Why finance must embrace change with Nikki Mamdeova

Speaker A: The role of finance need to change. I speak at a lot of CFO conferences and it's always come up how could part, uh, the perception of finance could be changed from being a gatekeeper, someone who says no, to someone who says yes. In being treated as a business partner, it is a problem where your uh, business partners only see you as a number crunching function, as someone who we only could come when we need approval. What we need to have is uh, was, um, business partners to have finance at the table when we're already thinking about something. Right. So that's why we need to start, um, change perception from being uh, backwards and conservative function to someone who is open to innovation, someone who deserves that set at the table.

Speaker B: Today I'm joined on $0.02 by Nikki Moedova. She is senior finance executive at RBC. First, uh, of all, Nikki, it's great to have you here. We're delighted to have you.

Speaker A: Thank you for having me.

Speaker B: Yeah, definitely. I'm sure our audience are really going to benefit from your expertise here. Before we get started, um, do you want to just talk a little bit about your kind of journey to your current position and kind of what inspired you along this path?

Speaker A: Sure. Um, like I mentioned, I'm a senior finance executive, been in accounting and finance profession for over 20 years. Um, I'm lucky enough because I started my career in Big Four and I've worked for several Fortune 500 companies and other recognizable brands. Amazon, Deutsche Bank, PwC, Deloitte, Saks, you name it, across different industries. I also worked in uh, New York, London, Tatona, Hong Kong and Bermuda. Um, very lucky in that perspective.

Speaker B: Yeah. So your experience is really far reaching, uh, which is really, really exciting to hear. Uh, and that's why we're really excited to have you here today to talk about this. I guess latest, probably the most crucial technological shift we've seen since probably the Internet. Uh, I would say with AI really this is the big thing, isn't it? It's going to kind of change everything. And um, I'm really e to hear like from your perspective as a finance leader, like what is it about AI that excites you the most and its potential to impact your work?

Speaker A: I'm really excited about AI. The most thing I'm excited about is how it allows finance to evolve because finance traditionally is always viewed as the back office, very transactional and AI is really allowing it to move it to become a strategic business business partner who drives the business decision. It's not just about automation of finance. It's really making uh, better um, decision making quick decisions. And I'll give you some example how we implement in finance already for example in a P and a financial, uh, planning and analysis. Uh, in the past we have been doing static monthly forecast. Now we're moving to real time uh, rolling dynamic forecast which is using the operational drivers, external signals as well as historical data and allows us to create um, a similar different business scenario. AI is also changing a lot. The uh, CFO vault as well as the reporting to the board. You can't imagine how many manual efforts we had in Binance putting this information together for the world. And it mostly was focused on historical performance. So now AI allows us to create dashboards, even suggest some narrative and as a result the conversation is shifting from what happened to what's next.

Speaker B: Yeah, that's really, really exciting and I love how you mentioned um, you know, uh, how it's making us a strategic partner. Um, I think that's a big part of it. Is I being a strategic partner, uh, like you were saying is it's not just talking about what the situation is here but like how, what the future is going to look like. I think that's what you're talking about, isn't it? Like, and that's how you can sort of not just talk about the data as it is now, but what it's going to mean for us in the future, where we're going to end up. And that's really, really great. Definitely. Really uh, exciting stuff. So compared to kind of then what I want to hit on today is kind of like, I guess we've heard whispers about there being sort of obstacles slightly in terms of like uh, AI adoption in finance as opposed to like where there is maybe in kind of marketing or other areas of an organization. Is there any truth to this Nikki? And if so, can you elaborate on it a little bit?

Speaker A: Sure. We are definitely cautious in finance more than our function and what you need to understand, we are responsible for numbers. So with the difference between using AI and generating email for marketing versus using AI for SEC reporting, the 10K, 20F, whatever's going to the market. Right. So with more risk involved and that makes uh, us cautious. You also need to understand that finance tradition is very conservative function. We are not the one on the front line of innovation which is also uh, holding us back a little bit. There's also other reasons as well. Is uh, because finance, like I said, the tradition is very conservative. It's also being viewed as a um, cost function versus uh, someone who could actually generate Revenue and add value. And because of that, in my experience it's much more difficult for us to get the AI investment versus for someone like Sail who could already justify or roi. So that some of those factors definitely holding us back a little bit.

