An Evaluation of the FPI AI Program and How 3 Finance Pros Are Using AI Today

AI has probably been the biggest technical evolution in my lifetime. Don't fear AI. Human civilization is full of examples of new inventions and new events coming and humans have survived it. For some problems, we really don't need AI right now. So AI is not a solution to each and every problem. This is not going to replace me and it is only going to help me to manage my work effectively. Today, we're joined by three distinguished finance experts, Nitesh Muki. Finance director at G42, who spent over two decades navigating global finance at giants like FedEx, Schlumberger, and KPMG audit, Rohit Menon, a regional finance manager at Biolitek, who brings nearly two decades of global finance mastery with extensive experience across healthcare, medical technology, and multinational business environments, and Sweatajalani, a chartered accountant and FPNA manager who transitioned from audit to financial planning. AI can definitely help you in crunching data, but the assumptions and the discussions and the human element, that is something which AI can't do. That's the better the input, better the output. So you keep improvising, first of all, as a user, don't just stick to one AI tool because this is the right time when most people are at the stage of learning AI. This is an opportunity which will not come in a few years down the lane. What do you believe is the most important skill someone needs to develop to be successful for using AI and finance? Welcome to another episode of FPNA Unlocked, where finance meets strategy. I'm your host Paul Barnhurst, aka the FPNA guy. Each week we bring you conversations and practical advice from thought leaders, industry experts, and practitioners who are reshaping the role of FPNA in today's business world. Together, we'll uncover the strategies and experiences that separate good FPNA professionals from great ones, helping you elevate your career and drive strategic impact. This week, I'm thrilled to welcome the three people on the show. We have with us Natesh. Welcome to the show. Hi, Hi Paul. Excited to have you. Samia. We have Rohit. Welcome to the show Rohit. Thanks once again Paul for having me. Excited to have you and Sweeta. Welcome to the show. Thank you Paul. Thanks for having me. Yep, excited to have you. So today we're going to be talking about AI and some training all three of these people did around AI through the finance professionals institute. But before we get into that, where I want to start, is I'm going to ask each of you to just give a little bit of your background. So tell our audience a little bit about yourself. And in this case, we'll start with Natesh. Then we'll go to Sweeta and we'll finish with you Rohit. So if you could just tell us the audience a little bit about yourself. Hi everyone. My name is Natesh Muki. I am currently working as a finance director with PreSight AI, which is an AI analytics and a big data analytics company in Abu Dhabi. Over the past two decades, I worked with a bonus out of several hats such as an auditor of an financial analyst, a treasurer and an FBN manager, worked across firms like Schlumberger FedEx and KPMG, and I have worked in various jurisdictions and gone through several different kinds of experiences in finance. Thank you. Thanks. Appreciate it. Sweeta, go ahead. Okay. So my name is Sweeta Thalani. I am a chartered accountant based out of India. I started my career in audit at one of the big fours and I actually didn't enjoy it that much. Somehow I stumbled into FBNA and I would say it's one of the best decisions that I've made in my career. I've been working as an FBNA manager at one of the subsidies of Thomas Cook. And it's been two plus years for me to be in FBNA and I do have good opinions about it. So yeah, really excited to be here, Paul. Thank you. Awesome. Love it. I'm glad you found FBNA. I never went the accounting route, but I've heard some people say audit can be a challenge. It's usually a pit stop, not a career for most people. So all right, roll ahead. Go ahead. Yeah, hello, everyone. My name is Rohit Patten. So I've been in Bon and Race in Central India. It's been in almost 15 plus years and the buy and I'm having worked for over 19 years. Had a great opportunity to work with various multinational companies, had the privilege to work in various roles. And then I think it was the year 2023 where it was a turning point for me and then yeah, decided to take up the FBNA course and basically try to move out of myself from the comfort zone and exploring better options because I think that's when everyone needs to be also give it a part that okay, how what skills should I adapt more to grow in finance. So yeah, I mean, that was a journey and yeah, currently working as a regional finance with one of the medical device company called Biolitec, a European Austrian Peace Company. Yeah. Well, thank you. Appreciate that background. So I pretty much start every episode with asking this question. I'm curious to see how different they are. The question I typically ask is what does great FBNA look like or how would you describe it? And I think for this one, we'll start with you, Svida. If you want to give your definition, how do you think of great FBNA? Okay. So for me, great FBNA would be an anchor where business, understanding and numbers work together in a way that decision making becomes easier for the stakeholders. And by that, I don't mean that you have to present your numbers accurately. Of course, you have to, but it goes beyond that. You have to show why the numbers look the way they do what's driving them and present it in a way that one of your stakeholders, they enter the room and they look at your analysis and they are ready to say yes, I can make a decision out of it. So that's how I look at it. That's the kind of version that I want to be. So I got to appreciate that. The cash, I'd love your thoughts on this. What would you kind of add to this? How do you think about it? For me, FBNA is a function where it's forward looking and not only just doing an analysis of the like a rare view mirror, it's basically turning the operational reality of business and sort of explaining it in terms of its numbers and narratives. At the same time, it's decisive, drives value and helps in sort of bringing some benefit to the shareholders and at the same time explains and gives the narrative to the numbers. So for me, that's what FBNA is. It's more forward looking, decisive and strategic in nature. Appreciate it. Ro here, anything you'd like to add, I know it's kind of hard when you go last, but we'll give you an opportunity. Yeah, I think Shrita Anitish have already covered, but I think it definitely goes far beyond budgeting and reporting. And as we see now that the team in multinational, the FBNA team, the impression is changing. So, Shrita already had