HR Happy Hour Podcast: Revolutionizing HR Tech With AI

Steve Boese: Welcome back to the HR Happy Hour podcast. Trish, this is the longest running and top downloaded HR podcast for 15 years. Can you believe that, by the way?

Trish Steed: I can't, but this has been a fun year of celebrating that.

Boese: I started it when I was 9 or 10.

Steed: Yeah, I was probably 5 maybe.

Boese: But I'm happy to be here today. Whether you're a longtime listener or tuning in for the first time, thank you for joining us. And be sure to hit the subscribe button. Stay connected with us. We're celebrating all year long, which we're super excited about. As I said, I'm Steve Boese. I'm joined by Trish Steed. Trish, we are in a wonderful place today. How about you explain to our listeners where we're at today?

Steed: Yes. So we are here at Workday Rising in beautiful Las Vegas, where it's about 100,000 degrees outside, but we are indoors in one of the most beautiful podcast setups I think we've ever recorded in, right? We're on the Workday bus, right, for rock stars. And it's been a good experience so far. So we're excited to be here.

Boese: Yeah, it's been fantastic. This is probably the coolest little venue we've ever had to record a podcast I'm pretty sure. Usually I'm in my closet with the door closed and hoping the dog doesn't bark too much, but the Workday bus is fantastic. It's at Workday Rising. It's going to be rolling onto HR Tech next week as well, and we're going to be excited to do some recording there as well.  We have two wonderful guests who I think are battling a little bit of euphoria and exhaustion at the same time from what is a remarkably big, complex, and vibrant event. And they've been running around all week talking to customers, talking to analysts, and hopefully having some fun as well. Our first guest we'll welcome today is Kathy Pham. Kathy is a computer scientist and product leader with experience across industry, academia, nonprofits, venture capital, and government. She's the vice president of artificial intelligence at Workday and serves as the Workday AI ambassador. Kathy, how are you?

Kathy Pham: I'm doing great. Welcome. Thanks for having me.

Boese: Thank you. And thank you for taking some time today out of your incredibly busy schedule to be with us.

Pham: All euphoria. It's been really, really fun.

Boese: Yeah? Not exhaustion? More euphoria for you?

Pham: Yep, no exhaustion. I'm just excited.

Boese: We'll ask Dave here in a second how he evaluates his mood. Dave Wachtel is with us as well. He's the general manager for talent products at Workday. He is responsible for the overall strategy, business plan, roadmap, and execution across Workday's talent product portfolio, including recruiting, talent management, performance, learning, skills, onboarding, journeys, and the Peakon Employee Voice product. Dave, welcome to the show.

Dave Wachtel: Hey, thanks so much.

Boese: Euphoria or exhaustion, Dave?

Wachtel: A mix of both, but definitely trending more towards euphoria. Rising is a really good conference for us. We get to meet with a lot of customers, learn a lot of things. It's a lot of fun.

Boese: Remarkably large conference, growing. I've heard numbers ranging from a few thousand to hundreds of thousands, and I believe it. The crowds filing in and out of the keynote sessions were amazing, and just wonderful event. And I hope folks who, if they're not here, they've caught some of it maybe online and streamed or caught some of the recaps online. But it's been a remarkable event and we're happy to have been here. And of course, at an HR tech event of any kind in 2024, right, a good part of the conversations we've had and will continue to have are around AI. And that's part of what we wanted to talk to you today. Certainly Kathy is the AI ambassador for Workday. We thought we'd ask you first. Where are we at with AI and HR? It's there. It's happening. You guys are developing wonderful products. But where are we at in terms of the maturity of products, people using them, reticence? I'd just love maybe— just give us a little overview of the state of AI in HR tech from your perspective.

Pham: Yeah. So I've got to talk about this all week with our 18,000-person attendees. So that's the number. And 30,000 total attendees being [crosstalk] virtual. And we're at with AI in HR— actually, it's related to also with having Dave here, who is our product person here at Workday. It's part AI, and AI by itself is a piece of technology. No matter how many big context windows you decide, or how big a context window you have, or how complicated the new models get, the value you get in any organization, especially HR, is how you take those models, figure out how to work within your organization - so with teams like David's team, with team like Katie Holden's team with Experience. She's had a phenomenal demo with something like, let's say, Workday Assistant - to bring those AI models to life in a way that really transforms how we think about recruiting, hiring, payroll, anomaly detection, and journal insights so that you don't have to wait till the end of the month to do something.