Speaker B: Yeah, definitely. Yeah. I think um, what you said about it being a uh, what did you say? A cost function or viewed. That's something, you know, for me as somebody who's like outside of finance, like I just don't, I don't get that at all how it could ever be viewed as that. How, where does that come from? Like being viewed as a cost function rather than.

Speaker A: Well, I mean with certain functions which view it as generating revenue for the company. And when finance tradition, if you look at it, uh, we put together the books, right. We keep books, uh, we do some projection but we're not the one who generates revenue. We view it as a compliance and admins function. And because of that, if you look at AI dollar investment and I'm talking about any company, big or small, uh, when we'll start uh, looking at allocation, where the dollars go, I guarantee you finance will never going to be the first function where people would say let's allocate their dollars. Because whenever you allocate any investment you want to see return on investment.

Speaker B: Of course. Yeah, of course.

Speaker A: It's much more difficult to justify it versus for example for sale.

Speaker B: Yeah, yeah. And that kind of conservatism that you mentioned, you know, the cautiousness. I suppose that's kind of. I uh, you said it holds you back but I guess it's totally understandable in a way in the role in, in finance like you said, when you're dealing with very sensitive data a lot of the time, like I think it, I can, I can definitely understand how finance would be. Let would be like less risk would be more risk averse.

Speaker A: Yes.

Speaker B: Than something like marketing where it's kind of like oh, you know, we can try a campaign and uh, maybe you know, it might cost us money but you know it's more about experimenting. Not actually but like I suppose if finance risk can lead to like really, really serious outcomes, um, impact for um, you know, if there's a data leak for example. Uh, and that has been some very, very um, public cases of that happening in organizations recently and it can be disastrous. Um, so I guess that, that, that does explain it a little bit. I think with. So that I guess that kind of um, ah, takes us on then to what we talk about next which is kind of like what is the cause of this cautiousness with AI. And, and do you think it is about kind of, do you think it is more about that kind of um, that ethical concern or concern about legislation or do you think it is more just about, you know, kind of the culture around it or legacy technology? What do you think it is? What's the main cause?

Speaker A: I think it's a mix of everything. And if you look at the industries, different industries, some industries are more regulated when our like financial institution, I'm an RBC customer so I definitely would not want RBC to play uh, with AI, uh, not in the responsive way. Right. Because they hold my money. Some other industries are not as highly regulated and like big tech. Right. That's why we're on the front of innovation. I do think you mentioned legal legacy technology. That is a huge part in my experience because some of these ERP systems are decades long really and even if you want to implement the cloud based AI solution, you can plug them in. Because some of this legacy system were just not designed. We were not developed at that time. I know it's changing, but it requires more transformational effort. But you think that's why some of the startups, I think we're moving uh, quicker than some of the larger companies because we start everything fresh. And you also mentioned culture. That is a very important component, especially in finance. In finance you would hear uh, some people say if it's not broken, don't touch it, don't change it.

Speaker B: Right.

Speaker A: And I think that needs mentality, need to change. But I also think that you could have good intentions, but you could have great culture. But if you notice, MIT recently came up with research which was said 95% of AI efforts fail in the corporation. Of course it's because with the disconnect between all this great intention, yet we want to do the transformation and we want to be great and doing this AI and actual execution and implementation. Because you sometimes don't have right people, sometimes it's too political, sometimes it takes a long time to make decisions about anything. Or sometimes you don't have right people at the table. Right.

Speaker B: That's why it feels a lot at

Speaker A: the implementation uh, stage. While a lot of companies could have good intention.

