Why CFOs Can't Just Layer AI on Broken Processes - with CohnReznick

Speaker A: Foreign uh, welcome to the FEI Podcast, where financial leaders come to think forward, lead with confidence and navigate what's next. For more than 95 years, financial executives International has brought together financial leaders to share insight, shape strategy and elevate the profession. This is where those conversations continue. Real perspectives from the people making the decisions. Real strategies from inside the moments that matter most. What you see is the outcome. What shaped it is what we explore.

Speaker B: I'm Heather Cole, your host as a finance leader, executive coach and proud member of fei. I'm here to bring you conversations that go deeper, from leadership and strategy to innovation and the future future of finance. Because what shaped the outcome is often where the real lesson lives. If you've ever found yourself wondering, am I doing this right? You're in the right place. Let's get into it. What if the biggest AI challenge for CFOs is not the technology itself, but the culture required to use it? Well, I'm Heather Cole, Executive Advisor and host of the FEI Podcast. In this episode I'm joined with Jennifer Witts and Kyle Broke of Cone Resnick, a leading advisory, assurance and tax firm that helps organizations navigate change, improve performance and prepare for the future. Jennifer is a partner at Kroenresnick's Client Advisory Services Practice where she helps organizations modernize finance function through technology enabled solutions, process automation and operational transformation. She brings deep experience leading large scale transformative initiatives, standardizing tech stacks and integrating AI driven solutions to improve efficiency and decision making. Kyle is a Director at UH Coenresnik's Client Advisory Services Practice, working with mid market companies and growth oriented companies to strengthen financial leadership, operational reporting and technology adoption. His background includes multiple CFO uh, leadership roles, giving you a practical perspective on how finance teams can adapt during periods of growth, transition and of course, technology change. Together we explore why CFOs simply can't layer AI on top of broken processes and expect transformation. Jennifer and Kyle share why finance leaders should start by identifying the repetitive, painful work that slows teams down. Then use AI and automation to elevate people to more strategic and analytic and advisory roles. For CFOs and finance leaders who feel excited but maybe a little overwhelmed, this episode offers a practical path forward. Start small, focus on meaningful use cases, bring the right people into the conversation and build momentum one bite size, win at a time. Welcome Jennifer and Kyle. Jennifer and Kyle, I'm super excited to have you today on the podcast and I'd like to before we hop in to getting into AI and technology and the future of finance, I'd love For you to each briefly introduce yourself and kind of share what you're seeing in finance. I mean, everything is changing. What's the big nuggets you're seeing? Jennifer, we'll start with you.

Speaker C: Sure. I'm Jennifer Witts. I'm a partner here at Cohen Resnick and I'm currently focused on our hospitality vertical and what we call client advisory services, which is outsourced accounting. And we're seeing huge trends in outsourced accounting. Really? And I think previously what we were seeing in the finance space was, uh, it was small companies that did not necessarily have the resources to hire full time teams. But we're seeing larger companies that are now seeing this to be a really smart model because there is an issue in terms of finding talent, finding the right talent, and then also being able to work with individuals who are invested in AI and can start to work in a more modern way that's sometimes hard to find. So we're seeing lots of trends in the finance world for larger companies that are outsourcing their financing accounting departments.

Speaker B: Excellent. How about you, Kyle?

Speaker A: Good to be with you, Heather. Name is Kyle Roog and I am a director at ah, Cohen Resnick. I lead our construction and real estate verticals. I would say a majority of our staff and clients, they're excited to see how AI and these technology improvements kind of impact their day to day. Everyone always has questions on like, how can we utilize this, how do we deploy it? So definitely a relevant topic for what we experience on a day to day basis.

Speaker B: So the topic that you guys kind of brought forward that I thought was really interesting for the FEI podcast is that how technology impacts the organizational culture. So when you hear that phrase, what does that mean to you guys inside of finance?

Speaker C: Yeah, so when I think uh, about culture and specifically uh, with what we do with outsourced accounting is how do you keep your people engaged in what we do? Because a lot of finance and accounting can be repetitive, especially if we are digitizing it. And so as we think about culture, how do we keep our teams engaged and excited about what they do every day because of the repetitive nature of it. And I think with AI coming onto the scene, it's given everybody something new to think about and new ways to engage with their work and also different opportunities for them to automate those recurring pieces and start getting a little bit more creative and how do they actually serve clients in a different way. So for me, that's been the most exciting thing about how AI can impact culture moving forward.

