First, thank you for joining today's webinar. We do have our flagship virtual conference coming up. It's called Forward. We're very excited to be talking more about AI transformation in practice at organizations.
We have a few partners. We would love to see you there. It's free. There's going be a lot of collaboration, lot of storytelling, so feel free to register for that.
And then we also have our next webinar, August thirteen, all around accelerating AI adoption with the slant on company culture. So if that's of interest to you, feel free to register. You can see the link here. It's on our website, but we want to make sure you don't miss those amazing additional opportunities.
And now that that's done, let's go to introducing our panelists. We're joined by Nina, Matt, and Yovanna, and I will go ahead and let them introduce themselves. So Nina, do you want to go first?
Absolutely. Thanks, Ria. I'm Nina Raphael. I'm the VP of People and Culture at Warner Bros.
Discovery. I'm sure you've all heard a lot about them, lately, where I partner with leaders across a few of our different revenue generating businesses such as consumer products, content licensing, in addition to that, our franchise organization as well. And throughout my career across media brands, consumer products, I'd say I've been part of leading through a lot of different types of transformations, big and small, and AI has definitely become a big shift recently in the workplace. That's why we're all here.
And so I'm excited for the conversation.
Fun ish fact about me. I just thought this was a relevant fact for today's session. I had a baby last year. So for the past nine months, AI has been the third parent in our household. I'm not ashamed to admit, but it is amazing how much Claude and Jatt GBT know about sleep schedules, wake windows, and quite frankly, how tired I am. So a little bit about me.
I love that. That's so relatable. Chatty bitty, the new Doctor. Google, right?
Absolutely.
Congratulations, Nina. That's so special. Okay. Next up, Matt, would you like to introduce yourself?
Sure. It's nice to see everybody. Matt Dyson, I support the people team at Dataiku, specifically around HR operations, analytics and tech.
I've spent my time in the HR space working for a number of different amazing companies, Amazon, Zoom during COVID, which was a wild ride.
Now at Dataiku, which offers and provides agentic services to large scale enterprises.
A fun fact about me, I'm a little bit on the other spectrum, Nina. So I'm teaching my son how to drive a manual transmission car at this point. So teaching him to balance clutch and gas pedal and brake. And it's actually brought us closer together. So I'm having some fun with it.
And yeah, I'm based in Seattle, Washington. Thanks.
Feel like the manual drive is a dying art. Until you go to Europe and you're like, oh, wait. I need to know how to do this.
Yeah. Exactly.
That's awesome, Matt. Thank you so much. Yovana.
Hi. Nice to meet everybody. My name is Yovana. Like Yovana, get to know me today. You can guess the many times I've had to say that. I'm also based in Seattle, Washington.
I also have a child, she is three, so I'm past the newborn stage but nowhere near the driving stage. I did learn on a stick shift, I am European.
Fun fact about me is I have four passports.
Almost got to five, but not quite. I work for a company called Rover dot com. We're a two sided marketplace. We're the biggest pet services marketplace in the world.
So if you have a pet and you have ever needed a pet sitter, check out rover dot com. We're most similar in terms of a business model to Airbnb. Some call us the Airbnb of dog sitting.
I have been at Rover for a decade, which is absolutely insane. I never thought I'd stay anywhere this long and the company just combines a really great business model with a really great culture. And if you work in HR, that's music to your ears. We're very values driven and just a really wonderful place to work. Plus dogs. I'm in my office right now, so lots of dog art all around the Rover office.
And so I am the head of people globally and have been in this role for the entire time I've been at Rover. So all people functions and people strategy roll up to me. And I agree AI has been crucial partner and change agent in my professional and personal life and something that I use every day and something that I think about all the time, just like many of us in HR. Excited to talk to you all today about the topics at hand.
Thank you, Yoavana. Can you just share where are the four passports?
Croatia, Serbia, Canada, and United States.
Wow, and what's the maybe fifth soon?
That was just me glitching out my internal AI, just kinda, there is no fan.
If I was to get one other one, it would be Spain.
I would absolutely love to live in Spain. Rover has an office in Barcelona and it's just stolen my heart.
Oh, yeah. Barcelona's amazing. Well, maybe one day you'll get your fifth. Well, as you all can see, we are joined by amazing panelists from very different types of organizations, different organizational sizes, different in their journey, which we'll learn a little bit about more.