Speaker B: Yeah, I can totally understand that mentality as well. Of like, well it works, what we do works just about so as long as like nothing's going horribly wrong. I think sometimes people are hesitant to change anything because they think, well, if we make that change we're taking a risk that something could go wrong. So why mess with what we have, you know, I think, uh, maybe it's the mentality and also like you said, people who've been doing it for a long time. It is a hassle, isn't it, to learn a new way of doing something, I think. And we're going to get onto that a little bit, I think, like the kind of um, AI literacy, which uh, is big. We can get onto that now. I suppose we can, because we can start talking about um, you know, um, how. How do we change this actually? Like what, what do you think? Like what is, what are the main, what do you see as being the main. The thing that we can start doing, um, to shift this and, and really kind of integrate AI into finances it through kind of education, Is it through uh, advocacy, having the right people at table working. Do you see? What do you think?

Speaker A: So you mentioned one important point about people being in the same place for a long time. And that's a real problem because if you've been doing the same thing over and over the same way, and someone comes to you and says, you know, what was a better way to do it? You're going to look at them and say, well, I know what I'm doing and this is the best way of doing it. So that mentality of having people doing the same thing over and over needs to change. And this is where, when you say, how could we change it? We as leaders have a lot of power to change it.

Speaker B: Yeah.

Speaker A: I spent some time, I would say, at Ramozone, which is probably one of the most transformational environment I've been to. Whenever I come to a different organization, I could immediately sport things that could be changed. And I start with observing and then suggesting change. So I empower my team to think the same way. And that's what we need to be doing. Making sure we start change, um, in mentality, in a way of thinking that it's not going to eliminate the job, but it's actually going to uh, make finance more valuable and uh, create some insight which could add to the business?

Speaker B: Yeah, I think so. I think that's a really, really great point. And you know, I've had guests on here in the past who've kind of talked about, you know, this, this I guess, perception of finance leaders as the kind of number crunches in the background. Um, you know, like, I guess a very kind of, not, not necessarily very innovation heavy. Um, and I guess that goes, speaks to what you're talking about, which is that once you change that mindset and you think of yourself as being like how much more could we do uh, in terms of how we're interpreting the data and how we're using it to uh, inform decisions that are being made at a broader scale then that, that then leads to I uh, guess more enthusiasm about embracing these tools, doesn't it? I think once you have that mindset shift. What do you think?

Speaker A: Absolutely. No, absolutely. I mean I think right now we're talking about AI in finance. Right. The overall the role of finance needs to change. I speak at a lot of CFO conferences and it's always come up how could part the perception of finance could be changed from being a gatekeeper, someone who says no to someone who says yes and being treated as a business partner. It is a problem where your business uh, partners only see you as a number crunching function. As someone who. We only could come when we need approval. What we need to have is uh, um, business partners to have finance at the time table when we're already thinking about something. Right. So that's why we need to start um, just change perception from being uh, backwards and conservative function to someone who is open to innovation, someone who deserves that sit at the table.

Speaker B: I see like so not like the fine rather than the final obstacle before we get something done. It's somebody who's involved in the process from the get go.

Speaker A: Well actually give your business because we have a lot of data, uh, we do get this data from someone else but we have a lot of financial insight and insight in the business which we could uh, if we have time, if we free up our uh, time from manual tasks. Right. And that way AI is allowed which is going to help the business to make better decision. But we need to make sure that we grow into this and the business is looking at it as someone who adds value versus someone who has a compliance based function.

Speaker B: Yeah, yeah, definitely. Having said that though, I mean I think the um, that ultra awareness of compliance that is necessary in the role is actually something that's very needed in AI adoption. I think at the moment, uh, especially it's one of the kind of um, top concerns that people have I think about AI right now. And I was wondering how are we going to sort of balance this do you think? Like you know the kind of, you know it feels like with AI there's kind of this still this mix of fear and um, trepidation and that's normal with any technological shift. How do you see us being able to balance the innovation I guess with the caution uh and I guess this is true not just of AI, but of the, of your role in general, of the finance role for anything. What do you think?

