How the Office of the CFO Is Becoming AI-Powered

One of the things that we'll probably see in the next one to two years is the people impact of AI I think is is a little bit underestimated. It's probably one of the larger technology shifts that we've ever seen. And today I'm joined by Kim Huffman, CIO of Workiva, one of the leading platforms used by the world's largest companies to manage financial reporting, sustainability reporting, audit and compliance all in one place. The re-skilling and the talent shift is something that organizations aren't thinking as much about that is probably going to be the most significant change that we're going to see in the next couple of years. What happens if it gives you too much fear of going back? Are we going to go to party work weeks or there's just going to be a lot of people looking for new gifts? We're trying to incentivize individuals to adopt it while the same time they're nervous about their job security. How is that translating into business objectives and how are we measuring that? I've never seen IT move as fast as it is right now. It's nuts. All those things that we have five year plans for, we're going to do them now. Kim, welcome to the show. Thanks Chris, great to be here. This is going to be an interesting conversation because I talk to people all the time about the regulatory and compliance side of things and even dabble into the dreaded word of ESG, which I think is really an important word, but I guess it's an acronym, right? But there's more standards now than ever before. There's more compliance, there's more regulatory frameworks and things like that. How would you describe what the world looks like today as what it was like 10 years ago? I think that world and the Office of CFO and the teams associated with that in general are. There's a lot of fragmentation, there's a lot of change, there's a lot of complexity, but there's also a lot of opportunity. I think especially when I think about using AI in the Office of the CFO and in the teams and what AI can offer those teams, I think there's a tremendous amount of opportunity for those teams to really begin to work differently. And so while it's ever changing, always complex, always being asked to do more with less, I also think it's an organization in a functional area that's right for opportunity if implemented right and done well. So talk through a little bit, you've been in the compliance space and regulatory space. I don't think people really have a good. They hear these acronyms and these terms and I don't think people really understand why or what they're doing. Why am I doing this? What's the importance of these compliance regulatory standards? Well, I think overall, there's been more and more compliance and regulatory standards that have been being asked of global organizations. It's one of the reasons why we see such great traction with our largest customers because they are increasingly facing more regulations, more compliance, more scrutiny. I think especially with sustainability coming on, now we have a fiduciary risk to think about how organizations are reporting their sustainability. And so, what does it all mean? They mean different things to every team and every country and every regulator. And I think that's part of the fragmentation and the complexity that many of the teams in the Office of the CFO are facing and many of our customers are facing. And one of our objectives as an organization is help to make complex things simple and to make the lives of the individuals in the Office of the CFO easier. And a lot of what they're trying to do is meet these regulatory compliance. I mean, you mentioned sustainability earlier or the dirty word, ESG Chris. That was a huge pivot this year for many of our customers in that they were headed down one path and then that path changed. However, if they have global operations, they still are needing to meet the European regulations and the compliance there. So, you know, when I say that what we're seeing is fragmented complexity and by the way they're being asked to do all of this and typically these are not teams that get tons of headcount or budget every cycle. So they're trying to do more and more with less and the scrutiny is increasing. The data requirements are increasing and you know, there's just there's a lot of complexity in their world. And there's a huge opportunity we think to help these teams work smarter, work better and specifically around like their most critical data. How they're using it and how they can work with their most critical data to get the most value from it. Yeah, and you mentioned that these are teams that typically don't have a lot of staff and they have a lot of data to collect. And they're dependent on other people to collect that data. So, you know, it's not like they can just go and grab all the stats off of some server that's sitting there and pull it in. I mean, they got to go to the IT group or to whoever, to sales department, whatever to kind of do that work. And so that's a complicated interaction. I imagine for those people, because you know, the people they're asking probably don't want to prioritize that in their world, but you know, they need it desperately. And you have reporting deadlines and all sorts of things like that that come into the mix that make it very complicated. You know, how is it? I know you guys are solving for some of that challenge. Can you speak a little bit to like what you do around that piece of it? Yeah, absolutely. I mean, I think one of the challenges obviously is so many disparate sources of data. As well as, you know, what we see is, you know, traditionally when we begin to