But before we really dive into our talk today, for those of you that aren't familiar, I did just want to share quickly a bit about HONE. We're sponsoring today's webinar.
I have been here for almost five years helping organizations on their upskilling journeys.
Hone powers live instructor led learning and AI coaching for organizations.
Our founders have backgrounds in HR and AI and we really have taken this moment, this sort of AI moment, and realized what it can unlock for humans at work. So if you're interested in learning more about our live workshops on leadership development, manager skills, AI skills, or our AI coaching functionality, definitely reach out and we'll share more at the end of today's webinar. But with that let's go ahead and get started. I'm going to stop sharing my screen so that we can all see each other better and we'll go ahead and get started.
So now that we did some very quick intros we'd like to better understand where you are on your AI transformation journey. So in a few sentences, can you describe your current state of AI adoption and what is the employee sentiment towards AI adoption at your organization? And I'd like to hear from all of you. We can get started.
Yovanna, you want to kick us off?
Sure. The way that we've built AI enablement really has been through a culture of AI productivity enhancements that started at the beginning of last year when AI was, I would say, new and scary.
And so we first started with showing the organization kind of having an all company meeting that I led with our head of IT on what AI was, how to use it, and all the fun ways at that time that were quite new.
And then from there, really who's been leading it has been our engineering organization because they are, of course, the most disrupted and the most required to adapt AI. And it's been a natural evolution with a lot of internal encouragement, so very much the carrot, not the stick. We developed a quarterly AI champion award. And so we give a monetary award each quarter based on nominations for people who have used AI in ways that are interesting and productive to the business. And then each month, we feature examples of AI use to give people an idea of how it can be used because so much of it is choose your own adventure. So much of it is individual adoption.
And the amount of productivity enhancements we've been able to see has been really wonderful by encouraging people. Our analytics, data science, engineering product teams have been really encouraged to use it. And again, a lot of internal use cases and showing productivity has created a magnifying effect. And so that's created a lot more inertia and velocity in the teams. And we have not really started to put stakes in the ground and expectations on AI use until really in twenty twenty seven.
But it has been made clear by the CEO and our head of engineering that using AI is an expectation. And that's kind of we've been walking to that with time so that people didn't feel whipsawed. Where are we with AI adoption? I think we do measure it. We have access to all the platforms, ChatGPT, Gemini and Claude. Claude being probably the most popular.
And I would say we are really strong in adoption. There are pockets that I think are still struggling with it a little bit, and that's something managers are working through. But being a tech company, we don't really have a choice. It would be like saying, I don't want to use the cloud, which by the way, I did say that at one point.
They were going to move all our HR files into the cloud like ten years ago. I was like, but anyone can access Google Drive? And the answer was yes, but the building can burn down and then you lose all your files. Did you think about that?
And I was like, good point. And here we are now, everything's in the cloud. Like, I can't even imagine having paper files in my office. So I think AI similarly is just not something that people can lean out of being in a tech company.
And everyone understands that. Highlighting all of the ways that AI is moving people forward has been really effective for us.
I love that. Thank you for sharing. And it's a good example. I've been hearing people relate this AI moment to the internet, For those of us that were around during that time.
And we have some questions on your AI showcase. I know people are really excited for specific things. We'll get around to hear from everyone, and then we can ask some more specific questions into the tactics, because I know people love specific examples.
Matt, where are you all on your AI transformation journey?
Yeah, it helps that we sell products and services that support enterprises on their AI journey. So, from an engineering standpoint, from a data science standpoint, that's where really our strength lies, cleaning data, agentic governance and agentic usage. I would say on the G and A functions though, it was, we're early stages. And so something that only is an HR agent that employs across the world. So we operate about twenty countries and about fourteen hundred employees. And we were just getting hammered with tickets just for when's my time off?
What's my benefit in this country? I have someone that wants to move. And so rather than relying upon a human to do that is we built our own agent on our own product that contextualizes who's requesting the information. So we see if they're a manager, we know what country they're in, ask clarifying questions, and then provides a responder escalates to a human when in need. So that has been good because it's encouraged some celebrations, I think a little bit on the people team. We don't feel like we're as far behind as some of our, maybe our peers.
And it's a journey and just sort of like trying new things and playing with the tools that are available. We don't use our own products for certain things like we have Claude, as an example, for building up business cases.