Pham: We're just at the tip because I think the last few years has really surfaced new technologies that can be used for HR. So lots of organizations have been building features, including us. And beyond features, what's next? Well, let's stitch together all these features and stitch together so many pieces in a complicated HR, financial planning, higher ed student system. Maybe even add in another partner somewhere, and the back end might be incredibly complicated, but on the front side, you just might be able to ask a question. And then you get the answer that you need. You don't need to see behind the scenes all the pieces that we do, because we know engineering, and Dave knows product, and Katie and [Buray?] know experience. We do that. And you ask us a question that might need to stitch together multiple different HR financial services and we get you what you need in whatever way you choose to ask it, however imperfect you choose to ask the question. So that's what I'm really excited about for just this tip we're at with HR.

Steed: I'm so glad that you sort of give that backstory and all of the context around that because, as an HR leader myself, in the past, that's something that I felt was missing. And one of the things that's been most impressive to me is kind of with that lens and that hat still on, is the customers that you have brought forward. In the keynote, for example, we had someone from Johnson Controls. We had someone from RaceTrac. And they were really talking about not just even in HR, but all of the other applications that are all working together and the impact and results. Could you maybe just talk a little bit about that? I know people are watching online as well, and if you haven't, hope you go back and look at it. But yeah, maybe talk a little bit about from the actual customer's perspective, how they're actually using the technology and having their employees engage with the technology.

Pham: Yeah. I'll start, and maybe I can turn it over to you too, Dave, because Dave gets a lot of the customers who dive really, really deep into the talent products as well. I think with our customers— this year, based on listening to customers, we really also doubled down on our partnerships and our platforms, and that's because we realize with AI, it's helpful for us to ideate what we want to do. And if we sit down with a Johnson Controller— I just interviewed Lo Stomski, who's the SVP and head of talent for Walmart— 2.1 million associates and employees. The kind of insights they can give back to us— we're like, "Oh, here's a job description. Here's Skills Cloud, which we've been doing for 10 or so years." And they're like, "Let me tell you about what Skills looks like for us at Walmart with our 2.1 million people as we figure out how to place one person who is so talented and do something totally different for them." So part of it is we release products and features, and our customers implement some of that. And they also give us feedback that help us figure out, "Oh, maybe we can connect this feature with this process, and just have you skip a couple of parts," right? And that's where some of— we'll dive into the agent's part in a bit, but that's where when you saw something like, let's say, the recruiter agent, it's like, "Well, what if you can just start with putting out a job description, but then tie that to notifying the manager, and tie that to something else, and getting feedback from our customers to really understand the processes that they need, helps us figure out what to build. But I would love your perspective.

Wachtel: Yeah, absolutely.

Boese: Yeah, I'd love for Dave to chime in here because I know as a leader of the talent products, you are working with existing customers and potential customers around some of these things.

Pham: Yeah.

Wachtel: Yeah, of course.

Boese: I love that perspective.

Wachtel: Yeah, and absolutely. And one of the themes that you might have heard from the conversations with Johnson Controls on RaceTrac is the connectedness, is what they're able to do through having all those capabilities in the same place, both from a data management perspective, and also the sorts of workflows and capabilities they can unlock. Johnson Controls talked all about our Peakon Voice to the Employee product, where they're gaining insights about the sentiment and engagement levels of their workers, and then using that to shape talent strategy over in our talent optimization products, for example. Things like our Career Hub are powered by skills and AI. You can start recommending gigs and recommending flex work and jobs and all based on skills. We see customers who are able to put those components together and roll them out, which we are trying to make easier, and we think we've made pretty easy. But start seeing the value of where HR is adding value not just to the business, but adding value actually down into the workers and down into the managers to help them do their jobs better.

Steed: Yeah. I'm glad you mentioned the workflows because one of the things I was taking away was that it really impacts the culture. And sometimes in HR, we don't always know what the— maybe it is productivity increases or efficiencies, but there's also that really human component of changing a culture. Could you maybe talk a little bit about some of your clients and how they're working with you to help mold and shape their culture of the future?