work with the company, what we're trying to solve for is, you know, the disparate sources of data as well as the disparate sources of truth that may exist in an organization. And really focusing on how do we bring all of that kind of that data that matters the most to the organization together in a single platform. So that it's it's audit, auditable, it's audit ready, it's secure. And then more importantly, as of late, you know, we can apply AI to that. And AI is actually embedded into our platform at the core. So the data set that they're working with is that consistent data set. And where where we see the value there and many times CROs are sort of in a unique position at our customers because they're they're able to. You know, unite some of the disparate data that exists, whether that's in a data warehouse or potentially in where key bus specifically for the individuals on the teams of sustainability audit, financial reporting, etc. And it allows us to unlock a lot of value for those organizations. What we what we typically find is each of those organizations work work together, but really there's an immense power in bringing the data into a single platform and allowing all three of those organizations to work simultaneously and to collaborate across functions within the platform on a common data set. And if you think about specifically the sustainability area, the level of data that is needed in sustainability is much broader than what we've seen on the financial reporting side of the house because we're looking at supply chain data HR data, etc. And so we're trying to bring that all together in a single platform, ensuring that it's auditable and audit ready and secure is a challenge if you're sustainability controller or you're trying to go out and gather all this data yourself. And so we're trying to do a strategy working with the CIOs, I work closely with our CSO or CFO on our own internal data strategy of bringing all this we obviously use her own product, bringing all of this information together and what we've done for our customers is when we can partner on that data management management strategy, they're getting a tremendous amount of value. And so I think that's really interesting because we talk about single source of truth all the time, right? And I know from working with different groups of people, they all have their own kind of data. And sometimes it's presented in a way that is relevant to them and that doesn't mean it's accurate necessarily for another group or another area. And so that gets problematic. And I would imagine that having that collection of the data closer to the source of where it's generated probably gives you more accurate reading. And so what it sounds like what you're talking about is having people manage their portion of the data to keep it current and then having it all in one repot. where everybody can take advantage of that. Is that pretty accurate? Absolutely. Yeah. There's certain data or insights that we might have in the sustainability area that are very relevant to the financial reporting or vice versa. And it allows for consistent linkage. It allows for audibility. So as those teams are working with their numbers towards the end of a period or prior to a reporting cycle, they can be assured that the changes that the sustainability team might be making that are going to be reflected in a financial report or vice versa. And they're all governed with the right levels of controls in a single platform. You've got that traceability. You've got that auditability. And you've got that lineage and trackability within the platform. So you're not wondering like, why did my number change? Who's doing that? Or if a number change is and it's not reflected appropriately in another function, that's where that collaboration really starts to drive high value and that trust and confidence in what they're actually doing with the most important data that they have and their most important kind of functions that they're trying to report on. So I'll say this from people who have had to provide this data from that perspective. It used to be so deeply frustrating because it was like you get a random spreadsheet sent to you. And like, please fill out these 30 pages of spreadsheet. And it's like, but I just filled one out last week and it was like slightly different questions. So I have to like completely redo all my answers. And it was like, oh my god, like I don't have time for this every week. And like, you know, like I think I imagine having one's that single source is like really beneficial to the sort of that and reporter because they have something to start with and they don't have to reproduce it. And if you need numbers swizzle a little bit differently into the finance group, you know, you have the ability to take those numbers and work with them still too, right? Absolutely. I mean, I think too, you know, as you know, at the days of, you know, getting multiple requests for the same information from multiple people. You know, hopefully we can reduce that across organizations. That's part of our goal. Not just on the on the on the financial reporting, but also as we think about sort of internal controls, internal risks, the governance around the risks. You know, how many times are you getting asked to certify or verify something, you know, you send an email. You're like, I just got this email where to go. We trap all that and we capture all of that in the platform. So not only are we helping, you know, the reporting teams, but we're also helping in helping them feel like they have the right level of assurance through our governance risk and controls that are all tied to the financials