mentioned that, we know it's not just to submit the reporting or the management back to the senior stakeholders, but also how we can present the data with the diagnostic analysis. Shrita, just showing the root cause, like what thanks up to that. I think this is what now management is looking at it. And yeah, I think I can say that I mean now these days with all these courses, certifications, FBNA team is definitely evolving and able to connect the financial data with the operational insights and have it by business and the surrounding. Yeah. It's definitely grown in importance and we can see with all the training out there that the role continues to change and be elevated. So it's an exciting time to work in FBNA. Right. So, what I want to talk about, and we're going to be talking about this quite a bit today is each of you took, I think, the AI FPNA program from Financial Professionals Institute. And so where I want to start is kind of asking each of you why you joined, like how did how did you make that decision to join the program? So in this case, we'll go ahead and start with you Natasha. If you sell a little bit of kind of how you decided to join that journey to end and end up taking that certificate. So Paul, for me in terms of where I was in my career, I already had spent two decades in finance and have gone through several roles in the past. And if I get FBNA was also one of them. So the basics around budgeting, forecasting, etc. was something which I had already gone and sort of experienced it in a real life scenario. But I wanted to sort of pressure test myself with regards to current trends, especially when I took the program, which was somewhere around mid of 2025 till end of 2025. That's when the program went on till. Artificial intelligence agents, tools, technologies had already started making its inroads as far as the finance function was concerned. And I wanted to sort of even see how the financial planning and analysis concepts and the AI sort of merge. And I found at that point in time the AIFBNA and also the CGFBNA, I think the course goes by both the names, was offering a sort of insight into those elements. And hence sort of caught curious and joined the program. Got it. Now thank you and appreciate that. Sweet, what's your take on this? How did you end up in the program? So I would say why not? Because AI is the hype right now. I mean, with all the fear of mongering and almost every conversation these days is about AI. And somewhere around February, I saw that AIFA-- AIFA-- got added to my CGFPA module. So I had enrolled for that with FPA. And I could not attend the FFA-- February cohort, but I attended the May one. I have been using Chaji Petty for a while now, but I wanted to understand how I could be using it in my work. So I was looking forward to a structured learning course. So that's how I entered this. I could totally understand wanting a structured learning course. And I think you touched on something that we've all built with. There's a lot of fear mongering, a lot of fear of missing out. And tell you educate yourself. You don't understand. Yes, it can help. But what's the right balance? Because you go on social media, and it makes it sound like you should be doing everything with AI. And I'm going to guess if I asked all three of you, there's still a lot of stuff you're not doing with AI. That it's not perfect for all your use cases. So Rohit, what was your journey? How did you end up taking the course? Nothing after completing this certification back in 2024. Of course, we all know chat, but yeah, I think the drawback is you need to have that advanced subscription. So this AI FPNA, I think, it got me interested with the course structure, I would say, where I myself wanted to try how I can apply AI with real business cases. And of course, when you are in that group community, there's always an opportunity to know what's going on in other business, how those industries are applying AI, or is it embraced, or is there a-- they feel stuck. So I think this was one of the things. And also, I think when you reach to an intermediate level, and then when you have a team, you definitely wanted to not just only setting up the KPIs, but also want to make sure they have the most advanced tools where you can train them, and to keep on encouraging that how this can make you more efficient free up your time. So I think, yeah, these were the factors that I wanted to end goalful. No, I appreciate that. And I think you mentioned in there also having team. So my job is we're-- we have employees. There's two sides at one. You want to lead out and be an example. And two, you don't want them to get way ahead, and you're trying to understand what they're doing because I think AI has probably been the biggest technical evolution in my lifetime, I would say. Yeah, you can make the argument. Maybe the computer. I am that old. I remember my first computer when we got it when I was, and I think through your high, or the internet. But definitely, AI is one of those watershed moments, especially as it got better and better. Is also-- and you're like, wow, it's actually giving good answers versus the very first when it came out. And there's a lot of making fun. I mean, it had good value, but there is still definitely a lot more hallucinating. So next, I'd like to just kind of get a little bit of an overview of how the program worked. So maybe you could just talk a little bit of what's kind of the format? How is the program set up for that AIFPA? It was shorter, I would say, maybe eight hours. So probably we're talking about a month, if it's a weekend class. So it includes, of course, ChatGPT, which I had used it by then. But then I was looking forward to Claude, an agent AI, and co-pilot. So I think-- Yeah, so two hours per topic. And then, yeah, this was the whole format. OK, anything either-- anything you'd like to add to that, to the format? Yeah, so I think Paul also would take that. I believe it depends on when-- I think Rohit took the course a bit earlier. So I think myself and Shweta probably came a bit later. And at that point in time, artificial intelligence had evolved. The people were conducting the course, such as Daval and Asif. I think in addition to the normal programs, they also had certain special classes for weekends, where they have sort of taken us through ChatGPT, Claude. In fact, Daval took us through Monas. It's one of the other platforms where you can agents. And even co-pilot, I think there was separate sessions done where you had certain people who are experienced with co-pilot to sort of give us used life cases of how things are worked up. Because the most important thing is, yes, we all know LLNs. It's a no-code kind of an environment. But to see actual use cases, people who have done it, to take you go live. So I found that particular aspect quite prevalent in the course. And it was not only in the