Speaker B: Yeah, I think that you know, when I just got back from the FBI Leadership forum and what was interesting, there's a unique buzz about. Everyone's really excited about AI, but they're also a little intimidated. Right. I think that we all have that. Like, I don't know about you guys, I try and study this, but I always feel like I'm behind a little. Like how do you get your teams to balance that or what do you recommend for them to balance that? Kind of I need to learn, but I need to do my regular work. And like what does that look like to you?

Speaker A: I think from our perspective we have a, uh, we've got like a core user group that is really invested and I would say has the, the technical capabilities to go and learn a lot of these technology and AI related topics and then they bring it back to our group, they kind of develop some use cases and then they get the buy in of the other team members and how we can uh, both internally but also bring to our clients some of these improvements.

Speaker B: I love that kind of blended model. It sounds like you have like the special forces that are constantly learning and then the special forces are training the people that are actually in the trenches. Right. I love that model because, uh, AI is just coming so fast to do both jobs would be overwhelming. So I love that AI is moving faster and faster and so many leaders are excited about. What do you think the biggest mistake that maybe CFOs are looking at today in your client organizations about AI?

Speaker C: I think if you're jumping in and a lot of people are jumping in without a plan, that can cause a lot of issues. It's really what do you want to achieve through AI and just throwing that into the mix is not going to get there. It's what are the steps that you need to take in order to successfully implement it. And everyone will say you have to have those change management pieces as well. So I think just really understanding what it is that you want to get out of it. But then once you've determined that you really have to make sure that you've got the underlying processes in place, I think that's probably something we can talk a lot about, which is if we try to throw AI on top of a broken process, you're not going to get good results. So I think that that's one of the things just not to jump in without a plan and make sure that you've done all the prep work before.

Speaker B: I like to say that AI is an accelerant and if you have like a bad plan or you have going in 50 different directions, you're going to get 50 different directions faster. Right. As we kind of look at that opportunity in AI and so forth, if you were sitting down with a dear friend that was maybe the CFO of one of your clients, but they became a, uh, close friend, where would you tell them to start to create that plan? Like, where do they even start? Because you hear everybody saying experiment, experiment. But maybe experimentation isn't the way. Maybe we've got to start somewhere else. Like, what are your thoughts on that?

Speaker C: Yeah, from my perspective, I think often it's going to be the tasks that are the most painful or the most repetitive. And so as a leader, sometimes you don't know what those tasks are. So I really feel like it's the collaborative effort to speak with your team to truly understand what are their processes. You know, if you can collect data around it, which is something that we often do in accounting, you know, we have time, data and things like that. But if you can collect data and you can start to develop some patterns where you're seeing time that could be saved. Repetitive tasks, things that are taking much longer than what was expected, that's where I would start. But usually you have to talk to your teams to understand what areas are ripe for this implementation.

Speaker A: I think to expand on Jennifer's point there, once you start engaging and talking to your staff about, hey, what takes too much time or what don't you you like doing in your day to day? I think the staff then all of a sudden gets excited like, hey, if I could get this off of my plate, right? It's a lot of taking these manual like data entry level type tasks and saying, okay, we can make this more efficient or we can leverage technology to do this.

Speaker B: I get that. Uh, but my question then is, what about the flip side of the coin? Because I see my experience in people I've been talking to, there's two camps. There's one camp that's super excited about AI and they're nerding out and there's like up all night trying new things and, and like just going to town. Right? Uh, that's me. And then there's another camp of people that I'm going to call the, the people that are terrified that they won't have a job. They're terrified. They tend to be like hoarders. Like, this is my task. Yes, it's very manual and I do it every month, but I'm not letting go. Like, how do we as leaders address that, going the two sides of that.

Speaker A: So, uh, that's actually something that we've addressed both within our team, but also at clients. And, uh, the approach that I've taken is your time really is going to be transformed. It's not necessarily you're going to be out of a job or you aren't useful or valuable. Right. To me, it's, we're going to take just mundane, like routine tasks and say, okay, we're going to leverage technology, leverage the AI to complete this. What we need is for you to utilize, like your brain. Right. Like you as an individual. You're looking at something, you're analyzing and you're providing that review or that feedback.