as well. So it's all in one place. It's easy to track. It's auditable. It's it's AI. You know, we've got AI at the core. So we're driving a lot of. I would say productivity and automation through looking at what are the tasks that are are most that there's the greatest degree of opportunity to help automate for not just the financial reporting team, but also the audit teams and the sustainability teams so that they can free themselves up to actually drive strategic insights and strategic decisions instead of some of the more routine tasks that those teams corner by corner. And let's busy order have to do, which is, you know, somewhat painful. So, you know, that's really where we see that huge opportunity with our with our customers. So I think that there's a lot of misunderstanding from from folks and organizations about, you know, like what the offices of the CFO does even, you know, and like what what motivates and drives decisions there and and like what are the what are the big concerns in that office. Yes. What are you seeing these days? I mean, I think, you know, if you think about the office of the CFO and even to some extent the office of the CIO, I think the the roles of those functions have changed dramatically over the last 10 years. And I think, you know, how how can the office of the CFO or the office of the CIO really be a strategic partner to the business. And it's it's about understanding what the business strategy is and it's about ensuring that the organization is prepared and ready to be able to meet strategic objectives as well as drive strategic objectives. And I think if you think about the office of the CFO and why we see such a huge opportunity is, you know, reporting is a is a small segment of what they do. And, you know, the ability to give those organizations more time to do higher value strategic work is an unlock for the business because they can begin to serve as a strategic partner to the business on planning decisions, forecast decisions. How should we go about making investments and spending time more on forecasting predictive analytics, strategic investments, those kind of things versus working on, you know, making sure we've got all over the reporting. It's not that that's not important activities. They're absolutely important activities. We want to just make sure we're providing them the technology to help them to be efficient as possible so that they can actually focus on those higher value strategic. And so, you know, we're trying to make sure that the higher value strategic activities much like, you know, if I look at my organization CIO, you know, we are driving business strategy and driving business change. The technology organization with, you know, injecting DNA, AI into the DNA of work, we're key, right. And so part of what we look at is are there opportunities for us to take advantage of AI. I think every organization is thinking about doing that. But I think the office of the CFO specifically charged with a lot. They got a lot on their plate. And I know it would be great to free them up to spend more time on some of the high value strategic activities that we'd like them. So, you know, that's what we hope, you know, some of the benefits are customers will realize with the work of a platform. Yeah, well, and not to mention the fact that CFO has liability as do some CIOs and certain conditions as well, you know, so there's a lot of like even personal risks. That goes without saying, right. I mean, you want to make sure your numbers are right that they're it's you're working within a secure platform. They're auditable. They're validated. You've got tracking around them from, you know, source to to target. And you're able to, you know, report with confidence. That's a table stake. I think that that you would you would hope every CFO is focused on and we feel pretty strongly. And I think, you know, we've got 6500 customers that feel pretty strongly that that's that's what we're able to do. So it's it's it's it's good. So, you know, you mentioned AI a few times and obviously that that's a big strategic initiative for you guys. Could you talk a little bit about like, you know, when when you're applying AI both in your product and in your and in your, you know, company. You know, like what what are the where do you see it bringing the most value for you? So I think from a product perspective, you know, our approach has been very thoughtful and pragmatic, right. You know, we we are very aware of the important fiduciary responsibility as well as the highly regulated environment that many of our customers operate in as well as the type of data that they're working with and the type of reporting. And and basically the implications of if there's something wrong there, right. You know, we need to make sure that we've got a secure intelligent environment with which to apply AI. And so what we have been is very prescriptive about how we release AI features. We built AI into the core of our product. We did not go out and buy AI capabilities and attach them in we built it at the core. And you know, we are very, very strategic about always keeping a human in the loop. We really feel like there is an opportunity to add an incredible amount of value to the office of the CFO, whether that's in reporting, whether that's in internal audit or sustainability. And so we have focusing on activities that are routine that are, you know, high volume that are repetitive and that we want to provide the ability for those teams to leverage AI in a way that it's doing work on their behalf, but they're always in the loop and they're always validating the results. So we were intentional in how we