course, in between the courses, as well they kept certain special classes, et cetera, as such. So that was quite interesting. And I think you make a great point. And I was talking to Asif. He was mentioning-- I was asking about one of his courses. And he'd given me some recordings of one. He goes, well, you can always join the August one. It keeps changing the law. Everybody's constantly changing what they're teaching, trying to keep up with AI. And I think that's a real struggle for people. And there's a balance. It's like, do I need to know every new thing? You can catch yourself kind of chasing what I like to call the shiny toy syndrome, where every new model-- you've got to figure out exactly what it can do versus what was it doing my work well. Why don't we just focus on that right now, and I'll figure it out when I have time. So I'm sure it's with the courses. We're all struggling to figure out what the right balance is here. Anything you'd like to add about the programs, what it-- what I like majorly was that they covered good case studies, which are actually applicable for my work, because otherwise, I would be too reluctant to try it by myself. So they covered variance analysis, management reporting, and then there was data cleansing that they performed using really messy data. So they literally showed us how to use a tool for a certain case study that you may be performing tomorrow at work. So that's how good it is in terms of giving you the push to start using AI. Yeah. Seeing actual use cases is always really, really helpful. I'd like to get some thoughts of who would you say the program is for? Is it for someone who hasn't used AI much? Someone very experienced. We'll start with you, Natasha. If I asked you, who do you think the program is for, what would you say? So I think it's a mix of people. I think it covers all levels, because it's starts with a very basic coverage of what FPN is. And then it goes through basic modeling, basic variance analysis, basic management reporting, right up to use of AI. The various other tools like Power BI. And then it also talks about data presentation, data to storytelling, business partnering. So it's an advanced management reporting. So I would say it sort of covers from people who are young financial analysts, FPN professionals, finance managers. And then also people who have come from accounting and auditing backgrounds who want a glimpse of what FPN is on the mouth. It sort of also gives a good insight into that. And then it takes off. And it also provides concept clearances around for CFOs and finance leaders. I'm a director of finance. So I came predominantly to see the new trends and the artificial intelligence related concepts. How I could leverage AI in my work as such, because as rightly mentioned by all of you, it's not about just knowing what the LLIM models are all about. You have to see actual use case. And also they were data enthusiasts and tech savvy finance professionals. So I think it sort of covers a broad spectrum of people. And I understand what you're saying when you say need to see the AI use cases, I'm involved in, I just wrapped up a course through Clawed itself. And I'm taking two other courses right now to try to get more up to speed on AI. So I can totally understand that one. So Philip DeNoe from your guys' perspective, what was the most valuable thing you gained from the program? What do you think it was most helpful with? And Rohit, we'll start with you first on this one. Because we could see that how finance is evolving and disagree with Neatysh, the previous comment that, it should definitely be for growing finance professionals and understanding how this can maybe take them to the leaves, we know, depend upon whether it's a lean company structure or we know, we're working in a big large multi-national. So for me, I think what was the valuable thing that the, you know, I was more of a concept plus system oriented. So when I had the opportunity, it definitely gave me a better understanding, better mindset than okay. This is not gonna replace me, yeah. And it is only going to help me to manage my work effectively. And then I can focus more on the business related, be a better strategic partner, business partner. So I mean, I would say that was my key takeaway, yeah. - You make a great point about the, it's not going to replace you. Because I always say yes, We'll start. Some people lose their job with AI, of course they will. I'd be naive if I said nobody's going to lose their job. Industries, companies will change quite a bit. Roles will change, but AI will augment and help us. Like I always say, once we hit AGI, if we ever hit that, all bets are off. But until then, it's about continuing to kind of improve yourself and recognizing how can I be better with the tools. Like so many people like AGI's going to replace everybody, spreadsheet ended up leading to more jobs, not less, computer led to more jobs, internet led to more jobs. The early studies I saw were saying they expect overall AI to create more jobs. But will it be disruptive? Of course. So I think you make a great point because I see people like, well, I'm going to lose my job tomorrow. You could lose your job or all the jobs going away. No. You need to make sure you're preparing yourself for what the future looks like is kind of what I tell people. So love to get your thoughts on this one. What was most valuable for you from the program? What was kind of the key takeaways for you? For me, I think the most valuable skill that I developed after doing this program was to prompt well because otherwise it used to be a way to ask. And this course actually taught me how to make my prompt, keeping in mind what my context is and what, how do I want the format to look like and basically designing it in a way that I get a good output. And it is totally dependent upon my question. So that's a skill that I've developed really well post doing this course. And there are more things, but yes, prompting well was one of the greatest skills. Thank you for sharing that. Natasha. So I think as mentioned by Rohit and Ashweta, I think artificial intelligence, real world applications. And I sort of concur with you as well that artificial intelligence or LLM models is just an enabler with regards, but you still need domain expertise. It can't be that you do not have domain expertise and you just start doing AI and you will learn everything. No, I don't think it's going to work that way. It's an enabler. It's going to enhance your work. And I think it's going to help you in your day to day work. And what I learned in addition to probably the AI and the technology aspects, I would say is I like even a subject like strategy, sort of the way they went about explaining strategy frameworks with case studies, because you sort of seldom you learn about all the concepts like port or five forces best, and PCG matrices, but