Speaker A: So it definitely matters. Right. Especially um, in a large organization. For example, you can't really uh, do anything in a large organization, especially in financial services without risk being involved or compliant being involved because everything needs to be approved. In small organizations it's a little bit easier. Sometimes we may not have as many resources, but. Bit easier, uh, uh, because they may not have a strict compliance function. Again, it depends on the industry. Right. What I always say you need to start with something. Start with low risk, high impact areas. Don't start for example with public company reporting.

Speaker C: Mhm.

Speaker A: HSC reporter. It's a high risk. Right. Uh, so start for example with reconciliation. I'm giving you an example. Or developing a better forecast. Reconciliation where a lot of companies still spend significant amount of time, amount of people you have employed worldwide. It's unbelievable. Start with that. Start with for example, which we've seen very recently in our organization, automating policies and procedures. Expense report. What's uh, some of the traditional way of checking the expense report. The expense report comes from the business and when someone uh, checking spending hours checking whether that expense report matched to the policy, it's the extent when it takes a significant amount of time to approve that report and business starts screening. Believe me. Right. At a very senior level. Uh, instead automating some of these policies allow us quickly to check the uh, compliance, uh, which is like multiple hours, could come down to 10 minutes, something like that. So it's a very important area, but it's a lower risk. I would say if you start with these areas you will build the momentum, you will build confidence and then you could move in a high risk area.

Speaker B: Yeah, yeah. I think that's a sensible advice for anyone in anything, isn't it? In a way. I think it's um, you know, um, because you kind of get an idea I guess of what could possibly go wrong when the stakes are low. Uh, and that's kind of like a test run.

Speaker A: Exactly.

Speaker B: When you want to roll it out and you can kind of uh. Yeah, I think that's, that's definitely true. Yeah, that's just really, really great. Yeah, sure.

Speaker A: Yeah. You always have a pilot, right. And if you think about any transformation he has one of those would always start with a pilot. And you're not going to come or pick that pilot as the most important uh, division in a company because you're going to, it's going to stop the operation. You're going to pick some division and when you, uh, see how that goes, then, um, learn from your mistakes.

Speaker B: Yeah, absolutely. Um, okay, so what do you think then? Um, what should finance leaders be doing right now in terms of kind of, uh, to prepare themselves then? Because this AI change is kind of is coming and it's coming for. It's going to touch everything eventually. Um, and I think, you know, we talk about finance being cautious, but it's just a matter of time, isn't it? I mean, it's gonna, it's, it, you know, it's gonna be a kind of sink, um, or swim situation. We either embrace it or we fall behind. That's, that's kind of what I think. So what should we do? What should finance leaders be doing right now, do you think? To prepare themselves, to educate themselves. What advice would you give?

Speaker A: So I don't think we have a choice, to be honest. The AI is here and it's taking over. I think it could take some companies and some areas of the country, of the world, uh, could still have some time, but I think it's already here. Um, the one thing which I always say when you ask me a question, we should be doing something instead of kind of sitting and hoping it's going to be after me. So the first thing before any has been implemented is first of all, we need to get our people trained, um, on A.I. because, uh, if you look at the finance skill set, it's accounting finance, it's not necessarily data science, at least I'm talking about not the new hires, but the people who've been around for at least 10 years or something like that. So we need to make sure that people, uh, we don't have to understand the entire AI doesn't have the entire tool, but we need to understand at least some of the simple AI tools and how AI could be used. The second thing that I always suggest is to do some secondments to have finance people being seconded to some, um, project which is led by team. For example, you have some, uh, AI implementation project may not necessarily be for finance. It might be poverty division, but have finance, uh, team members spend some time on it. Because by doing that we're going to learn some AI tools. We're going to learn, for example, altercation. I'm just giving an example, more simpler one. Right. We could learn tableau and power bi, something like that. What we could bring back to the team that actually excite a lot the team members, because we get involved into something outside finance and when we come back and we become champions, I feel like something that is what I see, uh, worked in the past, in my experience.