rolled it out, you know, we started, we started with basics, we started with, hey, let's pull in some third, third party frameworks, let's pull in some third party regulations so that you can kind of make sure some of your reporting is meeting the regulation, some of the references, those kind of things. So we're all comfortable with AI, get them comfortable working with AI in our platform. And then now we've begun to roll out sort of intelligent capabilities around audit sampling around creating your, you know, your report. at how. to benchmark what you're doing with other public, publicly available information and compare maybe your sustainability report with other publicly available reports. And we have all of that being done in the platform so that you're data staying in the platform. You're not sending it off to another LLM and we're pulling the information into the platform and we're embedding AI into the processes that those individuals already use. So that they're not going out and doing it somewhere else. So it sounds like, I mean, it sounds like it's beyond just reducing the workload of sort of repetitive tasks even. It sounds like there's really a benefit here for allowing it to do some of the work that just you just don't have time to do. Like going in cross referencing against other companies and benchmarks and things like that. Do you, are you providing, like, where's that data all coming from? Is that something that you guys have like industry standards or is that something that it's going out and finding in research? So we've brought in the data into our platform and it's all publicly available. Fileings are publicly available. What we've done is built AI that goes and looks at all of that and does a comparison against what you're what you're showing that may not be publicly available. Obviously, we're not putting that out there. We don't do it compare outside. We bring it all into the platform and do those compares. And we provide insights. We say, you know, this is what in your industry, others are reporting against. This is how deep they're going and they're in their very various reporting. These are their areas they're focused on in their annual reports. I mean, all of that information is public and AI can quickly go through all of that and summarize it. And we're just providing that summary and those insights to our customers within our platform. Yeah. I mean, that's got to be very powerful. Because we talk about just sort of compliance and regulatory reporting and things like that. But I mean, you did mention like executives need this kind of information to make good decisions. Like are we utilizing our internal spend effectively? Things like that that are not necessarily related to some compliance or regulatory thing. But actually just sort of that higher value work, like you mentioned, that they want to be doing. You know, could you speak to like what you're seeing, you know, your customers, like how that's because I got to imagine that's a fairly transformative process because it's like something they just didn't have the, it wasn't feasible for them to do previously. Or they had teams of people that that's all they did. Or they had teams. Yeah. I think, you know, I mean, I think, you know, one of our customers, we had our customer conference and she spoke and she said, I can now take my lunch. You know, I haven't been able to take my lunch for four years. I can now take my lunch break and I also have gone to my manager and said, I have more time to do other things. I'd like to, you know, focus on these other things as part of my function and I didn't have time to do that before. So it's about. That's going to improve job satisfaction. Exactly. It's about giving people time back. It's about giving organizations time back to, you know, maybe have some more work life balance than those teams typically see or having a lunch every once in a while is a good thing. Or, you know, to take on different types of work. And so I do think, you know, one of the things that we'll probably see, you know, in the next, you know, two, one to two years is there will be an or like the people impact of AI, I think, is is a little bit underestimated to some extent in that jobs are going to change. I mean, I know there's a lot of concern over, you know, job security and job loss. But I do think there will be a shift, you know, it's probably one of the larger technology shifts of our that we've ever seen. And, you know, how are we organizationly set up to begin to articulate what someone's role looks like in, you know, when they're using AI or when they are managing teams of people that are agents instead of people. Right. And what is that going to look like? And, you know, I think the re-skilling and the talent, the talent shift is, you know, something that, you know, organizations aren't thinking as much about that is probably going to be the most significant change that we're going to see in the next couple of years. It'll be interesting to see how business reacts to this because you do mention it's like it's going to give you some of your time back, right? But then there's a question of what happens if it gives you too much of your time back, you know, because I mean, you know, like, are we going to go to four day work weeks or or is that there's just going to be a lot of people, you know, looking for new gigs? Yeah. I mean, I think we're in between this, you know, you know, and that's I think what's also, you know, there's a lot of organizational change management thoughts around AI that are, you know, you're trying to roll out something and you have, I call it FOMO where you're, if you don't do it, you're