to see it in use cases, it was interesting. And even the segmentation, the business segmentation, the way they went about doing product pianos, etc. So it was quite interesting to see those aspects because both Asif and Dau will come from finance backgrounds and they sort of brought their expertise to the particular course. So I think that those were the good aspects which I learned about courses. There's something you said that has been kind of an axiom grinding, a point I've been making again and again. AI is a magnifier. If you know what you're doing, it will magnify that. If you don't, it will magnify that. It's just a question of when. And so I'm going to throw out a question with love to kind of get your thoughts. Anyone who has spent a lot of time on LinkedIn sees all kinds of promises with AI. I see everybody smiling. And you know, one of my scene is, hey, AI can build your financial model in five minutes. Right? Just tell what you want and walk away. So I'm going to give you guys an opportunity to just give your thoughts on that because that's one that drives me crazy. So now having used AI and kind of how you think about that. So we'll start. RoHit. We'll start with you on this one. FPNA guy here. I want to take a minute and share something I've been working on. I've spent several months adding new affiliate programs to my website. I'm wondering why affiliate programs? Well, I can't train you on everything, but I can show you and give you trusted resources with exclusive FPNA guy discounts in many cases on my website. I have several of the top FPNA AI people in the world. I have the top certificate programs. I also have other programs like Excel, Power BI. I'm bringing you some of the top people that train in the world. There's Nicholas Boucher with exclusive discounts, David 14, Matt and Carl Siedman with exclusive discount, the top programs, FPAC, FMI and more. So go ahead and check it out on my website. Sign up. And if you have a question on what program is right for you, go ahead and message me. I'll get back to you. LinkedIn or you can email me. So go to the FPNA guy.com and check out my trusted list of resources for you to upskill yourself. Yeah, I do. I mean, spend a decent amount of time on LinkedIn. I do see various surveys. I've been up post. I think probably before I answer that, I'd like to add a small survey which I end up taking up and commented like, you know, there was a survey that, okay, when you prompt and then by the time AI is giving you the output. So what do you do? You just crawl or you just go and get up and take a coffee or you actually, you know, prepare for the second prompt. What should be the one? So how I would say and only an expert can say that, okay, a financial model can be prepared in five minutes. But of course, somebody who has just started to use or believe in AI, I would say need to spend more time. I mean, in the various type of use cases or prompts, so unless as, and also, you know, adding to what they had mentioned that, you know, you need to be an expert in, you know, understanding whether this prompt is helping you or you need to change further. So yeah, it's a mix, I think, yeah, experts can always say it can give you a little five minutes, two minutes, but then yeah, one need to practice it for sure. So what are any thoughts, anything on add to that? I think when I look at such post, I've worked the first question that pops up in my head is are your organizations really applying these tools because in my organization, it is still not happening and we're still trying to figure out the real bottlenecks for which we want to use AI literally because there are too many problems and for some problems, we really don't need AI right now. We need to do some analysis as to really if it is beneficial or not. So AI is not a solution to each and every problem, but I think it's going to take a lot of experimentation, enterprise wide to figure out where we would be using AI solution and where you would be, you know, continuing as we are already doing. Great point. I love that you brought that up of look, AI isn't the solution for everything. I was doing a webinar on Excel and someone asked, well, can I just do this monthly process study? I do every month with AI and I said, why? It's an easy solution with power query. You know one plus one always equals two. You're not going to get any variability. Why wouldn't you just build it as a proper automated process versus sending it to AI? Not to say AI can't help, but so often like, well, shouldn't I just use AI for that? I don't care what technology you use. And really your boss doesn't at the end of the day. Yes, everybody wants to show AI returns, but you make such a great point. It's about the right tool for the right job and we're all trying to figure that out. And it's going to vary depending on how clean your data is and how structured your processes are. It's not a simple and every situation you use AI for this. It's going to vary. So go to you and attach your thoughts on this. So I think yeah, I sort of concur with all of you. And apparently when co-work came in from Claude and co-pilot, I think the impression was that it'll come into your computers and it'll start reading the files and they'll be able to sort of solve everything. But I think one very important element which we all forget is there is a human element in all our roles, right, especially the FP and a role. You have a concept of business partnering where you are engaging with operation teams, you're engaging with the human resource teams and because your budgets and your focus are like a living organism, right, because it's sort of assumptions are changing on a regular basis. So yes, AI can definitely help you in crunching data. It can't make you a model in five minutes, etc. It can make you a basic sort of a framework model. But the assumptions and the discussions and the human element, that is something which AI can't do. That a human being has to do. Thank you. I think you summarized that well of saying you have to have human judgment. Even if it builds you a model in five minutes, it doesn't mean you're done. Great, great point. So as you guys went through the program, where do you think is an opportunity to maybe improve the program or something that you would have liked to maybe be a little different? Any thoughts around that? I know it sounds like all of you really enjoyed the experience, but I always like to ask that question because I think we all know we can improve and it helps people to go in with their eyes wide open if they decide to do the program. So we'll start with you, Aswita, on this one. So there was one session where they taught us building your own GPs. And for that, I think somebody, I mean, the audience kind of needs to have a basic understanding of Python and I came from a background where I had no understanding of Python. So although I