Speaker B: I like that. Yeah. Because there's that fear. But it sounds to me like you're saying we really need to work on our culture and our trust, uh, factor. Right. Because there's some people that are saying right now AI is eroding trust within the organization because we're not creating that connection. Like when I ask you and say, hey, Jennifer, I need a hand, can you help me? You're an expert in this. We create a bond. Right. But once we go, I'm just going to do this in Claude. Claude and I have a different kind of bond. But what techniques can you have for helping to build that? What I'm going to call the safe culture that says, AI's an empowerment, not a job replacer.

Speaker C: Well, I think we talked a little bit about experimentation, and so everyone is still experimenting. And I think you do have to create a culture where it's okay to fail. So if you were to say to your team, I want you to bring back different use cases, and someone said, oh, I tried this use case. I spent hours on it and it didn't work. That's okay. And I think that we've got to normalize that and make sure that that is okay, that you can fail with this. And that's fine because it's still learning as long as we're learning from that and continuing to move needle on it. So I think that that's one thing, and I think as a leader too, just being very open about your own failures with AI and your own insecurities with AI. Like, I tend to think that I use it quite a bit, but I still get confused with all the different versions. I'm like, uh, which version should I use? Like, so I'm very open about that. And if I can have someone on my team help me with that, that's great. So I think we're all in the same place. Yes. Others are, like you said, nerdied out and they're much more advanced on certain things. But we are all still truly learning. And so I think that we've just got to be open about that and okay, that we are experimen failing together. But as long as we're all learning and moving forward, we just have to make that a safe place.

Speaker B: That's an interesting thought because it's kind of a shift, right? I don't know about you, but coming up over the years in finance and technology, I always thought I had to be the best, right? I had to know everything. And that was honestly what kind of made me successful, is I worked maybe harder than other people did to get really good at my craft. But now we almost have to, to change and say it's okay to be messy. Like I need to get a little messy with AI. Uh, is there techniques that you know or things that you're looking at that are the red flags where people should say, I don't need to learn all of this my own, I can get help from outside that's done it faster. Where's that usually showing up or people? Because I think that what I've learned is getting help from others makes it go so much faster. Like instead of trying to sit there all night and weekend trying to figure it out, go find somebody that's done it. Like when your clients are coming to you and saying, I, uh, need help, what are the typical things they're asking for?

Speaker C: I think again, if it is a company that doesn't, and usually this is the case when they, when they do come to us, that maybe they don't have robust processes in place or they don't have anyone identified as a champion, then I think they're going to just kind of run around in circles and not get anywhere with it. So they really have to have people, whether that be a function or just part of a person's personality and their interests. If they've got somebody leading it, we can help them with that. If they don't, then we probably need to bring in somebody to help change the culture of the organization and make sure that we bring in expertise and that they're not just kind of running around and trying to figure it out because it will take a long time without someone that's fully invested in that initiative to actually make any meaningful progress.

Speaker B: So as we look at the processes, how important is it that they really standardize before AI and automation? And can technology really fix a broken process or does it just make the mess faster?

Speaker A: I mean, to me, from what I've seen is you definitely want to fix the process, right? Like, I think it has the potential to, uh, to fix certain aspects of the process. But really what you're going to do is just like, similar to implementations, uh, if you're taking bad data in into a new system, it's still going to be bad data. If you have a bad process, you're still going to have a bad process even if you're utilizing AI.

Speaker C: Well, just to build on what Kyle said, I mean, an experience that we recently had is it's very rare, I think, that you get AI in any form and it's ready to go out of the box. You've got to test it, you got to experiment with it. Well, one of the things that we've learned through our own implementations is that if you don't have a good process, if it doesn't work, whatever that criteria is, it's very difficult to diagnose where the problem came from. Is it the AI itself? Is it the process, Is it the person? So you truly, if you're going to work with it to make sure that you do get the outcomes that you're expecting, you have to have all that nailed down. It has to be consistent because most likely it's not going to give you the result you want right away. So you're going to have to refine it. And if you don't have a solid process, where do you even start to understand why you didn't get the outcome that you intended? So we've learned that the hard way and you've got to have all three of those elements really nailed down in order to understand how to continue to refine and make it and optimize it for what you're trying to achieve.

Speaker B: Yeah, I think a lot of people look at AI as productivity, efficiency and so forth, but how important is it for them to maybe take a step backwards and say, is this process even what we should be doing? Like, I see a lot of times in my own business, I'm stepping back and going, okay, we've always done it this way. But wait, with AI tools, maybe we should like start with a clean slate of paper and think this process could be completely different and give us more results, faster, better. Like how important is it, uh, for that step away time?