like, should I be working with this AI thing and then FOMO, which is, I'm kind of worried about like losing my job and becoming obsolete. So I'm like trapped between these two states and, you know, we're trying to incentivize individuals to adopt it while the same time they're nervous about their job security. I mean, internally, the way that we've thought about it is we have thought about it as bringing additional capacity to the organization, not reducing hours and reducing people. Yeah. Which is great for a growing organization. Yeah. And the reality has been, yes, we've seen capacity, you know, we've seen increased capacity. I think the next question is what are individuals doing with that increased capacity is where, you know, that's, I think, what we're starting to kind of tease out is are people taking on new responsibilities are, you know, in go to market, are we seeing, you know, increased, increased, you know, bookings, increased revenue. How is that translating into, you know, business objectives and how are we measuring that? I think that's what a lot of CIOs and organizations are struggling with right now. Well, so on that, like, what are you seeing? I mean, are, is that top-lying piece of it like happening or is it like still too early to tell? Is it too hard to figure out? I go to all kinds of, you know, events and symposiums and I don't think there's a mouse trap that anyone has found that is working yet. I mean, this is the conversation, the conversation, Dejure, in a lot of our, in a lot of our meetings. You know, how are you measuring this? And I think there's various schools of thought. I mean, we've got, you know, overall measurements of how much capacity are we actually giving back to the organization through the use of AI and then functionally, you know, where we've got, you know, use cases that are focused on, you know, engineers, you know, we're looking at coding, coding efficiency, coding productivity, engineering productivity, go to market, you know, are, how are we developing assistance for our go-to-market organization and then how much time are they saving and meeting prep or follow up or notes and all of those things. And, you know, it's still something, I think, organizations are trying to figure out and it's similar to when we came out, you know, with any new technology, right? How are we measuring ROI around it, right? Right. It's not always easy. It's not always easy, you know. Yeah. Yeah. Well, you know, I think that, you mentioned that it's giving you a lot of extra capacity, but I think the other thing about, the other angle of that is it's increasing the speed of business, too. And I think that's a really interesting piece that's very compelling because, you know, not only can you iterate faster, which means that you can, you know, sort of resolve issues faster and get to the, that final, you know, product faster, but, you know, there's changes that are happening now. I have never seen IT move as fast as it is right now. It's nuts. And like, you have to be so on top of it to keep up with the way things are changing, to take advantage of those changes. You know, I'm going back to now like the office of, you know, the executive suite there. And, you know, the ability to make decisions is, it's becoming, you know, it's becoming very bogged down in the amount of time it takes to, you know, collect all that data and things like that. And what I'm saying is that something like what workiva is doing is giving, you know, the executive suite that kind of insight to not just, you know, like report, but to probably move faster, too. I mean, is, are you hearing that back from people that like, it's so important that we have this data to move faster now. Yeah, I think, I mean, I think one of the main components of, you know, a strong AI use case or strategy to generate insights is you're, where your data sits and you're, you know, is it in one place? Is it AI ready? Can we access it? What's the quality of that data, right? And so when you think about aggregating all of your most important data that drives, you know, what these teams are doing in a single platform, and you're able to lay around AI and on top of that, it's a pretty significant force multiplier. And I think the challenge a lot of organizations have, CIOs included, is, you know, as we think about, you know, broadly in the organization or AI strategy, we're realizing that the data layer and the data strategy is can either be a enabler and a multiplier if done right, or it can be a dead end. detriment and it can actually slow you down. If the data there isn't trusted and governed the right way, you might not get the results you want nor that you would expect because it goes back to your data strategy. And so where we have seen value and where we're able to bring value to our customers is where we can actually pull all that data into a single source of truth and act upon that data and provide insights on that data has been powerful for our customers. >> Well, and I think that's an interesting point because we talked years ago, we had started that conversation about the data fog. It's like there's a lot of data but not a lot of knowledge and there's not a lot of wisdom and things like that. But I mean, it is interesting because like, I do see a lot of companies nowadays, they get into a situation where they now have so much data that they are just get into this act of naval gazing. They're crippled by indecision because there's so many data points. So you do have to do a lot more than just surface the data. You have to transform that data into something that's actually actionable, right? >> Yeah, and we actually did a