took that session, but I am not sure if I can do it. but I was half nodding and rest of the session, I could not figure that out. Maybe if I go back and do it again, I'll be able to understand it better. But yes, that was one session where, because I'm not a techie, so I could not understand it so nicely. - That can be a challenge, especially when you have a big audience is sometimes not everybody's at the same level. So a great point there, appreciate that. Good feedback for them. - Natasha, we'll go to you next. So I sort of concur with, I think it was, I think few sessions were there on learning the technical codes, which was Python and the SQL language, which I understand, I think it's a critical part. But you know something, when I have to build something in terms of an agent or a some kind of a program, I actually go to the LLIM and sort of make the Python code, I ask them for the Python code and sort of make the agent myself. So technically, I was off the opinion that maybe I'm not the right person to learn that coding. So nothing with the program is just that maybe, that's something which I don't intend to do the coding aspect of it. So I think that is something which I found a bit slow in the course as such. - Okay, good feedback. I think it had covered everything. But as I said, or maybe I'd like to say is that these, you need to have like advanced subscription to explore more. So I think and the use cases, yeah, whether it is relevant to you or not. So I feel that I mean, now, if there will be an expert, I mean, they have a lot of use cases as Mataish also mentioned. So you need to, I think your takeaways, it's on you like, okay, whether out of these four modules and also as Shweta mentioned that, okay, in the organization that she's currently working, I doesn't really have those kind of subscriptions or doesn't even encourage. So you need to see that, okay, whether it is Jansi PT or co-pilot, I mean, which is now currently, I'm using it, Claude for sure, it's being used at the group level. So I do know that, okay, I would come across certain use cases, which, you know, I can, you know, capitalize it. So one needs to also know that, okay, what are your organization capabilities? Because of course, nobody would say, put the data out there in the, you know, unsecured AI. And then yeah, you're compromising your company's data. So that is something one needs to be mindful of. Otherwise, I think overall, the content, everything was good, yeah. - Yeah, I mean, being careful today is always an important one that we have to understand. I'm curious to know, what's the, your favorite thing you've built or maybe automated, you've done with AI so far, you know, you could share in work or you could even share personal if you want. Those are always interesting to hear. As I know, we also use it in our own life. So we'll go ahead and start with Rohit. We'll let you go first on this. FPate guy here, we'll get back to the show in a minute. This section is on scripted. When I started my business, I had two main goals. To be trusted and for my content to come across as authentic and helpful. I've heard from many of you that I've accomplished those. Today, I have three goals. To be trusted, authentic, and have the best beard and finance. All right, enough with the jokes, enough with the fun. What I'm asking for is I'm asking for you to help me out. If you've enjoyed the show, if you've enjoyed an interview, if you found it helpful in your career, can you please leave a rating and review? That helps more people find the show, helps me grow the show, helps me grow my business. So I'd really appreciate it if you could take a moment and leave me a review. You can do it on Apple, Spotify, YouTube, wherever you listen. Or you can go to my website, the FPNAguy.com. That's fp-a-n-d-a-guy.com. Go ahead and go to Wall-O-Love, go down to the bottom. And you can click to leave a testimonial. Thanks for doing that. Thanks for listening. Sure. I think, yeah, as I said, the curiosity of, you know, before joining the course, how I'm going to apply this into real business. So yes, I think I've done recently, you know, analysis on the healthcare, you know, financials. So, you know, implemented to see if, you know, how I can do the profitability analysis better. Build the process documentation, I would say, through co-pilot. And also drafting a policy, you know, locally. So I think these were the few implementations, which have recently done it. And yeah, it was, I think, quite a save lot of time, because if you know the content that you're looking for, if you have the knowledge of, you know, certain concepts, I think, yeah, you save a lot of time. And yeah, it was accepted as well. It's been reviewed and signed off, yeah. So these were the creating implementations. Always nice when you save time. Nobody complains about that. How about you, Natesh? So, as I said earlier, for me, AI currently in terms of the LLM models, because I use co-pilot co-work in my work environment as well. It sort of does a lot of heavy duty financial crunching. So, one of the sort of projects, which I sort of work on, because I have to work with growth team, quite in terms of on a regular basis. So a lot of data crunching in terms of the data, which we get in terms of targets for the financial analysis and to figure out whether the return on equity is a creative or not. So there is some agent, which I have developed, which sort of does that. In addition to that, it does a basic check of going through the net and sort of working out the cross-border taxation rules and the foreign direct investment rules, et cetera. So at least you have a basic profiling ready before you sort of look at the deal. So I think that's something which I'm quite proud of in terms of what I have done. Thank you. Appreciate that. And we'll go there, sweeter. How about you? I've been using Clod personally a lot for my LinkedIn post, where I create infographs and any carousels. And that's been very helpful for me. Other than that at work, because I was recently involved with the business transformation project, and I was supposed to give a business requirement document to a software developer. And I did not have access to Clod at work, but they had. So I used their Clod and gave my requirement and got a business requirement document in a couple of minutes. And I think I really got very surprised, because anybody who has done it, they know that those documents are really dense and difficult to draft. So I was really happy about it. And yeah, I mean, it was surprising for me. I think it is. It can be really surprising, especially when you mentioned Clod. To me, it felt like there's kind of a watershed moment about six months ago, especially on the modeling side when I see all of you nodding, right? When Opus kind of 4.6, now we have Opus 48 came out. It felt like the tool made a big jump in a lot of areas for