Speaker A: To me, like, I think that's a key element, right? Because especially if you start working or you're, you're interacting in, uh, an organization that's been around for a while, there's a lot of Processes a lot of steps that it's. Well, this is how we've always done it, right? Like, we're. It's Sally. Right. Like, this is the way we did it last year, and this is how we're going to do it now. So I think this provides that opportunity to really look and assess and evaluate what are we doing now and how should this look going forward?

Speaker B: If clients have not done that in a while, that can be kind of scary territory, right? You're like, oh, wait, I'm going to step back. It's almost like when we reconfigure our chart of accounts, right? We're trying to look at the different. The organization completely differently. Now. Is that services that you guys provide that you can help them with that discovery of what we should look like? Because, like, how would they engage you guys for something like that?

Speaker C: Well, yeah, it just depends on what extent they, uh, want to get involved with this. On that. I mean, we have a team dedicated to building out agents for our clients, for looking at their entire tech digital strategy. So we can build, uh, agents, we can recommend different softwares, we can implement those softwares. So we have a whole service line. So if you want to go full gamut, we could do that at coenresdig. But on the smaller end of things, it's really just, you know, if we're looking at simple tasks, well, how do we ingest the data and can we get that data in a different way? Or can we automate the ingestion of that data and then can we figure out how to manipulate it using AI rather than having clients serve that data up to us in a specific way? So it can really just make their lives easier. So we can kind of run the full gamut of that just based on what the client's needs are.

Speaker B: Excellent. For a CFO that's listening, how should they decide which technology initiatives or which pieces deserve prioritization? Because I look at it, I do a little sticky note exercise. I give my little sticky notes. I think all this stuff I could improve. And honestly, I get a little overwhelmed. Like, there's a lot of sticky notes when I do this. What advice do you have on how we can prioritize that and figure out, you know, where to go?

Speaker C: Well, I think there's. There's two ways to approach it. I mean, one, so Kyle and I are working on advisory initiatives for our CAS practice right now. And what we said is you really have to figure out what your end goal is with your client. So talking through what's your one year, three year, five year plans and strategies. What are the objectives that you want to achieve? So you could look at it from that way and say, hey, here's this objective that's really important to me that I want to get to. How do I use AI to help me get there faster or help me get there with lower risk? So that's one way to look at it. I think that's the glass half full type way. The other way is by looking at, well, where do I have issues today? Like, what are the issues that I have? What are the pain points that I have? So you could go that route too. So either one of those, I think you're helping to advance the objectives of the firm. But I would, I would recommend, just like you said, taking that step back to understand what's truly important.

Speaker B: So, uh, this is an interesting question I have for you. That came out of the FEI Leadership Forum. I gave a presentation afterwards. A CFO came up to me and he's probably was like early 60s in age, and he said, heather, I've been tasked to oversee AI and I just don't want to do it. He was kind of like, I kind of just want to, like, buy my time and then retire. And I think I see that, uh, it's like something that people don't actually bring up. Right. If you were working with a firm whose CFO came to you and said, I got a confession, you know, Jennifer, Kyle, like, I just don't want to do this. What kind of nuggets can you give them or what advice would you give them?

Speaker A: I think that's kind of where we step in. Right. And that's where a firm our size and the expertise that we have. Right. Like, this is how we're starting to engage and interact with clients. We have the resources and the capability to assist that cfo.

Speaker C: Yeah. The only other thing I would add to that, I, uh, think Kyle's absolutely right. But I do see this. It reminds me of, like, when I finished college and I was like, oh, good, I don't have to study ever. Again, not the case. But I think for people that are, let's say, more experienced in their career, they're not necessarily looking to make a name for themselves in this area. And like you said, they're just hoping to get through the next few years and not really have to push themselves into this area. I do think there's a place for them because they do have so much experience and they have so much wisdom from what they have done that even if they don't understand all the ins and outs of AI and how to necessarily use it, they can at least provide that oversight to the teams that really are digging in to say, here's how we would review it, here's how we make sure that it's correct, that's just as important, right? So if we have blind trust into AI, that's a problem. And so I think that putting governance around it would, uh, be an area that someone who maybe doesn't necessarily want to get all into the weeds on it, but does need to be involved. That governance piece is huge. And that really can only come from someone that's got years of experience of how we used to do things and how we should deploy it responsibly.