survey. It was interesting. We did a practitioner survey of the office of the CFO and we found that coming out of it was about AI and coming out of it was, they felt a high interest to want to use AI in their day-to-day work. Some of their concerns were around the data and the governance around the data. And that was going to be their biggest challenge, right? And so, which we looked at as a tremendous opportunity in that we can help them with that because if you think about it, and we provide a single data platform that allows them to utilize all the data and then depending on the fit for purpose need they have, they can leverage that. So, but it is something that is in the back of their minds that they're thinking about. The other thing they're thinking about and all, because I know this is IT visionaries, is I think, when I think about the office of the CFO and the office of the CIO, and really unlocking value for that CFO organization is talking about how it's important to, and this is any CIO, I think personally for me, is how can I be a business partner to all of the functional stakeholders, right? And if I think about the office of the CFO and work very closely with our CFO and our CSO, the power becomes in bringing all of that together, right? Because there's, I think that there's a data element, there's a governance element, and then there's actually the change management and the business process, right? Which is something that I think our CFO focuses well on. But then it's about enabling a CIO, helping to enable these business partners to really get to the next level. So I think that is an important partnership and a relationship to have to really, not just power business outcomes, but especially with AI and everything going on. It's even more important to have that connection there. Yeah, it's interesting you talk about that because if you think about it, the role of the CIO is actually a relatively new concept in history, right? I mean, it's maybe what, 20 years old, 15 years old, or something like that. I think the roles changed a lot in the last 10 years, right? I think with technology, it's absolutely changed the role. And I think this is probably the, it's either a heat lamp or a spotlight. I can't determine. But we got hit with COVID, go remote, and then Chatchy PT came out and it was like, go implement AI. So it never has to be so much stuff for us to focus on. For sure. It's so crazy. And I was going to say, it was relatively more modern term. And then say around 2008, when we have that, the first recession going on, there was a sense that all of a sudden, the CIO role was subordinate to the CFO role. We saw a lot of CIOs that were reporting into the CFO. And that sort of changed the nature of how technology worked in businesses. And then to your point, things, the world changed again, kind of dramatically. And all of a sudden, technology, every business became a technology company. And then you had, then you roll into the COVID and like, oh my gosh, we had a rapidly transform. We have about three months to completely, all those things that we have five year plans for, we're going to do them now. - Over night. - Go. - Over night. - And it was just, it was wildly unrealistic in a lot of ways. - Yeah. - But surprising in the fact that I think a lot of CIOs actually stepped up to that role and like, pulled off like literal miracles from what I saw in those times. So, and then you mentioned like, now we've got the AI thing going on. - AI data security. I mean, it just, you know, it doesn't, it doesn't, it doesn't. - Security is another big one. - Yeah, I know. It's a, I mean, do you, what, how it almost seems like the role of the CIO is getting to be too much for one person in some regards. You know, there's so much going on. I mean, from like, you know, I know we've got CISOs and CTOs and you know, like people to kind of divide it out. But I've even seen some areas where like, you know, these functions are in a larger company being broken out along lines of business and things like that too, because there's tremendous complexity this job. - There's tremendous complexity in, you know, I think the one thing too is there's not, they're not all like similar functional remits. You know, if you think about data, you think about business systems, you think about security, you know, they're different functional remits. I mean, there's, there's different teams, different mentalities of teams, different mindsets of teams, working under the, the CIO. I think, you know, with AI specifically though, I mean, you know, the, the AI, the remit of AI is, it's a team sport. I mean, there's nothing that a CIO can do without full sponsorship and partnership at the functional levels at the exact level. And that's really true of, I think, many of the things that, you know, we're trying to do from a strategic perspective. But yeah, I mean, there's a lot of organizations that are depending on the size, they're breaking out the, you know, they've got the CDIOs, they've got the chief AI officers, they've got CSOs and they're breaking them out. Because the remit is large and I think it's really dependent on the nature of the company, the team, global responsibilities. I have ADD, so it's perfect for me. I like to do multiple, where multiple hats. But, you know, it has been a busy five years, I would say. Yeah, and there's no sign of it slowing, right? I mean, what? No, but this is exciting. I mean, this is, this, A.I. will be, like, we'll be, we will look back on this and it will be the biggest, you know, I think one of the biggest transformation moments. And organizationally, we'll look back and we'll identify what it is. We'll