the work we do. And not to say it was bad before, but I think people who may be tested it early on are like, "Yeah, it doesn't work well." It's like, "Okay, you always have to be testing. It's getting better and better." And I know what you mean by dense documents. I've given it some things and comes back and it's like, "Okay, I probably would have spent a couple hours doing that." Now I got to spend 20 minutes reviewing it versus three hours writing it. Huge fan of when it does stuff like that. So I want to ask each of you, if someone's watching this episode and they're kind of thinking about joining this program, what advice would you offer them? And we'll start with you sweat on this one and then we'll go to Rohit and then we'll let Natasha go last. So we'll just go in that order. So my advice would be that you should do it not because AI is going to change your life, but because this course will give you that structured learning stage, you will develop that urge to try AI in one of the other tasks at work or even personally. Otherwise, you will keep saving grills and hacks and you will never really go back in those folders to see what works, what does not. And if you do this course for four weeks, it's just what, eight hours? You give those eight hours and then you have that tendency to use AI. So the willingness to experiment, I think you should do it. - Thank you. - Appreciate that. - Rohit. - Whether a basic or advanced level user on AI or you wanted to know more, I think, yeah, this probably changes your mindset. And then, yeah, as we all know that, it's going to be technical expertise, world where each and every role requires certain amount of technical expertise. So we need to go with that flow. And AI definitely, I think, leaves one message, which is like the human judgment, there's always good to have some kind of system capabilities which can give you better results or at least impression that, okay, it always helps to create something new. And something which will also push you out of your comfort zone because you would, during the process, you would come up with your own, you know, but real cases, business scenarios, things like that. So yeah. - Thank you. - Nitesh. - So I think, yeah, you should do the course because I think it is first of all an organized sort of structure which is in place, which they are giving the course. And in addition to that, the AI part, yes, I think, as spoken by Rohit, that's what that. but also 12 upon the experience of the people giving the course because they all are from, they have the domain expertise and their work and finance for so long. So I think that is something which is, which you don't get with LinkedIn Reels and or the other web related videos as such. It's sort of a context setup and a use case which is very important for you to understand the concept. Thank you. Appreciate that. Now I want to ask each of you, what are you most excited about as we go forward kind of future of technology and AI? Well, it has you most excited or if you want, I'll even flip it around. Where are you most concerned about? I'll give you the opportunity to take it either way because I think we obviously feel a little bit of both sometimes and we'll go ahead and go Rohit, Sweatit and we'll finish with Natasha on that one. So go ahead Rohit. Probably I would say that it's going to be more of a access being given to experts who can really change the process and it's going to, I think for sure during the process you're going to feel that it's going to free up a lot of time and then you can use that time on businesses, developing those relationships with the stakeholders, other departments and add more value to the business I would say to reach to a sustainable growth. This is what I think the senior leadership they always look for. So I think the future is going to be like that. So I think I would encourage that especially people at intermediate level to senior level. So yeah, this is definitely for that. All right. Thank you for that, Sweatit. We'll go to you next. I am excited about how my role is going to evolve and using technology, how much time I'll be able to save because there are a lot of redundant tasks that even I want to avoid and use on something which is interesting. And also I am more excited about these enterprise level implementation for AI tools, what kind of bottlenecks we are going to solve and firstly figuring it out. The entire process of speaking to stakeholders, trying to figure out what AI tool we should implement and then doing trials and errors. So that's what I'm pretty excited about because I've worked in smaller setups and I know how many issues they have. So I love something you brought up the excitement of the enterprise. I think that's an area where a lot of people are struggling. AI is kind of being implemented a lot one off. You know, a lot of companies, not all. Some companies have done a really good job. But I think the true benefit becomes when it's an intelligent layer which requires an enterprise solution because you got to make sure it can take in all your data and really help everybody be smarter. So I really appreciate that. I think that's one of things that's most exciting is we really start to figure out how do we leverage this across the entire company with all our data. But I'll go ahead and let you share your thoughts in the test. It's quite exciting. The way I see it all is sort of freeing you up with a lot of data assembly, data crunching and especially if you are able to sort of implement as at an enterprise level then it sort of also does a lot of a basic level correlation of data etc. And it frees up your time to think in much bigger and larger areas and sort of become having a more sort of a support in terms of your decisions. So I think it's got to sort of free up you and sort of take up most strategic kind of decisions in terms of what you are actually currently doing. Great. Thank you. Appreciate that. All right. So we're going to move into what I call kind of we have two standard sections. I have a brief FPNA section and then a little bit of a get to know you. The goal here is keeping the answers relatively short 30 to 45 seconds, especially given we have three people to answer each of them. And I'm going to ask three questions. Two of these are ones I ask on every episode and then the third one is one I kind of adjust a little bit for this episode. So I'm I'd love to hear each of your answers. It's amazing how many different answers we get for this question. So we're going to start with unit tests. What is the number one technical skill that FPNA professionals need to master? Financial modeling is something budgets forecast. This is something quite critical, right? They have to do that. Okay. So financial modeling, Rohit, what would you say? Yeah, I think probably I would agree with them. They should if you cannot, you know, interpret