Wachtel: Yeah, I think, I mean, HR now more than ever and HR technology has this opportunity to do that. We work with our customers. What they ultimately want to do is create more opportunities for their leaders, for their employees. And again, by pulling it together, we're able to do that in a way that I think before some of these limitations in technology and before AI and LLMs and all the other models had made it, we didn't have as many options. I think something to also think about in the context of AI— yes, you hear a lot about AI at conferences like Rising and everywhere in HR, but as somebody on the application side, HR is— we are looking at AI as another tool in our tool belt. And I think sometimes we get caught up in thinking about AI as this destination we're all going to. We're going to land there one day, and we're just going to be on this AI island, and I don't think that's it. I think AI is another tool for us. We had Skills over the last few years, and we did a lot with that. We had Big Data before that. We had Mobile before that. We will continue as application teams to continue to leverage the great technology that Kathy and our ML teams are building and then use those as another how, like helping solve the same business problems.

Pham: I'd love to add to that because as someone with AI in my title, I'm very excited for the moment when it's— we're just a tool, a very advanced tool. The whole computer science field is abuzz, right? Because we have capabilities now where we can say, "Oh, there's that backlog of all those HR wishlists. Oh, maybe we can use this new thing." But we're still just a tool, and I'm excited for the moment, where we have the product and experience capabilities and know-how to figure out how to use those tools. A few years ago, I was a fellow at the MIT Media Lab, and we had put out— we started a project for fun to turn the concept of humans on the loop around because humans on loop is this term of where are humans involved. But that concept means that you build a system, and you figure out where humans fit into your tech system. But it's really AI in the loop, which leads to what David said, where you have these deeply human systems. We want to build systems to help us all be better at work, to connect with each other, to grow, to support our families with our payroll. AI has some part in that, yes. But you follow first with the problems that you have to solve for. And I'm actually really proud of the partnerships we have across our teams to figure that out.

Steed: You're very lucky because you do have such a wide range of expertise here at Workday. One of the things that I have not heard much about though, and you kind of just maybe touched on it, is there might be some hesitation if people are thinking about AI— I mean, Dave, if they're thinking about it as a destination, they're not thinking of it as a tool, right? You're saying you'd like that day to come. What would you say if I'm an HR leader, or just a business leader, maybe, who's wanting to learn more and understand more about artificial intelligence and the impact it can have? What are some of the hesitations you're hearing, or maybe the misconceptions? And I'll throw that to both of you. Maybe you first, Kathy.

Pham: Yeah, I can start. I honestly think one of the hesitation just has stemmed from the hype. So when you're in a hype cycle, you get a lot of pressure, and especially for, I think, if you're kind of in the middle part of leadership, right? You get the pressure from employees that are like, "In my personal life, I was able to type in, 'I want to plan a trip across three generations with kids these age, with these dietary restrictions, and I got back this really interesting itinerary to start.' How come when I go to work, I'm still clicking things?" So you get that. And then from the top down, it's like, "Go find value for AI and HR." You're like, "What? Where? How? Which vendors? Help." So I think one of it is that. And I actually think there's actually quite a few good content. And I'll add, we just published an AI masterclass where each of our leaders went through topics about AI, from Experience, to Aashna on Dave's team has one about talent. I did one in the evolution of AI. Kelly Trindel did one in responsible AI. And it's not Workday product-focused. We might have an example that might be, "Well, this is how we do it here," but there's no product pitches. It's just to explain what AI is like in fields. We're not unique. There's quite a few videos and content at this point.

Pham: And I think that's one benefit, actually, of the hype. Lots of groups have produced— you have to find the right one, but lots of groups have produced and I would, one, do that. But I think another one might be— and I'm a big proponent of this, and this might be my academic brain, but to find communities where maybe a couple of other HR folks that you get together where you're just in a little community together and you're like, "What are you seeing? What are you seeing? What are you reading?" And the power of that, at least right now, to just wade through some of the hype can be really powerful just to demystify it a little bit and help us understand how we can actually use it. Dave?