just scratch the surface. Hopefully I'll be rich. Yeah. What's retirement? I don't, I don't, I don't get to do that. No, but I, I think it, it speaks, I mean, like, where do you see that? Like, I mean, like, where do you, like the role of the CIO? You know, like, like you said, it's been changed so much in five years. What do you think the next five years is going to bring? Well, I mean, I think, you know, one of the things that I think we've seen with, with A.I. is, it's the first time that we've democratized a technology, or a technology has been introduced to individuals in an organization. At home, prior to it being introduced at work, and you can use the same technology at home, and you can use at work. No other technology has, I mean, there was the difference between B2B and B2C, you know, software, but they were different. You know, you don't have a sales horse type software that you're using at home, not true with, with the A.I. and chat GPT. It's the first time we've seen this phenomenon occur, and I think what it is doing is it's bringing technical capabilities closer to the business. And so I think when you think about the role of, you know, your business applications or your corporate, you know, applications team, it's going to change dramatically where, it's probably going to be more of a center of excellence for capabilities that are then utilized by the business that are able to much like you think about onboarding a new employee, you would onboard a new agent with new capabilities. That's where I think it's going to go. So I think it's about enabling the organization to utilize this technology more so than we've seen previously. Right. I think with SAS, there was always like, well, you can configure your own reports and you can do some configuration here. But this is true. Like we're going to democratize these capabilities out to functional people and to individuals so they can develop their own assistance, which we haven't done before in an organization. How how do you do that? does the technology organization or the business technology organization create a framework, create a services type offering to enable that in a workplace, to work for each individual employee. Like, that to me is the vision of where we're going to probably go, which is kind of exciting and fun and, you know, we're not there yet, but those are the things I think about, right? You know, I wanted to assist and I need someone to help me do my meeting prep. Well, let me pull this up and leverage it. But we got to make sure it's safe, it's secure because it's in the enterprise environment. So I think it's going to be a focus less on, you know, the building out a lot of different processes and more about enabling the capabilities that are then kind of like, you know, I'm creating my own employee or my assistant that can do things for me in my role. And I need them to do these, you know, kind of jobs to be done. I'm going to bring this group together or these group of agents together to get these jobs to be done. And it's they have a catalog of capabilities, right? That's where I see it going, probably. I mean, that's like, you know, two or, you know, I don't know how far away it is, but that's kind of where I see it going. Yeah, I mean, you think, oh, that's like five years away, but maybe it's like three months away, the way everything's going. Well, I mean, but that's an interesting idea because like if you think about it, you know, like maybe you've got 100, 100 employees in your organization that you're, you know, kind of keep it track of. And then all of them have employees. And now suddenly you went from 100 to 100,000, you know, with all these agents, you know, like, like, you know, managing to that is one of them, you know, yeah. But then then I then I wonder like, where should who owns who at the end of the day should own those agents? Like is that something that like are people, you know, it's sort of the BYOD kind of conversation? Like are these are, you know, like are people going to be like, well, I have all these agents in my personal life that I use and leverage and should I bring those into the workplace? And then how do you vet those? And then like, or, but then you to restrict it. And then that's like sort of that. I mean, the one analog I could kind of think to that was sort of that, that dichotomy between, you know, like private and business is sort of like when, when the internet started getting really big and everybody like the companies had T1s, which were relatively slow to some of the broadband offerings and they're like, I got faster internet at home, you know, you know, I mean, is it going to be like that where like everybody's like, but I got better agents at home and I, you know, like, I'm not going to use your agents. I want to use my agents and then like every see how you talk to saw that is like, I want to use chat, you see, I use it at home. Why can't I use it here? Right. It's like you're using the free version and you're sending your data to God knows who and you can't do that in a corporate environment. So, you know, I think we've worked, I think most, most organizations have worked through that nuance and we now people are aware of like, you know, how, how these, you know, part of it is the literacy that you focus on as far as the AI program awareness literacy, how, where the data is going, you know, there was a lot of that early on. And I think people are cognizant of that now and realize like, I can use this at home, why can't I use it here? Because the data is different, but yeah, you know, they, they, they have a home version of something and it's the latest and greatest and they