Speaker B: Yeah, the kind of skill sharing. Right. Um, I think that's really powerful. Um, in any organization, uh, rather than kind of doing, you know, usual where we sit in a meeting and we watch the senior leaders kind of a lot of times share slides on things, it's like, it's a good idea, I think, to bring in people who don't normally share things and say, like, what have you learned? You know, you've gone away and you've learned this new skill, you've done this. I think that's really, really great. And I think, um, a lot of organizations benefit, I think, from that, you know, from bringing in more skills, you know, more talents. I think in that way is a great idea. Yeah, definitely.

Speaker A: I think people need that. I always say, I always, um, inspire people and give them ownership. And I, and I basically, whenever they come up with some ideas, I let them lead that project and I let them educate their peers about it, because that's what makes them exciting.

Speaker B: Yeah, definitely. It's good for work culture as well, I think, as well. I think probably in, in finance like that, that, that is probably something that isn't talked about enough as well. Is that kind of like that, uh, that collaboration in the communication. But I think, um, you know, I mean, I don't know, correct me if you think I'm wrong, but like finance, again, being viewed as someone who's kind of separate from everyone else, but I guess when you've got them actually sharing skills, uh, and talking, it removes that kind of stigma, doesn't it? Um, and I think that's a really, really good thing. And because we should all be integrated, shouldn't we? You know, I think every department, wherever you are, should all be, should all be talking. You should all be cross, functional. Um, that's the goal. And it doesn't always happen, but it's what we want.

Speaker A: That's exactly. With a lot of silos, for sure.

Speaker B: Yeah. Yeah, definitely. Um, okay, so what do you think then? Um, how long do you think this is going to take? What do you think? Because in terms of, obviously you've talked already about the kind of, uh, impact that you've already seen and how you've already used it. Um, but what do you think what timeframe we're looking at for this to be adopted? Do you think? Globally, what do you think? Let's go.

Speaker A: If you would ask me that 10 years ago I would have thought everyone's already now on AI. After what I have seen I think it's going to take time, at least 10 years if not more. And there's a reason for that. Right. As well, like I mentioned, uh, what are some industries which have to be more cautious? We have to build their own tools. Financial services, one of the examples. That means it's going to take longer. It needs to be also a generation change, I'll be honest. Right. That perception of finance, that we need new people who educated with new skills to come to um, to start working as well as uh, get to certain level. Um, and that's going to take at least 10 years.

Speaker B: You think so? Yeah.

Speaker A: On a global scale. On a global scale. That doesn't mean like some AI is not going to be implemented. I mean some uh, um, startup which is like way ahead of this. Right. I'm talking about some of the uh, global multinational companies. It's definitely between five to 10 years. On the global scale.

Speaker B: Yeah. Do you think in financial services, um, you talked about this a little bit. But is there, do you think they're scared of like customer response sometimes a little bit or like kind of that, you know, when you're dealing again. Again. I guess I'm going back to kind of sensitive data here again. Are they worried that they're going to scare people off a little bit? Uh, do you think if, sort of, if they embrace this technology too rapidly or what do you think?

Speaker A: Well, I think it's a very high risk. Right. We talking about, I mean if we talk about the bank, like I said, if I would hear that one of my banks would just be implementing AI very rapidly. It's my data involved here.

Speaker B: Yeah.

Speaker A: My customer data. Uh, it involved gear.

Speaker C: Right.

Speaker A: And a very sensitive data. So we need to be regulation around um, infrastructure. Right. And controls around the data. It's one thing. And when the data needs to be correct, that's kind of a different thing that financial services definitely more highly regulated than a lot of other industries. Uh, you have to meets the regulator, um, requirements and also what needs to happen as well the regulation about AI need to come in place when you ask how long it's going to take. How long is it going to take for the regulator finally to put certain requirements about the data, for example. So that matters as well. So I think financial services definitely takes longer to. Because also we we developing a lot of tool internally versus someone else could go buy them in the market. It's very risky for this particular industry.