We tap into Bursin if it's an HR compliance or HR specific piece of information that we need, his Galileo product. So we rely on the services and products that are sort of what we feel are experts in those areas, But it's something that we all own internally as an organization. And we've had to change hiring practices around it. So are we hiring for skills regardless of what their role is in the company, that they're curious learners, that they are familiar with the tools and capabilities of these products that are out there, and how can they leverage them when they're here at Dataiku.
So much good stuff in that, Matt. I wanna ask follow ups on all of it. But really quick for everyone on the line, since I know we have mostly HR related people, how many of you have some sort of HR business partner bot or HR chat that helps with some of those, you know, logistical benefits, like, type questions. I feel like this was one of the main use cases people started with AI and experimenting with AI. So just curious in the chat, you could put, like, a one if you're doing something like that or a comment of how you're approaching it or if you're thinking about it. Okay, Nina, would love to hear from you.
Thank you. I think we're a little bit further behind the new map there than even Yovana, but WBD, I'd say we're definitely moving more from that experimentation phase to scaling AI at the organisation.
The focus has really shifted to more of that practical, intentional adoption across the organisation. So where can AI help teams work faster, make better decisions and create more of that capacity for the work that actually requires a human judgment. And it's definitely been a journey to get here over the past year or two. Teams across the company have been really focused on building that foundation to use AI responsibly at scale versus just what we've seen it really been within individual teams and being such a large company, really focusing on how do you bring that all together, but also appreciate and respect the nuances and individuality of what different functions and groups need across the organization.
And I think the employee sentiment has been what you'd expect with something moving so quickly. There's, right now, I'd say real appreciation, curiosity and momentum. But entertainment has always been impacted by tech changes. There's a lot of different companies.
And so there's obviously very fair questions around clarity, safety, practical value, what AI means for people's roles. And I think that's why the strategy behind it needs to stay focused on what's our intention and how do we scale responsibly and have the biggest impact. And I think for me personally, it's not to chase the hype.
It's more about how to help teams operate more effectively and really free up that time for the work only people can do. When we can't outsource to machines.
And at such a big organisation, I assume, similar to Rover, it's pockets, right? You might have one team that's fully transformed, you might have another team that is more novice in its journey, and it just sort of depends on how do you meet them where they are in service of the larger business goal. Yeah.
Well, thank you all. And I'm sure those of you on the line, can think about where are you on your journey in your organization and can reflect on that as well.
So we asked in the beginning of the webinar who owns AI transformation and we saw a lot of HR and IT executive team. We saw no one owns it. We saw everyone owns it. Right? It's interesting to think about. So before we go into, like, specific tactics and things like that, I would love to hear maybe, Yovanna, you can start us off.
How is the strategy, the overall strategy being defined, and who is owning it at Rover? Would love to hear.
So I think the tone is really set by the CEO.
They either lean in or they don't, and they either encourage it.
Well, a lot or a little.
I think it's then it's the executive team that takes that to the next step because adoption looks different by team. As I mentioned, obviously engineering is much more disrupted than some other departments, but so ours has very much been top down.
And internally, who's been leading the culture of AI productivity enhancement has been myself in partnership with our head of IT, who has actually set up time and programs with every department to sit with them to work through what are the use cases, what kind of AI tools are best for them, and how can they accelerate adoption. Because we what we found that people wanted to do it, but they didn't know where to start or where to find the time or how to do the thing. That's why those examples that I mentioned that we share every month are helpful because they make you go, oh, that's what I can do.
I can dump the data into it and I can have it summarized and even think about that. And so for example, the IT leader who sat down with our team, what came out of that is we have an AI chatbot that is going to hopefully replace our HR rover dot com alias where a ton of questions come in from employees. And it's either going to open up a ticket, which it's already doing, or it's going to answer the question by searching our current Confluence database where a lot of the answers really do sit. We also do not have a recruiting coordinator anymore.
That is completely done by AI. We use a platform called GoodTime, and it's actually really good.
And then our compensation analyst role has been probably fifty percent automated by different agents who are able to search compensation data. And then they have done that for other departments as well in their use cases. Procurement has seen a lot of gains, legal has seen a lot of contract review gains, and then there's been actual monetary savings as well outside of just headcount costs and time in other departments.
I think that was another part of your question. Did I answer it all?
