Renee Mauldin

▶0:00HostWelcome to the Built by People podcast, where we share the stories and insights of the world's top HR leaders. Join us as we dive deep into the minds of HR executives, uncovering their strategies, challenges, and triumphs in shaping today's workforce. Renee, thank you so much for joining us. And as a starting question, I always love to ask if we could learn a little bit more about your career journey.

▶0:49GuestThank you so much. It's a pleasure to be here and appreciate it. There's been some amazing folks that you've had here on the pod, so excited to be a part of the discussion. I have always been as someone who's been interested in data and analytics and how that applies to people problems. I love to see people grow and transform and organizations grow. Started my career in industrial organizational psychology. My first AI assistant, if you will, or AI-like assistant, was a clunky computer in 1999 that had SPSS on it. For those of you that are statistical geeks out there, that essentially is something to measure things through. Social sciences, and how do you sort of predict. So really something that's been a passion of mine and started all the way through, uh, as at the organizations I've worked at. So always running towards hard problems, uh, like to go towards things that are gonna be hard. Only worked at founder-led companies when the founders were there. So Capital One, Google, uh, Uber, Nubank, you know, these are all very, uh, vibrant cultures due to, uh, the folks at the time where I was there leading them, which were the founders.

▶1:54HostNow, a lot of our conversation today is gonna center around AI. And I'm curious how you identify within your people team who is best positioned to drive AI initiatives across Project 44 and any initial resistance that you faced when implementing the approach that you took.

▶2:17GuestYes, definitely. And I'll answer both of those. I guess one thing I would call out is there was a lightning bolt moment for me. It was last August when we were sitting there talking about our actual platform on our business side here at Project 44. And this intense need for us to change almost overnight into being, you know, an AI-transformed platform. And with that was a moment of clarity that we absolutely need to do that on the side of our team members with, in terms of making their culture, our culture richer and ensuring that people's careers and just overall lives were enhanced by AI. So that was kind of the beginning of it. And I would say that the people team, all of us just kind of jumped into the middle of it. Whether it was enablement, our L&D team who started focusing on the business problems in our customer success area, our HR business partners that started to, you know, really evaluate where we can actually get more efficiencies and where we can actually make more robust culture, our talent acquisition side where we started to make changes on how do we use AI. So I think, you know, that was a big piece of it where we started to partner with IT. We said, let's do this together. I think the biggest resistance we we've seen is around change management. And that's where I think, you know, it becomes obvious that the people teams at organizations should be front and center in helping run the change management, the communication. How do you foster and nurture that in a way that everyone is excited about it and people are embracing it in the right ways? So it became a really tight partnership with our IT organization and just leaning in and ensuring that we were getting involved from the very beginning.

▶3:51HostCan you walk us through how you developed and implemented the AI bootcamp AI bootcamp that enables new hires to create their own AI agents. This seems really unique from my point of view, and I'd also love to understand what measurable impacts that has had on things like employee productivity and engagement.

▶4:11GuestYeah, so AI bootcamp is something we've been doing more recently. Before that, just to get into our nascency of where we started, was around AI competitions to start getting the interest in the organization. We also did things like asking people to present what they were— they're using AI at home. I had someone talk about how he's using iPhone Shortcuts to be a better husband and all kinds of things. So that was kind of the beginning of where we were with the ideas, and we started to see that we needed to put structure around it. And that's where we developed the AI bootcamp. We said, let's start with our new hire cohorts. And now we've just, in the last— next week, we're expanding it to the whole company. And it's designed really to ensure that folks come in and actually go through our tools of either our ChatGPT Enterprise tool or Copilot tool, along with Workato, to actually have, you know, real scenarios of where their work can be applied to it from day one. And really wanted to ensure that folks understand that it's part of our culture, but also giving them the tools to use it. You know, we really do believe you build that early confidence, as they say, and you're going to build that, really the confidence over time, that early competence leads to confidence. So, We then have folks join a process pioneer team. So we've got this kind of journey that you go through at Project 44 related to AI. And I think the, the important piece to say here is that the metrics and the measurements is the piece that we're struggling with, right? Like, this is an area where I think folks need to focus on if you're doing this in terms of what is the true return on investment with some of these AI tools. In some cases, right, having some of these tools in place for engineers, for example, is going to retain an engineer. It may not necessarily be a productivity measure of more code or high, higher quality code. It may be something that actually, it leads to a richer playground for engineers that will actually help them innovate for customers, but it may not be a direct tieback that you can see right then. So, I do think it's important to think about metrics in a broader way, but also ensuring, again, 1,000 blooming flowers can be hard to manage for an IT organization. So, how do you really pick those? But, I would kind of highlight that's where we are in terms of our challenge. We set up a 25% productivity goal across the organization, and every department is now really seeing how they can apply that and how does that make sense within their organization. So we have actually seen a lot of metrics go up. We also embedded it into our engagement survey, our team member experience survey, to ensure that we're measuring the sentiment on AI and how people are using it, as well as just ensuring that we're measuring how our courses are doing, our AI bootcamp through actual folks that have gone through it. So still in a nascent phase there in terms of measurement and would love all viewers out there to maybe comment or actually put some things here that are good, good ways they've done that because we're looking to learn in that area too.