Wachtel: Yeah. I would just add in that you also don't have to— you don't have to bite it all off at once. I mean, the industry's moving really fast. There's a lot of innovation, a lot of content, a lot of things you could do. I think I actually— I think back on how Skills has evolved and organizations trying to be Skills-based organizations over the course of the last two to three years, and I think it actually shares some similarities. Two, three years ago, I think people were saying Skills is this thing everyone's going to do, and there are still lots of conversations about that. But a lot of the customers that we've seen be successful in rolling out things like Skills are people who didn't try to tackle all of it at once, everywhere, all the time, in every possible workflow, but instead said, "Hey, here's a business problem we need to solve. We're having trouble hiring in these locations. Maybe we can use Skills to expand our pool," or, "Hey, we've got this static set of talent over in this part of the organization and we need to try to find opportunities for them, or we've got a regrettable attrition problem over here." As soon as the businesses started thinking through which problems they want to solve, which are— by the way, they're not new problems. They're the same problems they've always had. It's then trying to pick where we think, where they think it makes sense to try to deploy some of these solutions, some of the capabilities we're building, some of the agents that we're working on. And again, I think, especially for HR leaders, that's how they're going to continue to get the buy-in and support from the business counterparts, is when they can deliver results. I don't think they're going to win awards for just deploying AI things. Maybe in the short term, perhaps, but over time, for the business to continue to invest and to continue to innovate and grow. I think it really comes back to having a clear point of view on the problems you're trying to solve and the opportunities, and then figuring out where of the capabilities that we're enabling makes sense.

Pham: You made me think of an anecdote that I'll reshare here from one of the leaders in one of our councils where they— like, "How'd you get buy-in?" And they said, "Today's point, we try small." But you don't try small by trying one feature or that. You try the whole capabilities. For example, let's say you're in a hospital system. There's lots of high-risk. What if you try some AI scheduling system to schedule maybe your cafeteria staff? You're using the whole capability. And then you're like, "Oh, that worked out pretty well. All right, now I'm going to schedule my surgeons."

Boese: Yeah. Don't start with the surgeons, right, I think your point, Kathy. Right?

Pham: Because you don't want to mess up over here, but if you do, you can probably mitigate it and fix it. You mess up over here, lives might be at stake. But in both scenarios, you're using the whole system. You're just using it in a much less risk— it's smaller, if you will, kind of way, and that might be an interesting way to think about how to implement.

Steed: Well, I like that you both made it seem like it's very accessible. because I think sometimes when you're sitting in the HR chair, you feel like, "I don't even know where to begin. Maybe my question or problem or issue is too small to take to a vendor. I don't want to look silly. I don't want to look uninformed." And you both made it sound like, "No, that's what we're here for. Come to us with those questions." They don't have to come to you with a fully-formed plan of how they hope to address all of their employment needs. Right? That's what you all are there for, is to really help them sort through and figure out those places. And I liked your example of figuring out how to use the entire system in a smaller way. And one of the things that used to annoy me was hearing about, like, "Go after the low-hanging fruit." I don't think that's it at all. So I loved your example because you're saying, "No, take something that's really important, but do it in such a way that you can actually make some changes or experiment with it a little bit," which I know is one of the things we want to talk about, is experimentation when it comes to HR, which is super exciting.

Boese: Yeah. Certainly, we have talked for a while about agility. Organizations need to be more agile, adaptable. Some of it is the fallout from the pandemic when the whole business world, and the whole world, honestly, was turned 180 degrees around. And so we were thinking about, "Boy, how do these technologies help organizations become more agile, allow them the ability to experiment, Kathy, as you said, maybe with pilot programs, etc.?" I mean, Dave, maybe I'll throw it to you. What are some of the ways on the talent side, right, with hiring or development, succession planning, etc., that some of these new tools, whether they're AI tools or just other tools that you guys are developing, are helping customers and helping organizations just react a little bit more quickly to changing market conditions, changing labor markets, etc.? What are some things that stand out for you in the last couple of years?