No, that was great and really good examples. I'm curious, someone came up with the concept of let's have IT meet with each team. Like, was that a joint collaboration where you're like, how can we help individual teams? And you came up with some of this program.
So I, like everybody else, have been reading about what the heck is going on. And I've heard HR and IT work closely together, and IT has been reporting to HR. And so I've been talking to IT. I roped our head of IT into doing that presentation, which really kicked off.
I raised my hand to head the culture of AI productivity enhancements. I cannot move engineering forward. I'm not technical enough, and I'm not the right person. That really is a tech leader.
And then as we put those stakes in the ground, I started asking, how are we going to figure out how to use AI? Because I hear, as I mentioned, people don't know where to start or what to do. And I suggested we hire an AI evangelist to do this work. And our head of engineering said, I think the head of IT can actually do it.
And I said, all right, well let's try. And he honestly blew me away and has done a way better job than I thought. I think the entire IT org is passionate about this. They work on it.
They're excited. They see the gains. People are thankful, which always feels really good and fulfilling, like I helped. And so that's kind of where it came from.
So it was more of a collaborative effort between us and technology.
You were ready to hire an AI event. I would love to dig into, yeah, the job criteria for AI evangelist. That is fascinating.
And I think that's the hard thing because I was hoping to find actually a product manager internally because I thought that would be the right it'd be great to have someone internal because I think understanding your culture, your relationships is really helpful to driving change or hiring from the outside.
But to your point, there's no outside expert. And so the head of IT was a really great solution.
Thank you.
Matt, Nina, anything you'd like to add from your perspectives on how strategy is being defined, maybe overall, but maybe also by teams or collaborating with IT and HR?
Yeah, I think one thing that Ioannna touched on is that relationship with IT is really critical. We have an enterprise data team that we work with really hand in hand and did so on launching our HR agent solution, because they're really awesome at guiding us on things that we should think about. So how do we think about use cases in determining what the impact will be? How do we score use cases? We focus on the right priorities. How does this tie to what other folks are doing in the organization?
So if we have two or three groups of people that are doing similar work, can we package it together and create a project that everyone gets cross functional gains out? So that's been helpful for us.
Makes sense, thank you.
We did get a question in the chat around the HR AI bot. I think we saw a lot of ones, people are doing this and some people, maybe they're thinking about it, but they haven't done it yet.
I'm going to make it a little more general, which is from an HR standpoint, which we all are HR here, how are we thinking about the security concerns and the governance model?
I think we can answer Janine's question within that as well around sharing employee data with a bot. Curious if any of you have thoughts on that.
It's definitely a real concern for people around security, especially in HR, of like, what can I put in there and how transparent can I be? And we have rolled out AI policies, product guidelines, and we also set up Warner Bros. Discovery AI COE, and that's helping to provide those standards and implementation guides and governance. And so, you know, I think the balance is for us a little bit more around empowerment, with guardrails and how to use AI and do it safely and responsibly. I think the important part of this is it's not about, Hey, don't do this, and then slapping on the hand. It's more about giving people the comfort of, This is how you can use it, and here are the steps and measures that we've taken to ensure that the data in here is is protected and, try to support with some of those concerns. And I think not only IT and HR, but leaders play such a big role in in creating that safety for people to feel like they can experiment.
Absolutely. It's the newest COE, right? I feel like we've had centers of excellence for a lot of different G and A functions, and now this is the next one up, AI governance.
Okay, moving along, I want to get into some more nitty gritty stuff here with our panel. So AI fluency is a big topic, especially at home because we teach it and we partner with our organizations to address AI fluency. How are you thinking about enabling AI fluency, helping people with the tools they have access to, helping them with understanding the governance and the leadership aspect of it, right? This is a huge body of transformation work.
Would love to hear a little bit more about that. Maybe Nina, you can start us off.
Yeah. Absolutely. So we're approaching AI fluency at a macro level as both learning and and change management as well. And it's just it's not for us just about what the tool does.
It's knowing when to use it, when not to use it, how to protect companies we just talked about, you know, and how to keep that human judgment at the center of it. So one of the ways in which we're moving forward with the learning is there's a Learn AI, AWBD AI learning platform. So that's bringing together more of those foundational courses, practical learning paths, copilot training, which is what we use. So things like that just to give people the foundations and feel a little bit more comfortable with our experimentation.