Speaker B: Well, guys, uh, so I love this idea of outsourcing. I think for many organizations, it would give them the opportunity for the finance leader to really focus on their business. Being able to focus on that governance and using their expertise, but leveraging skills from an outside source firm. If a firm's to that point where they're like, you know what? We need help. We know that AI is a key driver in our business going forward. We're not quite sure how to do it. We don't have the time or the resources to do it all ourselves and learn it. What questions should they be asking when they're interviewing firms that are they're looking to help them?

Speaker C: Well, I think as just like a threshold question, one of the things you want to know is what platforms are they comfortable with. So at Cohen Resnik, we are a Microsoft shop. A lot of large companies are. And so having expertise in how do you deploy AI in that environment is really important. So making sure that you are at least aligned on the right platforms. The second thing I would say is just make sure that they actually do have a dedicated group. So anyone that's been playing around with AI may think that they're an expert, but truly there are people that are experts that are certified. And I think that that's really important. Make sure they have a dedicated group and they're not just trying to sell the hobby of somebody that's that's on their team. And the final thing is just to make sure that they are considering security. So again with the, uh, governance conversation that we just had, we've got to make sure that we've got security front of mind throwing in your data into an unsecure model or having it be trainable on your data, something you don't want to mess around with. And so if the firm that you're talking to is not bringing that up or asking those types of questions, that to me would be a red flag.

Speaker B: I love that. Because another thing that I, uh, had a lot of conversations with CFOs at last week's event is they were also talking about that they went to firms, they got these bids, and then they asked them kind of more details on how they do it. And they were saying that the firms were like crickets because what they've discovered is they really didn't know what they were going to do. Right. They were experimenting on the quote for the client. And I think that that is something that we all need to be like. I don't know, uh, I'd be like, warning Will Robbins, you know, danger alert. So being able to make sure you guys are asking the right questions. Kyle, you've served as a cfo. What questions, based on the knowledge you have today, would you be asking of a firm?

Speaker A: To me, my mind goes to like the payback or the roi, right? Like, what specific areas are we focusing on? What's the potential for either internal cost savings or are we redeploying? Are we able to expand and grow? But I think ROI is kind of top of mind.

Speaker B: I love it. Uh, do you think that AI is going to actually change maybe the role of finance teams and make them more strategic than, you know, historically we've been kind of like the people that report on what happened kind of project what might happen. But I think is this twisting or changing the role of finance leaders?

Speaker C: I think it is. I really do. You know, we still need to have some of those fundamental or foundational finance and accounting pieces. Like, we need to know that. But we've already started to see where we don't need to focus on that as much. And really what we need to focus on is how can we be even more creative in the advisory services that we provide. How can we tell the story better? Those are the types of things that we need to be focused on. I think another skill that will be really important is being able to review at that high level. And so it's something that I think about a lot is as I grew through my career, I did everything I was able to book journal entries, do a bank reconciliation, pay a bill. Like, I was able to do everything, which made me a good reviewer because I had done it well. There should be eventually no need for us to actually do that type of work. So how do you get people to actually review without being in it? So that's going to change the way that we assess things. Things. And we're going to have to get much better at recognizing patterns in data and being able to recognize anomalies or exceptions. That will take a certain skill that I don't think we've necessarily developed yet. So that will be changing as well.

Speaker A: And I think the speed and the access to information in kind of identifying, okay, here's where those anomalies are, and then getting to the underlying issue or what's driving that, that's what I'm seeing right now is we're able to, uh, dive into those areas a lot quicker than what we used to or what's been historical.

Speaker B: So does this change how we should be training our finance professionals coming up through the ranks like the younger ones? Because as you said, Jennifer, you grew up doing the journal entries and really learning by doing, we're going to automate all these systems. Right. And now it's, uh, almost like we have to teach people to think faster. We've built experience to be able to think bigger. Is it even possible to teach younger people how to think faster with the speed of data?