Wachtel: Yeah. Yes, I mean, there's a number of things that— I mean, obviously the pandemic changed the way that a lot of organizations think about managing their people, managing through challenges. I mean, one of the things that we did—really accelerated a couple years ago——was the investment in Extend and Partners because we knew that there were a lot of things that customers would need that we weren't going to be able to build at the pace that they needed them. A really good example, the one we go back to over and over again, is things like vaccine management, where we had a plan to build something along those lines, but through our Extend, our open platform for customers to build out capabilities, they're able to do more of that on their own more quickly. And here at Rising, we talked about Built on Workday, which now enables partners to build solutions within Workday that will help meet some of those needs. But within our own product set, the one that really stands out to me are some of our capabilities like Career Hub, where customers can roll that out piecemeal and incremental to parts of the business where they have potentially issues with managers not knowing how to coach and develop their team or employees who are looking for more. And we see real value in it. We know that when we looked at numbers from customers before they turned on Career Hub and after, we saw an increase of 138% in internal applications to jobs.

Wachtel: So if you had a internal mobility challenge or you weren't getting enough activity for some of your internal workers, things like Career Hub, which you can roll out in pieces and see if it works in some areas and maybe better in some areas than others, those are absolutely options. Another place that we do that is with Peakon Voice of the Employee product, where you can roll that out to bits and pieces. A lot of companies are still doing annual engagement surveys, but oh my God, how much changes in a year. Right? Especially in these last couple of years. And so being able to do employee listening and engagement quarterly, monthly. We at Workday do it weekly. We do engagement surveys at the end of each week, and the Peakon Employee Voice product is using AI at its core to understand key trends, key insights, recommend key drivers that managers can pay attention to. And now, as we announced here, we talked about comment summarization. So if you're part of a big team— which I lead a pretty big team, and a very vocal team. We get a lot of comments, and now with comment summarization, that fits into the accelerate phase of the types of ways that we're thinking about AI, but I can now go in and very quickly, in a few seconds, just see the general sentiment.

Boese: Yeah. So instead of taking two weeks for some other data analyst to compile the results of your quarterly, or maybe even annual engagement survey, and provide feedback to managers, you guys can do it almost in real time.

Wachtel: I mean, it is real time. I mean, it is real time because it's all built into the product.

Boese: And customers can as well.

Wachtel: Customers can as well, and customers do. And we think that that's— to go back to the question about how they can roll these out, that's one of the ways that— it's generally pretty easy. Once you get the change management and process in place and you're aligned with the business, if that's something you want to do, technology enables that now. We couldn't do that without the AI underlying it, but people weren't asking us for AI solutions. What people were asking us for was a better way to understand the sentiment and the movement and the trends of what was happening in their employee population. And so they didn't come to us and say, "Give us more AI." They said, "We need to understand our employees," and we built that solution.

Boese: Yeah. And that's really the key, Dave, of how these technologies are going to become a little bit more impactful. Right? Because we'll stop talking about them. Because we talked about cloud for a long time. Right? When Workday came on the scene, we talked about cloud and softwares and service. And we talked about mobile for quite a while as well. Right? And we talked about big data for a while. Right? And people analytics. Right? And we talked about tech. And we're talking about AI now. We're talking a lot about tech. Not as much yet about outcomes, solutions, and improving people's lives, improving organization performance.

Steed: But I think in Dave's—

Boese: We're getting there.

Steed: —example—

Boese: We're getting there.

Wachtel: We're starting. I mean, I think Athena Karp, who is the founder and CEO of HiredScore, she only talks about outcomes, and I think she's bringing a lot of that to Workday. She talks about iconic outcomes, is her word, and you're starting to hear that more at Workday now. You're hearing teams talk about delivering iconic outcomes, like the 25% increase in recruiter efficiency that customers see when they turn on HiredScore in our AI recruiter coach. I think customers now, businesses now are making the transition into, "What's the value I'm getting out of this?" And I think it's a mistake to think about it just being efficiency. It's very easy for us to put it in the bucket of it's about efficiency. That may be the case for the next 6 to 18 months, and will always be there, but businesses expect more than that. Businesses expect better outcomes.

Steed: Well, you want your HR leaders to be empowered to have those conversations because I feel like even as little as 5 to 10 years ago, if you go in— if I went into my CEO with my CFO and the entire C-suite, and I couldn't have made any of those examples you just gave— I couldn't have had that information at my fingertips. Now, if I can, right before my meeting, figure out what is a sentiment of a certain department, a division, my team, whatever, and go in with recommendations that, "Oh, and now I have data to back that up," I'm now empowered. And that's what was missing, I think, even just a few years ago. So I feel like the examples that your customers you've had on stage that we've had the opportunity to hear from, that's my takeaway, is that they're showing real results and getting things done— getting business done, and it's not about just AI, kind of to your earlier point.