Speaker B: Yeah, yeah, I, I mean I totally understand that definitely. And I think people are, people are more aware of these Things I think than ever. More hyper, hyper aware of it. And I think it's definitely something you said about. Yeah, yeah. I mean, I, I, I can only agree. If I found out my bank was, was, um, you know, inputting my data into some new AI system, I'd be, I'd be freaked out. Yeah. I mean, and I'm very someone when

Speaker A: you bought from someone else. Right? Like, I don't want my data. I love chat dpt. I mean it's, but I don't want my data to go into some random chat dpt.

Speaker B: Yeah, yeah.

Speaker A: It's all my bank information in there. Right. It's my social insurance number. It's Social Security number too.

Speaker B: Yeah, yeah, definitely. Uh, okay, so we're gonna, we're coming to a close now. Um, I thought maybe we could do some, some just kind of more kind of general questions about the finance role. Um, what is your, these are questions I kind of ask everyone at, uh, the end of the podcast that I just think are really kind of fun for like shorts and stuff. Uh, so, um, what is your kind of the biggest kind of finance myth that you'd like to see go to room 101 that you'd like to see disappear? And about the finance role that we always say no.

Speaker A: Okay, I don't want people always think about that. Someone like a policeman or someone like that. I want people to start thinking about as true business partners who could help versus, uh, prevent business from doing something.

Speaker B: Yeah, yeah, yeah, definitely. That makes total sense. Yeah, yeah, Great. Um, okay. And what do you think? Um, let's sort of split it in two. So where you think, where do you want the finance role to be in 10 years time? And then realistically speaking, where do you actually see it being? Where do you think it will actually be?

Speaker A: Definitely when I talk about being a strategic business partner where people come to us for insight and information and help them to make new deals and go to new markets. I want us to become strategic function versus transactional. I also want us to eliminate manual processes. We have a lot of manual processes. I'm talking about, uh, every single company I was working for, every single. So many manual processes. We spent so much time and uh, so many people on doing things which take our time away from doing things which really matter.

Speaker B: Yeah, yeah, yeah, absolutely.

Speaker A: Move away from this and start like uh, being, analyzing things and thinking about the future and telling what the future is going to be versus keep focusing on the past because that's what we're doing. Uh, that's what I really Want us to, to be. To be. Are we going to. I also want finance department to become not just all accountants and finance majors, it's like data analysts, right. Maybe engineers or something like that where, um, we could work together. Are we going to get there, like I said, within five years? I don't think so.

Speaker B: No, no, no, absolutely not. You think it's going to be. So you think it is inevitable that these manual processes disappear, but it's going to be a long time coming. It's going to take a long time.

Speaker A: What needs to happen, right, in order for everyone to adopt. If you think about like the phone, when we got the iPhone, it started with someone and when everyone started adopting and everyone saw the benefit and that's like how long it took us to adopt, how long took it in Internet. I know with a lot of companies out there who are not Amazon, who are not Google Google, uh, who are very profitable companies, but we're still doing things that we've done for 20 years because like, remember we talked about that before, it works, it's not broken. So to convince them that we need to bring AI and implement the risk which is going to, uh, uh, stop some of the finance operation or business operation, it needs to be major evolution happening.

Speaker B: Yeah, yeah, yeah, yeah.

Speaker A: Where people start talking about, yeah, hey, we implemented AI this work and we, we saved this time and for this to happen.

Speaker B: Yeah, yeah, yeah, yeah.

Speaker A: Like any revolution in any new invention happening, it will take years.

Speaker B: Yeah, absolutely. Yeah. And I think that what you did, what you're saying there, that is really the difference, isn't it, I guess, between a kind of, um, maintenance and an innovation mindset. A kind of like, oh, you know, this works, we'll keep it going. And then the innovation mindset is more kind of like, but how much better could we be? You know, how much better could we actually be? And I think, um, yeah, it takes, maybe it is going to take some time, definitely.

Speaker A: It's also another thing why it's taking it long. Right. Some people think about it as a threat to the job.