Speaker C: I don't know. I mean, we've talked about it and I've, you know, there's two ways of thinking about it. One is to have them actually do the work for a month or two, like in. In the world that we live in, where again, we have, like, these repeatable processes. Let's have them actually do it. Okay. So then they get that experience. And what would typically happen in a normal environment is you do that for a couple months, and then you do it for the next eight or nine or ten months, and it gets very boring. Right. So we can get rid of that boring part of it for them. And we can say, now that you've mastered it, now you can move on to this next level, which, again, I think is much more engaging for our people. So there's that school of thought, but that's not necessarily the most economical for a company to do because you're kind of wasting time on people doing things slowly. And so then there is the, well, let's just take that out completely and let's figure out a new way to train them and let's make sure that they are using, you know, they're going to have to have a stronger background in data analytics, truly. And so that would be another capability they have to come or that we have to train them in. So I don't know what the answer is. Like, we're still really experimenting with that to see how do we get good results from our less experienced people? How do we train them up in this new world? I don't have the answer yet, but there's different ways to think through it.

Speaker B: I think, I think it'll be interesting to see how that plays out because, uh, like you, I see it both ways. And it's like, which one will actually work? We don't know it. Stand by, we'll find out, right?

Speaker C: Absolutely.

Speaker B: So if, uh, a finance leader is still. They hear this, they're like, okay, I can outsource this, I can get help. But they're still feeling like they're way behind in AI. What is one step they could make this week to start to make progress? Like, if we had to give them one call to action, what would you tell finance leaders to do?

Speaker A: From my perspective, I think if you feel like you're on an island or you're not sure. Right. Reach out to others. Reach out to, uh, whichever firm you're working with, reach out to other peer groups that you're a part of and just kind of see what, what their experience is, what are they looking at? And that's something that we do, ah, as a cast industry. Right. Like, I feel like we have a pretty good network of firms that we talk to on different items and topics and relevant issues that would be. My advice is lean on your network.

Speaker C: I also think that when we look at AI adoption, you look at it this, like this long, uphill battle. And I think truly, when you begin using it and you get a couple good use cases, all of a sudden you just start to adopt it much faster because you start to get the hang of it and it starts to open up your mind to all these different use cases. So just getting one or two examples in there, I think you don' to think about is, oh, it's going to take forever. Like, no, it truly catches on. I mean, we've seen that within our firm where we've adopted an AI tool and people started using it. Word starts to spread. This is how we're using it. It's super helpful. And then everybody wants to jump on. Right. So I don't think it's as overwhelming as people think once they do get started. But the other thing that I always talk about is I didn't even know how to get started with it a couple years ago, and I was like, how do I get some training on Copilot? And then I was like, why don't I ask Copilot how to get training on it? And it was so Stupid, but it was true. And so I, like, put that in there. And it gave me all these training videos and everything. And that was so easy. And so I think that is just a way to do it as well. Whatever AI tool you have available to you, just start prompting and asking, how do I learn you? How do I use you? Here's my situation. What are some use cases? Use the tool because you're training yourself in the meantime, but it will also give you ideas on how it can be utilized within your organization for your purposes.

Speaker B: I love that because that's actually what I started doing as well. It was late at night, I think, where I said, well, how can I do this? Like, um, what should I do? And also I was like, dang, why shouldn't I? I should have asked that question like six hours ago. So great answer. You know, I think that AI, it's almost like, here's what I'm gonna say. So I think that the techies branded AI in artificial intelligence to be really scary for the rest of the world. So they seem like they're experts. Right. In reality, what I think, Jennifer, you just told me indirectly is that AI and these tools, like copilot, are really no different than when we first started using Excel. It changed how we did things. It was a little scary and it was exciting at the same time. But, uh, what did we do? We jumped right in. And now we all have a love hate relationship relationship with Excel. Right. I think that we're going to get to that point with AI as well, that love hate relationship. So what is one mistake you would encourage your finance leaders to avoid when they're doing this modernization? Like, what's the big thing that you're seeing a lot where it's like, oof, duh.

Speaker A: I think from our perspective is not including others, so. Or trying to silo what you're doing. Right. Because the more people you get involved or at least make aware of what's happening, they'll bring certain topics, they'll bring certain ideas or experiences that they have to the table.

Speaker B: Anything to add, Jennifer?

Speaker C: Yeah, I was saying, I think Kyle's spot on with that because you just don't know who's going to gravitate toward it. You might have some people that you think, oh, they seem very technical, they might be great at this. This may not be their bag, to be honest. And so we have some people that have really raise their hands in our organization who I did not expect to, and they've been really good at this. And I think one of the things about it is again, if you think about people who are really techie, you think that they may be more inclined to use it. But I have found that it's more of our, uh, creative types that are very excited about it because they have the imagination to figure out the different use cases or they're not stuck in their ways and they're saying, I'm okay with changing how I work every single day and I'm open to trying something new. So people may surprise you, I think. And so keeping that as open as possible, you may feel find some really great champions that you would have overlooked before.

