Workiva Amplify 2026 | Building the AI Native Enterprise

Clips
More from Workiva Amplify 2026

Kim Huffman

CIO

Workiva

play_circle_outline Redesigning Workflows and People Processes for AI-Powered Automated 10-Ks

play_circle_outline Strong data foundation: quality, trust, lineage, and governance

play_circle_outline Start small with low-risk, high-value pilots and scale thoughtfully

play_circle_outline CIO responsibilities: integrate AI across data, people, and technology

Info
Transcript

Building the AI Native Enterprise

Kim Huffman

CIO Workiva

In this interview from Amplify 2026, Kim Huffman, senior vice president and chief information officer at Workiva, joins theCUBE's Krista Case and Alison Kosik to discuss what it takes to build an AI-native enterprise. Huffman explains why becoming AI-native requires rethinking end-to-end business processes rather than simply automating isolated tasks. She points to Workiva's own use of its platform, including the automated 10-K, as proof that a strong, connected data foundation is essential for scaling AI safely. Huffman emphasizes that AI-driven work in the ... Read more

explore Keep Exploring

What does it look like to redesign a workflow around AI from beginning to end? add

How has the rise of AI (especially generative/agentic AI) changed the importance and role of data governance and data quality for organizations? add

How should an organization (or CIO) approach adopting and scaling AI technologies within the company? add

How should organizations integrate AI into their technology strategy to maximize business value, adoption, and transformation of data, people, and processes? add

bolt Powered by CUBE AI

Building the AI Native Enterprise

search

Alison Kosik

>> Welcome back to Workiva Amplify 2026. We're coming to you live from Las Vegas. I'm Alison Kosik alongside Krista Case, and we're about to dig into what it really means to build an AI-native enterprise and how companies can get there.

Krista Case

>> Yeah, Alison Kosik, I think it's a really important conversation because there's so much buzz around AI. That it can be difficult to determine, like you say, what's just bolt-on and not really adding value versus where there is actually some meat on the bone.

Kim Huffman

>> Oh yeah.

Alison Kosik

>> All right. Let's bring in our guest, Kim Huffman. She's the senior vice president and chief information officer at Workiva. Welcome to theCUBE, or I should say, welcome back.

Kim Huffman

>> Thank you. Thank you for having me.

Alison Kosik

>> So I'm curious to hear what's resonating for you so far with Amplify.

Kim Huffman

>> Oh, wow. There is a lot resonating from Amplify. We had an amazing keynote this morning. So I have the benefit of seeing all of the great product features firsthand prior to their announcement to our customers today and really excited about all of the capabilities that we're bringing to bear around AI for the Office of the CFO, whether that's in the financial reporting area, the sustainability area, or the governance, risk and compliance area, as well as our most recent announcement around Agent Studio and really the fact that it allows us to extend the platform of trust and that data platform that we have built has been a core strength of ours for many, many years with many of the customers. And how are we helping them leverage what AI can do to really help their teams accelerate realizing value in the work that they do on a day-to-day basis. It's all about making everyone's life easier as well as accelerating the work that the individuals in the Office of the CFO have to do. Yeah, yeah.

Krista Case

>> So yeah, I love that perspective, Kim. I know, before the cameras were rolling, you were talking about how you're customer zero, alongside your team. So great to get some fresh perspective here. I'd love to understand when you think about, you referenced the Agent Studio announcement this morning. I've also been really intrigued by the Workiva Knowledge announcement, back over the summer. When it came to Workiva adopting these tools, what were some of the bigger barriers that Workiva had to overcome in order to get them up and running? And as you're referencing, get some value out of those AI deployments, was it data silos, was it ownership?

Alison Kosik

>> Can you explain?

Kim Huffman

>> I think what AI has really done is it has allowed organizations to rethink how they do the work across the company. And when we talk about AI-native organizations, it's really talking about thinking about the business processes that individuals in a company are doing on a day-to-day basis and not just thinking about maybe how am I going to enable part of the job to be done faster. It's really about thinking holistically about the end-to-end process and the outcomes that those users are trying to achieve in their work. And how we can bring AI and the AI technology to bear, leveraging a strong data foundation to accelerate and actually drive the outcomes. And so what's really been exciting about being customer one and being able to actually see this internally is building on our capabilities as far as our usage of Workiva as a platform internally. The strong data foundation, the connected data that we have going into the Workiva platform, and then working closely with the Office of the CFO internally at Workiva and also with our clients to understand what are the outcomes that they are trying to achieve and how can we rethink how they do their work on a daily basis and how can we bring technology to bear to accelerate the work that they're doing, but also with AI, ensure that that AI work that's being done is traceable, it's defensible, and it's audit-ready, because that's really, really important in the Office of the CFO because it's the high-stakes work that they're doing.