Pham: There's a thread with both what you said with results and also what you said with we're not talking about AI anymore. And Athena, I'll channel you here again. I do this all the time with Athena. She's so brilliant. And the AI you can't see, you don't see, or you don't want to see. I've worked on search mail technologies in the past, and a number of times you question if your search results, like "What's the AI behind that?" You just get what you need. So to some extent, there's some AI software you want to know that it's AI. Maybe you're generating comments or summaries of your Peakon data. You're like, "Oh, this is generated by AI. We should know that as an organization." But there might be other experience where it just works. It feels better. You're like, "Oh, I feel so good with this result because it's the AI you feel, but you don't see." And it'll be interesting to see that move. I think we need both. There are times for transparency and explainability reasons you want to know something was generated by AI for sure. And for other times, no, it's back of the house toolbox stuff. Right? You shouldn't be like, "Hi, I'm AI," all the time. I mean, you shouldn't have to see that as a user all the time.

Wachtel: Yeah. I think I've heard Athena say multiple times, "The new UI is no UI," is the language that we've heard.

Boese: Yeah. And it's so funny because a few years ago when Amazon Alexa sort of emerged as a thing, and Siri has been around for a little while, we thought, "Oh, it's just going to be that conversational user experience." You would just sit down at your desk— or not even at your desk, just at home or whenever, and just start interrogating your systems, "Oh, show me the list of the best performers in this office because I'm about to visit that and I want to make sure I know who I should speak to, etc., etc." And we're getting there finally though, and maybe it'll be Voice or maybe it'll be other mechanisms, but the fact that these tools are evolving to just become flow of work tools. Right? Ubiquitous in our processing, and through Agents and other mechanisms going to be there to support us in what we're trying to accomplish and not things we must deal with in order to get our jobs done, which a lot of software's been.

Wachtel: Totally. And I think Voice will play a role. I think Voice missed, I think, some of the underlying capabilities that are now available to do some of those things besides setting timers and maybe [crosstalk].

Boese: I know. I talk to my Alexa every day, and it's largely the weather and the news updates.

Steed: Yeah. Can you talk about Agents a little bit though? Because we haven't really dove into that. And I know before we kind of wrap, I would love for people to understand what you're doing with that.

Wachtel: Yeah, absolutely. I can take a first pass at it, I think. Agents is really a big next step evolution that I think is going to really change how we think about things in HR and in technology, broadly. If I think back to the big steps that happened in the evolution of HR technology, maybe there was a point where we took employee records out of file cabinets and we put them in a computer. Right? And then we went through this next phase, which was, “Okay, let's put a UI in front of that computer and let's build out some workflows and some click paths and things like that.” And that's the space we lived in for a long time. And somewhere in there, we moved to cloud. But from an experience standpoint, that's what it was, and there hasn't been a lot of change. Sure, maybe there were some voice apps here and there, but it hasn't really changed. I see Agents as the third wave. It's going to be the third wave of how we interact with software where you won't have to go in and build out rules-based workflows and work cues. I mean, there may be places where that still makes sense, but with things like our Recruiter Agent, which is helping recruiters to identify where they need to create job recs, create the job recs, screen candidates, work through interview scheduling. I mean, we envision this world where the workflow with all of these steps compresses to much tighter, and the Agent's going to do that for you in a trusted way that is secure, that is managing your data. I think it's just a really exciting time.

Pham: Agent topic is my favorite thing to talk about right now. And I'll also preface that with, I don't know if we'll still call it Agents in a few weeks or months. Right?

Wachtel: That is so true.