don't understand why we haven't rolled it out internally and we've got it. Why does it take so long to vet things internally when I can use it on my home computer? So that's a, you know, that's another interesting challenge. Peace out. What an interesting and that sounds a lot like compliance too. You know, it's like, I can do these things at home. Why can't I do my work? It's like that doesn't fit in with our compliance today. You know, and that's, and I think that's one of the things, you know, when we get back to that like the whole like, you know, I got to do all this reporting for compliance and things like that. I mean, like, it is actually designed to slow you down a bit because like you do have to like spend time vetting things. So you know, in our personal lives, we, you know, gauge risk very differently than what, what risk to a corporation is, you know, potentially. And sometimes people just do need to slow down a little bit and think through what the implications of what they're trying to do are. You know, so maybe there's going to be, you know, like these more, you know, rigid AI, you know, I know there's going to be more rigid AI compliance and regulatory standards that are going to come up. And what those are going to be, you know, who knows? Yeah. And I mean, I think they're already, they're already are. I mean, and just, you know, similar to GDPR and privacy, I mean, there's, there's different ones in the, you know, that the EU is trying about than the US and, you know, there's, you know, the, the NIST and the, you know, ISO and around cyber. And, I mean, I think overall, you know, the general like regulatory climate around cyber and that whole area is we're probably going to see a lot more there just with the predominance and proliferation of some of the recent attacks and, you know, threats that are out there. I think, you know, knock on wood will get our arms around it. But I mean, they're using AI now in that. And so it's, it's become very interesting. Yeah. I mean, and, you know, anthropic just, you know, release that report on how, how they had a basically fully autonomous system that was just running attacks. So that's coming. Yeah. So yeah, there's that, right? That sounds like that. There's that. That's going to be awesome. But, but I think that's, like, I think that's just the tip of the iceberg because like, you know, we keep going back to this. Everything's moving so fast. And then like that, like, you know, you have to slow down to make sure you're doing things right. And, and those two things are very much at odds right now. And so I got to imagine a ton of stuff is slipping through the cracks right now. And, you know, like, there's going to have to be necessarily a lot of, you know, analysis of what we've built and what we've done. And, and like really piecing through all of that to like really understand, you know, where we sit with all of that, right? Yeah. And I think, you know, I mean, we talked about like, you know, it's providing more time for the organization to do other things, right? Like, if I think about our internal audit teams, right? I mean, they are going to need a lot more time to do these kinds of analysis and these kinds of special projects to look at some of these things that companies, rather than, you know, doing sampling and testing and, you know, those kind of things that they've just naturally done. I think the types of things that and the activities that those functions are going to be doing are going to change and there's going to be a need for them to do other things. So I think across the board, you're going to see that. So. Well, yeah, maybe, maybe it's, you know, like all, like you said, all this free time that we're getting back to those people aren't going to get to spend more time with their family. They're now going to have to learn how to do security work and analyze everything. Well, I mean, we hope that they get some time. We hope that we contribute a little bit to the work like balance of our customers and the teams that our customers. Yeah, maybe AI will create enough problems for itself that we have a whole new industry that's going to spawn up jobs for, you know, everyone in making sure it's safe. Well, that's, that's a, that's an interesting twist on the whole thing. Makes you more confused about what's going on. So I got to imagine this is like all great signs for, you know, workiva going into the future. Yeah. I think, you know, complexity, you know, making, you know, simplifying complex things, helping our customers be more efficient to drive greater value, you know, and certainly with what we're looking at with, you know, the data and AI and engaging in that story and helping them be as effective and productive as possible. There's a huge, there's a huge opportunity. And, you know, we've got high customer sat, so we want to continue to keep that bar high with all of our cut, you know, so we want to keep that bar high and make sure we're continuing to delight our customers. So that's awesome. That's awesome. Well, I, you know, thanks so much for for being on and sharing all your, your wisdom and and. Yeah. No, this has been a great conversation. Like when, when like the, the realities of the world kind of collide with the, you know, the business and the business has to react quickly. And if they do, it's a strategic advantage. And I think that's kind of what you're, you guys are helping to bring, bring to the market. And I think that's very cool. And if they want to find you guys, where should they go? We're keva.com. We're keva.com. Yes. That's had there right now. Right. Okay. I appreciate it. Great. Chris, thanks so much. Take care.