Speaker B: It's interesting you say that because some of the CFOs I work with that are also artists seem to be the ones that are coming up with really creative uses of this. So I think you're right on there with that. Something about that. As someone that does paint by numbers, I'm not really an artist.

Speaker C: Like how many CFO artists do you know? I know Sierra,

Speaker B: but they're really good at that. So what I'm hearing from you guys is one seek help. But I want to jump back a little because I wrote it down on my post it note, which means it's important. And Kyle, you said about reaching out, asking get part of different communities, that you guys have a whole network of firms that do this. I think that that is absolutely a key thing that I did a presentation called building your inner circle is more important in the world of AI. And I think if I were to make one recommendation, it would be guys, everyone listening, go build your inner circle. Reach out to people like Jennifer and Kyle and just ask the questions. Here's the cool thing about AI. Nobody really knows what we're doing, right? It's the wild west, it's a new frontier. And so we can ask whatever questions and nobody will judge you. So there's no stupid questions in the AI world, right? There's only possibilities. And so as we kind of look at wrapping this up, Jennifer, I'm going to start with you. What parting words would you want to give our listeners that are excited but scared of AI?

Speaker C: Well, it's the same advice that I give people on my team, which is just bite sized pieces. And again, if you're thinking about what's my total AI strategy, how is it going to impact everything that we do? How do I embed in every single process? I think you'll never get started. And so I think take a bite sized piece, figure out something that's important to you, really master that, employ all the tools that you can think about it in a different way, get help collaboration, but focus on something small and I think then you'll see it really spread and you'll have the imagination then to actually have it make a bigger impact.

Speaker B: Kyle, same question to you.

Speaker A: Yeah, I definitely think leveraging your network, leveraging your team, not operating in any silos or trying to take this all on by yourself. The more open you are, the more people will bring to the table with ideas and experiences. And I think it gets back to building that culture of uh, this is new. It's territory that a lot of us are kind of experiencing for the first time. So what have you had successes with? What do you think we should try and where do you think we can make the most impact?

Speaker B: Thank you guys for joining the FEI podcast and we'll see you next time. As we wrap up today's conversation, one thing is clear. AI is not something CFOs should try to figure out all alone. The opportunity is real, but so are the risks. AI can help finance teams move faster, reduce repetitive work, improve decision making and create more strategic capacity. But as Jennifer Witts and Kyle broke remind us, technology works best when it's supported by a strong process, thoughtful governance, secured platforms, and a culture where people are feel safe learning, experimenting and asking questions. A few takeaways that stood out to me is first, don't put AI, uh, on top of a broken process. If the process is messy, AI will only make the mess move faster. Second, start with the work the team already knows is painful, repetitive or just taking too much time. Those are often the best places to begin. Third, involve your people early AI adoption cannot happen in a silo. Your best champions may come from unexpected places, especially from team members who are curious, creative and willing to rethink how work gets done. Fourth, governance and security matter. CFOs need to ask the hard questions about the platforms, data controls and whether the firm they're going to work with truly has a a dedicated expertise to guide AI adoption responsibly. And finally, you don't have to transform everything at once. Start with a bite sized use case and learn from it. Build confidence and then expand it. For finance leaders who are excited about AI, ah, but not sure where to start. This is the moment to lean into your network, ask better questions and bring in the right experts. Firms like COHEN RESNICK Help CFOs think through strategy, process technology, governance and provide implementation support needed to modernize finance in a practical yet responsible way. The future of finance will not be built by leaders who go it alone. It will be built by leaders who are willing to collaborate, experiment, strengthen their teams, and use technology to elevate the role of finance. Finance across the business. I've had so much fun with this conversation. Jennifer and Kyle, thank you for joining me today and to our listeners. I'm Heather Cole, executive advisor and host of the FEI Podcast. We'll see you next time.

Speaker A: Your career doesn't grow in isolation. It grows in rooms, relationships, and real conversations. So here's your next move. Expand your network through the FEI network because the right connections increase your network net worth and your impact. Plug into the programs, the people and the community and keep showing up until opportunity recognizes your name.