the financial data into a reporting. So I think yeah, this is one of the key feature. Yeah, it's technical skill. Yeah. That's so fun. You're going to go with the same answer. I'm kidding. I get that sometimes. I think the last episode I had three different answers from the people. It was really interesting. So we definitely get the same sometimes. I'm kidding you. That's a very common one. But I swatted. We'll go over to you. What's your thoughts? I sort of agree with them, but just because you wanted a different answer, I would say. But business and financial acumen, I think that's very important. If you have one and not the other, it's not going to work. So you need both. Yeah, you definitely need both, right? I mean, even though I ask what the number one is, there's not just one skill you have to have. It's more just kind of curious to see people, how people will answer it. So now we're going to ask you, what's the number one soft skill? Kind of human skill that you believe FPNA professionals need to master. That's what I will go ahead and go with you first. And that way you won't, you know, have to feel like you're at the end in coming up with something different. Sure. I would say storytelling and also ability to build relationships with your stakeholders. So that's something that this is an asset that compounds or what I mean. Okay, storytelling ability to build relationships, both very important. Nitesh. Sort of concur, business partnering, communication storytelling, and I think there are two more aspects I would say is the empathy to understand the other person's view and also very critical is to sort of have the mental ability, you know, to sort of, sort of achieve what the goal is. So I think these are the human elements I would say for you know, I'm going to say you brought up one of my favorite answers and that's empathy. I am a huge, huge believer that the more we can have that in FPNA, the better a business partner we can be. So now that I have biased it, we'll let Rohit go. I'm just kidding. Communication skill. So if you're not able to explain the best analysis and you're able to interpret and clearly explain it to the stakeholders. So yeah, then I think you're not winning. Yeah. I've worked with people and I've had times where I did not do a good job of communicating. I can tend to be very detailed. I've had times where I boss is like, you've lost me. Stop. Let's go back. Walk me through it. And so it's a skill. Truly learning how to communicate, be a good listener. It takes practice. So I really appreciate you bringing that one up. All right. So this one I want to ask, obviously, given we've been talking quite a bit about AI, what do you believe is the most important skill someone needs to develop to be successful for using AI and finance? So we'll go ahead and go Natasha, and we'll finish with you on this one, Rohit. So go ahead, Natasha. So I'll still say that you need the domain expertise because I as I mentioned earlier as well, AI amplifies. I agree. Right prompting, etc. That's important, but I still feel you need to have domain expertise so that you can sort of ask the right questions. So understanding what you're doing versus giving that to AI. Love it. Go ahead. I absolutely agree with them because if you don't know what to ask and where to reach, you cannot prompt it well. And also you need to have some patients to verify, at least right now, you cannot just give it a prompt, get an output and send it across. You need to have the patients to verify and maybe give it back and then get an answer. So that's a loop that you have to solve for some time. 100%. I would say anything I give it that's complex. I've been using it to help build a lot of websites is I ask it three times to review, oh come back and say here's all the changes to make. I have make review again, review again. And every time it comes back with a couple more. And so I try to have itself check itself as well as reviewing it myself because we all know that it's not going to be perfect just because it can save us time doesn't mean we should trust it. Go ahead. I think the better the input, better the output. So you keep improvising first of all as a user. And yeah, don't just stick to one AI tool because sometimes yeah, Reese, I mean, past few months I realized that okay chat ZBD wasn't giving me that kind of great response. And I switched to co-pilot, co-pilot was, you know, giving me all the I think the advantage also in your company if you have co-pilot, it kind of integrate with your emails, works or it gives you the all the most updated, you know, information. So yeah, just improve, keep improvising the input so you get at the you get the better output. I agree with you, you know, at the moment there's definitely differences you're going to get from each model and their time when it may make sense to use something else. You may not have that opportunity and work, but if you do it's a good one. You know, myself, I have accounts to clawed, paid accounts clawed, chat cheaply tea and co-pilot. And I switch between them certain tasks. I'll ask all three. When I'm trying to decide what I want to use and I'll narrow it down and I'll ask them in a kind of like a bake off. They keep going back and forth with me, you know, kind of being in control. Most people don't get that ability at work to be able to switch back and forth between three of them, But there's times I'll even pull in a fourth and just kind of until I'm comfortable that I like Yeah, that I've got I've maximized whatever I'm trying to accomplish. Usually that's more marketing stuff and how I'm going to word something versus math problems. Not your finance typical finance stuff, but all right, we're going to move into the get to know you section. So again, we're looking for, you know, relatively short answers here. Have three questions. Just kind of fun to get to get to know each of you a little bit better. So the first one, if you could have any superpower and we'll start with Natasha on this, what would it be? What would be the superpower you are? Well, I can forecast everything without anything so that once I have the superpower, that's it. I'm done. I have to do it. So I'm taking you to Vegas if you have that superpower. Yeah, I'm going to go make a lot of money. Or the stock market. Yeah, either one. Stock market usually takes a little bit of time. Vegas, we can get it all on one night. So how about you? I think I would want to be invisible and want to know what my stakeholders really thought about analysis after I moved out of the room. So I want to be invisible when they're discussing once I'm out. So invisible. All right. So yeah, superpowers and forecasting, invisibility. Let's see what our hits superpower is going to be. I think of course, it's pretty much relates reading the senior stakeholders mind because it's like sometimes you just prepare a presentation and