steps as possible? So, 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 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 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.That's what most folks want, is a simple explanation in plain English to pass on to the decision maker of the company. 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, help them make better business decisions. So what that looks like is not this complex, you know, 45 tab Excel financial model. A lot of the time it's a plain English explanation that is backed by numbers.
Host: Paul Barnhurst:: Well, thank you for that, Adam. We have just another question here, 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 quick two-minute thought of how the small and medium businesses think about all this is, Glenn and I both know and as you see, there's a ton of worry. We've talked a lot about this and they're getting left behind. Companies are like, how do I start adopting this? As you've mentioned, we're not expected to be prompt engineers or we shouldn't be. You feel like that's too much. So where do we start? What would you advise for these 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 of years? Any thoughts there?
Guest: Adam Tzagournis:: I have a few different opinions on this. I would say, one of them is it's the onus is not always on the end user to understand all of the technological advancements. That's kind of the benefit of having this highly leveraged mechanism called software kind of translates those advancements in technology to a better end product for the user. So, you know, on the 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. But I don't think that that's the full picture. 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 and 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 time. 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. So I think it was last week or the week before you had on the founder of Puzzle, the new accounting system, that's AI-enabled. When you think about kind of what they're doing in terms of introducing AI and really the benefits of it. 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.
Guest: Adam Tzagournis:: And it's pretty amazing. 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. Podcasts that I listen to that you did with, with Sasha, 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 LMS or AI models. So last week I 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 uzzle 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 where your business is going and, and, to help you actually make decisions about the future.
Host: Glenn Hopper: 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 Clifford 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, moving up, the value that we're getting from AI and where our focus is shifting. So when I just seamlessly integrate 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, the an extra layer of value there. So I think 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 LMS. 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 Foro coming out, I just decided this week, for mine, that I would just ask for 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. 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?
Guest: Adam Tzagournis:: Let me think about this for a second. So what would it be called? What is it about? Okay, what it's going to be called is what are we doing here? A lot of times finance and accounting folks lose sight of the end goal. 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 nodding out about that. happy to talk about that any time 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? And at the end of the day, it is about helping that end user, the business owner, the CEO, whoever actually makes a real business decision to run their business better. Like that. That's the whole purpose of accounting and finance. So in this finance-themed reality TV show, everyone would have, let's say a prompt each week from a business owner, and you would then watch everyone almost like, you know, great, great British Baking Show, everyone takes their raw ingredients of, excel, any tools they want, whatever.
Guest: Adam Tzagournis:: 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. 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 or, clients have with their business. They don't care how fancy your Excel spreadsheet is. They don't care how great your Xlookup you know does, 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 T.V. show. What are we what are we doing here? Thinking about the end in mind.
Host: Glenn Hopper: I love it in a secret show twist. One of the contestants is an AI.
Guest: Adam Tzagournis:: Yeah, one of the. Yes, exactly. That's the ringer there
Host: Paul Barnhurst:: 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, 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? It gave question number three. What's the most surprising prediction you've seen about the future of finance that you actually believe in?
Guest: Adam Tzagournis:: Okay, I don't know that I've seen so many wild predictions, that I that I believe. 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 eyes doing that for us fully. I don't buy into that. I think that that's throwing the baby out with the bathwater. I ultimately think that 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 organs in bigger companies wear different hats. It's not just FP&A, they do treasury management and all sorts of other things. 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 going to see that again, coming back to the humble accountant. You're going to see the accounting role kind of eat into the finance role, or they're really going to blend together. So the finance role is not going to 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, or elevated to this, to this kind of the 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, to take a jab at accountants.
Guest: Adam Tzagournis:: I'm a CPA as well. So I have only the utmost respect for my fellow accountants. but I do think that eventually they will kind of get folded into this, this more of 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 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. So maybe not too wild of a prediction, but I would say that you know, the more interesting part of this is the timeline on which it's going to happen. I'm thinking more 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 more of, 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 understand that eventually, yes, the accounting and finance roles as we know them today are going to look very different in the next few years.
Host: Paul Barnhurst:: 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 you joining us with us Adam, and sharing some of your wisdom. We'll put your contact information in the show notes so people can get a hold of you. We know you're on LinkedIn so people can reach out to you there. 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.
Guest: Adam Tzagournis:: Absolutely. Thanks, Paul and Glenn. Really appreciate it.
Host: Glenn Hopper: All Thanks, Adam.
Host: Paul Barnhurst:: Thanks. Thanks for listening to the Future Finance show and thanks to our sponsor QFlow.ai. If you enjoyed this episode, please leave a rating and review on your podcast platform of choice, and may your robot overlords be with you.