Speaker B: Right, of course, yeah, of course. We haven't even touched on it because

Speaker A: you're thinking, like, what is this gonna do? Like if I implement, if I simplify certain thing, when it doesn't require 10 people, right. It may require, uh, one person. And some of the people I've really reluctant from doing it. And while we continue to have this type of mentality, it's gonna slow that down. That's why I said it needs to be generational change as well, because some of the new kids on the block, we think different way than people who been in the business for 20 years or 25 years.

Speaker B: And you need that. Yeah, definitely. I think people who are coming into it for the first time, um, will be thinking about, they won't have any kind of preconceived notions about what the role is. That's the thing. Uh, and I think, yeah, when you've been doing it for so long, it is really hard to keep that going, I think. Especially when it's a high stress role. I, um, think. Yeah, that's a really, really good point. I like that a lot. I also like what you said about, um, you know, not just people with finance degrees, uh, with a financial background. You know, you could have some, um, what's the word? Like, um, you know, you bring in people from different skill sets. Sometimes can be really helpful, I think, in freshening any kind of anything up, you know, any kind of discipline up. Um, yeah. What would you like to see? What kind of people would you like to see in finance? Would you say?

Speaker A: So it's interesting that when I was starting my career, uh, I got into accounting. Many people don't know. I actually have a math degree.

Speaker B: Oh, okay.

Speaker A: Yeah. Which has helped me a lot because it's a highly analytical mindset. I'm good with numbers, but a highly analytical mindset. I look at certain things in a different way because I also studied statistics. I also have an economics degree which is whenever we do the uh, podcast, uh, it reminds me of my econometric class many years ago. So you want to have people who are data scientists who um, have engineering background as well, like AI skill set. You still want to have the traditional finance major, maybe a little bit of accounting. But I do think that accounting could be automated a lot. So it needs to be a team from different professions. We should be also economists as well because I think we sometimes are missing that economy, um, background when we do forecasts. It's not just like 10 accountants in a room for being the same as.

Speaker B: Yeah, so you talk about the economics background. I guess that's, that would be helpful in terms of being mindful of like where, I guess like what the current kind of financial climate is almost. Is that what you say?

Speaker A: Absolutely. Because like the external factors impact the business as well. Right?

Speaker B: Of course, yeah, yeah, yeah.

Speaker A: Historical performance. It's, it's operational drivers, it's external signals. So if you don't know a, uh, uh, economic. If you don't have that background, you would be just focusing on historical numbers. This is where a lot of my experience comes in as well. Like I'm a CPA math degree. I also studied business, but I have a very good understanding in terms of how the external factors impact the business as well and that come from my diversity of my background. If I were just an accountant, all I would have known is just how to do journal entry. Well, get what like chat deputy could do journal entry now.

Speaker B: Exactly, exactly. Yeah. Well, we're talking about now I guess is, um, you're only, I guess you're only going to be fearful of your job going if your skill set isn't. Isn't broad enough. But if you broaden out what the role of finance is and it is more strategic, then it's safer, isn't it? I guess like it's. Or it's.

Speaker A: I don't think you whenever. I don't think you need to think. When you think about the narration. Safety is not the right word. How I could do this better and quicker. I use. I personally I can't live without ChatGPT or Gemini or Copilot I can't use because it helped me to do certain things quicker.

Speaker B: Yeah, yeah, yeah, yeah. So then you can start using your brain, actually using your brain once you've done certain things.

Speaker A: Yeah. Because you kind of. You almost have like a friend or you could have a colleague who has access to more information than like a human and could be your sounding board sometimes as well. Right. It could switch. So if you think that way you naturally will evolve and the way you do your job will evolve. But if you just used to doing the same thing and you start thinking like, well, I used to do the journal entry. I used to do this pedal thing or um, I did certain things certain way. Obviously you're going to make yourself redundant at some point. It's a mentality shift. It's a mentality.