then yeah, you just come out of the room and then yeah, you see in the next five minutes, you have a new email or maybe a better breakdown of what you have already presented. So reading that I think mind, which we all know, I think over a period of time that okay, this might be the possible expectation, but the as sometimes it gets difficult. I think these days they are also giving us solutions that you could have done this via AI. Look, I have done this. So that's really frustrating, but it's happening. One thing I found interesting is I think all three of you tied your superpowers to work. I'm not sure I would have tied my superpower to work. So I like it. It shows how dedicated you are. I probably would have went with something totally unrelated to work. I don't know, being super strong or something like that. Okay. So next one, if you could recommend a book, maybe a favorite book you like to read or something you think the audience would enjoy, what would you recommend and Rohit will let you go first. A book by Morgan Hughes, it's about the explaining the, you know, about the money part, which is it's not important that you have the money, but how you behave and it teaches you certain strategy, you know, being basically a difference between Rich and wealthy. So I think I would recommend that. The one on money, what was the name of the book again? I think it's by Richard Morgan, the psychology of money. Yeah. Okay. I've heard of that. Psychology of money Richard Morgan, great. Natasha. I have two books. Both are from PE investors because I like to understand the concept of investors. The most important thing by Harvard Marx and common stocks and uncommon profits because they tell you aspects which you should look at it when you are sort of evaluating your business. Great. Sweet about you. What's your book? So there are a couple of books that I would recommend. There's one on strategy by Harvard Business Review. I've not completed it, but it does cover a good number of case studies. So that's one. And then there is a breaking the habit of being yourself, which is also a nice read if you want to change yourself. So yeah, those are my two recommendations. Sorry, Paul. If I may add one more book because I think this is something really, you know, this was in with my last organization, the CFO actually gifted me this book, the cultural map. So when you work in a MNC, you know, you work with various nationalities. So how you, you know, as a leader, how you interpret their personalities, don't being judgmental in the very nation's days. So, you know, things take time to open up and each, you know, culture or nationality has its own way of expressing. So I think, yeah, that is one of the book, which I think it's a must read for everybody. Yeah. Thank you. All right. So next one is if you could have dinner with one person alive in the world today, who you're going to take to dinner? Natasha. We were in buffet because sort of really admire the person, you know, as to how he has gone about running a successful organization and he's been a successful investor. So definitely more in buffet. Is he retired now or is it the end of this year? I think he's retired. He's sort of not in active kind of. That's what I thought. I thought he had retired now, which is, I mean, he's like 90. So you got to eventually retire, right? So, so effectively, I can ask him if he's interested for dinner. Yeah, exactly. Well, let me know how that goes. And if you can get a plus one, let me know. I'll come with you. Yeah, sure. Rohit, who are you taking to dinner? I think Satya Nadila, I think because it lines with AI, the person who, you know, brought the AI and then what he did with the, you know, Microsoft. So yeah, I think probably had to understand more from the, you know, senior leader for in top of your field. Yeah, he'd be a great one to pick his brain. So appreciate that. And how about you, Swede? Who are you taking to dinner? I think all I would like to have to know with you because you are a treasure trove of all good and, you know, it's fp any content. So I would like to go on a dinner with you. All right. Well, I'm going to make that my new commercial now. I think you're the first one that said they were taking me to dinner. So there we go. All right. Well, thank you, each of you for joining me. It was great getting to know each of you a little bit, chat with you. I think this will be great for our audience. And before we wrap up, I'll just let each go around and any last thoughts, anything you want to leave the audience with. And we'll go, we'll go with you, Swede, first, we'll go with throw hit and we'll give Natasha last word here. So we'll go in that order. So I would say that, first of all, if you are in fp any, this is the right time when most people are at the stage of learning AI. This is an opportunity which will not come to many in the, in a few years down the line. It's a place where everybody is trying to learn and you can have leverage if you learn quicker, faster and sooner. So I think do that, start learning in whatever ways you can. Just try experimenting. Great advice. All right. Throw hit. I think it's it's most of the professions, no finance professions that taking up a certification is, you know, very key in this range of the career. And fpn is one of the famous, you know, name and one should definitely take up this course, not only to learn more conceptual learning, but also brings additional or add-ons in terms of how AI can build capabilities within the fpn function. So definitely look out for this course and yeah, you're going to just feel happy about it after completing the course. Yeah. Thank you. Natasha, any last thoughts? Why thoughts are don't fear AI. It's just a new way of doing things. The domain expertise still counts. The fundamental way of doing things still counts. Invest in yourself because learning compounds and that is what will keep you instead for the future and sort of do the certification. I think that will add a lot of value to you. So I love that. Continue learning, learning compounds. Well, thank you all three of you for joining me. I appreciate it. I appreciate you carving out some time on a weekend is a recording this on a Saturday, so I really appreciate it. So thank you so much for joining me. Thank you very much Paul. It was a pleasure. All right, three meet you all. That's it for today's episode of fpn a unlock. If you enjoy fpn a unlocked, please take a moment to leave a five star rating and review. It's the best way to support the fpn a guy and help more fpn a professionals discover the show. Remember, you can earn CPE credit for this episode by visiting earmark CPE dot com downloading the app and completing the quiz. If you need continuing education credits for the F PAC certification, complete the quiz and reach out to me directly. I'm Paul Barnhurst, the fpn a guy. And I'll see you next time.