▶6:55HostRenee, your company has an AI knowledge base, and I'm curious about what specific challenges you've encountered with maintaining and updating that knowledge base and also how you're addressing the human elements of change management to ensure ongoing adoption and utilization.

▶7:14GuestYeah, we're in the midst of designing something we're calling the Beehive. And obviously it's something that, you know, needs to continue to be fostered. It's our biggest challenge. It wasn't the infrastructure, of course, it's human behavior. How do you get people to buy in and how do you get people to put in there all their professional knowledge and the process steps that go into their role every day, so everyone else can actually access that. We're building in nudge systems to ensure that at certain points in time in someone's journey, or certain points in time of the week, folks are reminded of that on how to use it. And also looking at recognition systems and how we can tie those into essentially, you know, requirements for the role in terms of expectations. Again, very, very early on, and it is, I think I would call out that in terms of that ongoing adoption, or testing on different, different levels, and it depends upon the team. But I definitely think, again, putting the stories forward, communication is key, of course, rewarding that with recognition systems. Again, we do fun things around our contests here, and then building in the nudges have been some of the things that we've really tried to focus on.

▶8:20HostRenee, obviously AI is going to have an impact on what roles employees assume within organizations, and I'm curious to get your perspective on how you're helping employees whose roles may be impacted in some way by AI and helping them develop transferable skills and create personal learning plans that position them for future opportunities and success?

▶8:46GuestYeah, so the first thing we have done is we've targeted individuals in roles and actually really encouraged internal movement into new roles. And that ensures that we actually force automation to move more, more quickly, right? We actually move that roadmap along faster, we find, if we're able to move that talent by focusing on internal movement. And we've seen some success there, specifically our customer support area, and team members moving over into more technical roles. And that again ensures that we've got to, you know, be intense about driving our automation there and not backfilling those roles. So that's one way we've really done it. In other cases, we've combined roles and responsibilities. While providing the appropriate support. But again, then it redistributes our prioritization to ensure that that function in particular is automated faster. So again, the opportunities around increasing people's jobs and making them more meaty, I think does lead to that prioritization versus kind of waiting for people to do that on their own. That encouragement and enablement is critical. We do do individual development plans like other organizations, that really, of course, helps foster the conversations around it. But one of those pieces, again, it's internal movement. It's targeting actually individual roles where, you know, those roles are going to change and supporting those folks.

▶10:08HostWhat parting advice would you like to provide to our community?

▶10:11GuestYeah, I think, look, start with your own shop. If HR isn't being used or isn't using AI internally, you know, you don't have that credibility in leading the rest of the organization. So piloting tools, being at the center of that is super important. And then again, like I said, focus on ROI and metrics, be ruthlessly outcome-oriented, but also adding in there that outcome-oriented is about team member engagement and keeping folks at the organization in a way that they feel like they have a vibrant career and a vibrant workplace. And so I think those are the key pieces.

▶10:44HostRenee, thanks so much for joining us today on the Built by People podcast. It was a pleasure to have you involved.

▶10:49GuestThank you. It's great.