Pham: And then if you want to really look up, there is these battles, "But that's not really computer science. It's how you define Agents." We'll put that aside. The term, I don't know. But what sticks is what Dave just talked about: that concept of you have these different systems and you bring them together, and that's completely changed our perception of how our system should work. A conversation I had recently was— and also I think what I love about Agents is that it brings to the table, "This is what technology is actually good at." And in some cases with the AI hype area, it's, "Let's just try to fit it in all these places where it's not good at." Tech is really good at taking a series of instructions and doing something with it. So in the past, for example, you can say, "Let's stitch together in a prescriptive way. I'm going to write down in my code. Do these five steps. I'm going to time it. I'll do those five steps." What AI and Natural Language models has done is, you know those five steps you had? Any user of a system can think about those five steps right now, say it to a computer system, and it can generate that prescription of those steps on the fly and give you the results right away versus us knowing what those steps are, and that has fundamentally changed our acceptance of how we interact with any system.  And I'll add, when I think back to the moment we came into the cloud as Workday— and not just the cloud, but we had a user interface there that felt a lot like the personal tools people were using. Right? So that cognitive dissonance of going to work and learning a new work tool, you kind of took that out. So right now with AI/ML, people are experiencing large language models in their personal lives with ChatGPT or something else. We come to work and you kind of expect the same thing that stitches together these processes and what you want to do, and there's an expectation there of what you should get.

Steed: And it's familiar and comfortable, right?

Wachtel: Yeah. And I'd say, just to bring it back to something you mentioned before about should customers keep engaging with their dreams and hopes. And I think that's exactly— yes, because of the reason that we built UIs and systems to mirror what other processes were was because that was what customers were telling us. And now there's all this opportunity, and the way that we're going to get there together with Workday and our customers is by continuing to hear those hopes and dreams and the use cases and the opportunities, and we can partner and work and build those things now.

Steed: Well, and before we started— before you were here, I gave him a whole list of my wishes and dreams for HR for Agents, so.

Pham: Keep them coming.

Wachtel: Yeah.

Pham: Yeah.

Steed: But no, I think that's it. I think it's the openness that both of you, but also Workday collectively, the leaders here, you obviously take into great consideration what your customers are needing and wanting, and it sounds like you view them so much as a partner and not just someone you're selling some software to. Right? This is a true partnership, so you're both learning.

Pham: And it's, for me, the honoring of the expertise. Sure, we might have the expertise on AI product experience. Y'all have the expertise on HR people and your organizations in ways that we'll never know because we're not there. Right? So we honor that expertise as partners and we figure it out together.

Boese: Yeah. The spirit of community and partnership has been overwhelming here for me. I've gone to a lot of events, a lot of conferences, and just the vibe here, the community—

Steed: It's different.

Boese: —the spirit here is quite remarkable, and it's a testament to all the work that's been— great work that's been done here over 15-odd years, 20 years now almost. And so you should be applauded for that, and everyone else on the teams. And we thank you for that. Before we started recording, Dave and Trish and I were talking about just HR software more in general, right, and how it's really pretty noble. Right? Because we're talking about things like connecting people to opportunity, improving their work lives, giving them opportunities to develop and feel included and feel rewarded, and provide for the families, Kathy, as you mentioned as well. It's a super important part of everyone's lives. And it's great to be a part of that community. It's great to partner with folks at Workday who do other things besides HR software, I know, and maybe we'll talk about that on another podcast, but to really just illuminate - to use the Workday word - to illuminate the great work you guys are doing, the care, the consideration, and the innovation. It's fantastic. So, Kathy, thank you so much. And Dave, thank you so much for taking some time out of your exhausting, euphoric schedule—

Steed: Euphoric schedule.

Boese: —to be with us today.

Pham: Yeah, absolutely.

Boese: It's been great to see you guys.

Wachtel: Yeah, thank you so much. It's great to be here.

Boese: We will put some links in the show notes to some of the Workday content, the Rising content. Kathy, we'll find, if we can, the links to some of those classes that you described.

Pham: AI Masterclass, yes.

Boese: We'll get those in the show notes as well because I think folks will want to tune into that as well.

Steed: Absolutely.

Boese: Yeah. Great, great stuff. Trish, this has been awesome. I'm so glad we were able to come here and record in this beautiful venue. We'll get some pictures posted. Hopefully some folks can watch this on YouTube as well and see some of the background as well.  So we want to thank everybody for listening today. Make sure to subscribe, tell a friend. Hrhappyhour.net. The network has new episodes coming out, usually a couple every single week. Workplace news, diversity, inclusion, Gen Z, HR tech, plenty, plenty more. Thanks everybody for joining us. My name is Steve Boese. This has been the HR Happy Hour Show. We'll see you next time, and bye for now.