Krista Case

>> Is that so?

Alison Kosik

>> Let's try to make this practical. I'm curious what it actually looks like to, redesign a workflow around AI from beginning to end.

Kim Huffman

>> Yes. Well, it has been an interesting journey. So I think the biggest thing is, I think when we're talking about AI, it's really talking about how people think about AI and the art of the possible, because I think people start their AI journeys at different points. And for some people it's somewhat scary, right? You have a lot going on right now in companies. There's the FOBO and FOMO, right? It's the fear of missing out. Should I be using AI in my work? And then I want to use it, but what does it mean for my job? Am I going to become obsolete? Right. And so it's how do we really work with the individuals, the people in an organization to get them comfortable around the concept of using AI and then talking about what outcomes are they trying to achieve. So many times we'll work in workshop settings where we'll get a broad group of individuals from different functions that are together talking about what outcome are we trying to achieve. So for instance, we talked today about the automated 10-K. The automated 10-K is really an amalgamation of many different functions collaborating together. And so getting them to think less about their own specific role but really what the outcome is. And then where can we leverage technology, or in this case, AI, to do some of the work on behalf of the individuals to achieve that outcome? So we've got to make sure the people are ready first for that change, then ensure we're getting the right people in the room to talk about the end-to-end process and then understanding where it makes sense or where the company is comfortable introducing AI to do certain functions of that end-to-end process and then enabling it and ensuring that throughout the process we're enabling users to input, to validate, to approve what the agentic capabilities are doing so they're comfortable with that result set.

Krista Case

>> Yeah. So Kim, in this process, you've said a couple of times about that strong data foundation, right? And I think it's from two perspectives, first, definitely we see that as a differentiator for Workiva, but looking more generally, when you think about your role as a chief information officer, right? It's obviously you're in charge of getting that metaphorical house in order.

Kim Huffman

>> Correct.

Krista Case

>> Easier said than done, right? And so one conversation we've been having, here at Amplify this week is as we start to adopt AI, does it make any existing challenges worse? Right. So if there are, so if we don't have that trusted data foundation or if perhaps we do have some processes in place that are, outdated or not working correctly, AI is only going to make that problem worse. So I guess when you're talking with your customers, how prepared do you think that they feel like they are, that they have at least kind of this data foundation in place to then be able to get what you're talking about in terms of the people and process side of things.

Kim Huffman

>> Yeah, I think it's a very valid point. And I think, AI has, I think, amplified a little bit of the importance of data quality, data trust, and data governance. I think historically people have looked at some of the, governance functions around data as potentially slowing down, the speed of how organizations want to move. But in the era of AI, I actually view governance as the ability to move faster. If you can build strong governance, you have a greater degree of trust so that you're able to trust the outputs. I think internally, it has been something that as a CIO, data governance and data quality, obviously always top of mind. I think when it— when, the agentic AI, GenAI was introduced, we see more of it. Right. And so I think organizations need to think about that governance associated with the data. They need to ensure that what data is sitting in the platform or feeding into the AI is something that they trust, that the actions that the agents are taking on that data can be traceable, can— there is lineage to source systems. It is defensible, which allows you to be more confident in the decisions you make and also move faster at the end of the day, which is really the goal.

Krista Case

>> Yeah.

Alison Kosik

>> So you think about legacy systems and complexity and all this. So for leaders who have years of legacy processes and disconnected systems, how do you keep the idea of becoming AI native from feeling just overwhelming?

Kim Huffman

>> I think it's important to be very thoughtful and pragmatic about what you want to do. I think, internally at Workiva, we've taken a very thoughtful and pragmatic approach, which is we're not going after everything on day one. We want to identify, I would say, low-risk, high-value opportunities and start small. Start your journey with some really concrete use cases and nail those. Get the organization comfortable with the concept. Get your internal data architecture and your AI architecture solid so that you can feel comfortable as you scale. Get the individuals on the teams comfortable with the change and the change that is— AI at the end of the day is a technology. It's a very powerful technology, but it's still, from a CIO perspective, it still comes down to people. It comes down to process and it comes down to data really to be successful.