Speaker B: I think that's really a really great point. I think that really is like. I think that's been the main gist of this conversation is that ultimately, you know, um, we're talking about something that is, you know, um, an external factor, but really it is. It's an internal mind shift that needs to change. That's, that's really the big, the main gist of this. I think it's really great. Um, just, just out of curiosity, um, what is the thing that you use AI for? Um, or particular or chatgpt. Whatever it is that like you think like, like it just kind of makes you go, oh, that is such a lifesaver you know, like, like it like you, you kind of think like I don't know how I did it this way before. Is there anything like that in your role or even outside?

Speaker A: I mean dashboard, like example dashboard like instead of like looking at this numbers, looking at the dashboard. Uh, and because ChatGPT could also give you the narrative like I said, right? You could also tell you this is how I could looking at this performance and just saying with this forecast and saying, hey, this is what I want you to know. What you could say example as well is like I said, I use ChatGPT everywhere I go to the conferences. It could give you the speaker notes. Yeah, I could look at, I'm giving you an example, right? Forecast. It could give you suggestion. You could look at. It could give you suggestion for example. I'm just giving an example, right? Like let's say the company is implementing revenue recognition standard. If you develop an internal version of CHAT dbt that could actually tell you all the guidance you need to know, everything you need to consider which is going to be very valuable when you go to the business and say before you do that, this is what you need to be aware of. Benchmarking as well. For example for the public company report, benchmarking, uh, is extremely important just to see what your peer is doing. You could use AI to do that as well. In AP we use this to do three way matching very quickly match, um, the invoice, the purchase orders. There's so many opportunities, to be honest.

Speaker B: Yeah, it's massive. That's what I was saying before, before like this is not um, this is not obviously not a flash in the pan. This is like huge. Like there's, there's nothing it can't touch. And I think that's why people are fearful of it. Like you said, there's the job loss fear always. But I think it's just uh, like you said, the way around it is just you, you can't worry because it's inevitable now the genie is out of the bottle and you've got to, you've got to adapt to it.

Speaker A: You get on that train or the train will leave without you. So the. Will you get on that train better?

Speaker B: Yeah, absolutely. And learn how to work with it? Definitely. And learn how to kind of augment the skills that you had that you weren't able to use because you were bogged down with so many other things that you had to do before. Um, I think that's probably the point.

Speaker A: That's a we spending so much time during the Day on things that someone else could do. And I'm talking about they are. But we don't actually have time to use our brain sometimes.

Speaker B: Yeah, exactly. Yeah, yeah, yeah, absolutely. Yeah. That's really common experience.

Speaker A: We're very smart professionals. Right. We're very smart leaders. So we should have time and capacity to be able to look at the, analyze that information, to read those report. But right now, a lot of time we do it ourselves. And I'm talking about our teams right now. Right. Which don't have time to do anything else.

Speaker B: Yeah, yeah, definitely. I think more time to think. More time to think, think leads, uh, to more time to innovate. Definitely. I think big time. Yeah. Well, thanks so much, Nikki. It's been a great conversation. Um, if people wanted to reach out to you, talk, uh, to you more about this topic, where should they go?

Speaker A: LinkedIn.

Speaker B: LinkedIn. That's always.

Speaker A: Oh, come to the conferences, conferences around the country. So always I'm always open to, um, hear about what others are doing as well, our leaders, uh, because it's interesting, it's how we learn.

Speaker B: So for sure, yeah, definitely. I mean, this kind of change that you're talking about, it's going to happen through conferences like what we do at Finance Alliance. You know, it's. It's getting together, people putting their heads together, sharing these frustrations with each other as well, I think, and, um, inspiring people like you do, you know, talking about how the role could be different. Uh, really looking forward to it. Uh, Nikki, thanks so much for today.

Speaker A: Thank you.

Speaker C: And that wraps up another episode, episode of the two Cents Podcast. Thank you to our listeners for taking the time to tune in. If you enjoyed this episode and want to hear from more finance leaders like today's guest, please subscribe to the show and leave a rating or review on your favorite podcast app. It would mean so much to me and my guests if you can show them some love and appreciation for sharing so many great insights with us on the show. Again, thanks for listening. See you in the next one.