Krista Case

>> And Kim, what would be some of the measures of success, that you look for when you're adopting an initiative and that you might recommend to a peer to look for as they're thinking about rolling out some of these AI initiatives? Yeah, I think—

Kim Huffman

>> I mean, I think myself and many of our counterparts right now, many companies are, they're seeing a shift, right? You know, I think out of the gate there were a lot of productivity gains that companies saw or are seeing from adopting AI. And I think where we are now is how do we move from productivity gains to what I would consider either top line or bottom line business outcomes. And the top line or bottom line business outcomes can really be around revenue growth, going after new markets, or operational efficiencies, right, where we're actually able to fundamentally transform how internal processes are working so that we can actually reallocate those individuals to do higher-value activities.

Krista Case

>> Absolutely. And so what would be some of the areas that you think, when you— I guess when you think about yourself and your team, what are some of those areas that you think your team will be focused on, increasingly over the next 12 months as you start to maybe offload a bit to AI?

Kim Huffman

>> Yeah, I think, for a technology organization, we obviously are utilizing AI to do our development, to do our configuration. So we're seeing a shift in the type of work that our technology teams are doing. It's primarily driving down time to delivery as well as increased quality. And so there's obviously productivity gains there. Where we're also seeing a lot of opportunity is in the art of the possible, in areas that we hadn't thought about actually putting capabilities into the hands of our internal teams, whether that's the go-to-market team or whether that's the customer success team, and enabling them to deliver more value to our customers and to our prospects.

Alison Kosik

>> I'm curious also what you would tell maybe a fellow CIO who believes in AI but is still stuck in the bolt-on AI phase, what would you tell them?

Kim Huffman

>> I think AI is a fundamental technology that's going to reshape the landscape of technology portfolios in every organization. And I think when you think of it as a bolt-on capability, you're probably going to get bolt-on outcomes, right? And so I think you really need to fundamentally think of it as core. And with any technology, as I said before, when I think about technology and really what gets the highest degree of value in any technology implementation is if you think about the business outcomes you're trying to achieve, the data, the people, and the process. And I think AI and successful AI implementations are going to change and transform all of those components. So starting with that strong data foundation, understanding what those business processes are, and making sure that the people are comfortable with the technology so that they use it and adopt it. And especially with Agent Studio, so they see the value of being able to build on it, you know, that they're comfortable with it.

Alison Kosik

>> Any closing thoughts?

Kim Huffman

>> No, I think the only closing thought I would have is, we've got some great sessions here. There's so much opportunity that this technology has brought to bear for the Office of the CFO, and we're so excited for our customers and our partners to be able to take advantage of it.

Alison Kosik

>> Fantastic. I think— do you have one more question? You look like you—

Krista Case

>> Oh, no, sure, Kim. I guess you were mentioning Agent Studio, right? And I just— I would love to kind of get your take on, if there are any use cases that maybe surprised you, that you found as you're working with Agent Studio. And if there's maybe any that your team is thinking about experimenting with over the next 6 to 9 months.

Kim Huffman

>> I think one of the most amazing things I think about AI in general is, if you put the technology capabilities in the hands of the day-to-day users, you are going to find use cases that you never thought possible, right? I think the biggest aha moment was how quickly the teams that were introduced to Agent Studio were able to understand it and were able to build something that was really valuable in a very short period of time. In days, they were able to get something that worked for them for their specific use case, and they were able to see immediate results. And so to me as a technologist, that's probably the most exciting aspect of it, is there's not a long ramp time to get comfortable with it. It's fairly easy to use. And I think the use cases that we're going to see across all of our customers are going to be more than we really ever could imagine, because I don't think we've ever put technology so close to the users before and allowed them to build it themselves. So that'll be exciting.

Alison Kosik

>> Well, it'll be exciting to hopefully be back here and interview those customers about what they think. And I can see on your face you're extremely excited about it. It'll be interesting to see their excitement as well. Thank you so much for stopping by theCUBE.

Kim Huffman

>> Thank you for having me.

Alison Kosik

>> And you're watching theCUBE, the leader in live tech coverage and in-depth expert analysis. We'll be right back.