And and also business specific sessions that show how AI is being used in in the real workflows. I was joking with the panel before we joined that. Right now, there's a session for HR specifically on storytelling and data and analytics that I'm missing for this. So I will be watching that recording then.
You know, and the goal, I think, is to make AI feel less abstract by connecting it to the work employees are already doing every day. But again, we're such a huge organization that building this we also have to build that fluency through more of a broad based and some more targeted programming. So as examples, there's a let's talk fluency webinar that features AI in divisions like news, sports, tech, and creative and and other business units, which I don't have visibility into, but I've just heard that they are all kind of working on focused adoption plans as well. So finance has the AI adoption strategy, for example.
So and again, the the emphasis has been shifting from some of that passive learning to more hands on applications. How do you train, apply, assess, measure what's working? And for leaders and teams, I think that means really, as Ioana mentioned, identifying real use cases, being able to experiment safely and sharing those wins, also looking at what doesn't work as well. And we talked about already the policies that we've rolled out to help that balance from that implementation and experimentation and supporting people and knowing what's okay and and maybe where they shouldn't be using AI.
Are are you doing something specific for leaders as well as specific functions? Yeah. That's what it sounds like.
Yeah. And, you know, I think, for leaders specifically, they have been asked more around, like, what is their role within AI? And then I I know we'll get into that in a little bit as well. But for leaders, it's really about how do they help drive AI and even asking them to bring things into a into goals and media connections and conversations and helping them understand that they don't have to be an expert in everything AI. They just have to be able to enable the space to navigate into it as well.
Some of those skills you mentioned, you need to feel safe to experiment. You need to have that psychological safety with your team to bring up ideas, to fail in a new way. Right?
AI is all about iterating and prototyping, and Yeah.
A lot of teams aren't as comfortable with that as a product or engineering team. So Yeah. New muscle.
And role modeling it too. Right? How do you demonstrate using it and and moving forward? And we've not put on the shelf or neglected things that we would normally be doing. We just ran more sessions on, you know, feedback and difficult conversations, which we've we've all done for a really long time, but, obviously, those types of sessions evolve and adapt to what whatever it is that we're dealing with. So we run a course with people managers, but individuals too to really just help refresh some of those skills and help people understand how to create that psychological safety.
Yeah, the human skills are just as important to the transformation success as the technical ability to use in your case copilot.
Absolutely.
Matt, would you like to share?
Yeah, very similar to Warner Brothers Discovery. We have a lot of embedded learning on our learning tools. We have employee journeys, so they would take them on a journey to learn how our product works.
The differences between agents, why data governance is important. And then we do a lot of practice sessions. That's really important skill. So not only are they learning the skill, but then they're practicing with data, so they can produce an output. I think the other thing that we do, which is pretty powerful, on a regular cadence, we do what's called Thursday Connects, where we have customers talk about their experience in using our tools.
So whether that's something around social impact, whether that's around driving better analytics across our organization, seeing how customers are using it is empowering it. So the work that we're doing connects to larger outcome that we can all sort of rally behind. It really spawns some really cool ideas. And it's not a passive experience. We get to ask questions for these folks and learn what's really special about our products and services. So that's been pretty powerful.
And that is helpful regardless of AI, right? Absolutely. Connecting to your customers, hearing directly from them, being able to ask questions makes a lot of sense. I'm curious for the data, you said you actually give them space data to work Is that something you make up the data for them? Is your team leading those workshops? If someone wanted to do something similar, what might they do?
Yeah, yeah. There's several data sets that have been quote unquote anonymized, but we do everything from movies of the past twenty years about revenue and box office and ratings. We sort of pull from different data sources. Sports is another one that folks can deep dive into if that's their passion.
And so we give them a bunch of data sets that they can tailor it to their own sort of either an interest. And that is really helpful too. It gets them comfortable because they contextually, they understand what that data means.
From a real world use case, from a governance perspective, we have data standards and governance standards, we have what we call goal data sets, which is our lockdown data sets to certain individuals. And we don't alter our security stance based on if you're using our tool or you're using like a Workday or using our tool and you're using Salesforce, we mimic the security and governance. If you have access to customer data in Salesforce, then you can build out tools that you can use to help better support your customers with that same sort of data. So that's been pretty helpful as well.
And now it's easier than ever to get a sample data set because you can ask AI to create one for you based on the sports statistics or the movies. But interesting, both Nina and Matt, you mentioned this importance of it's not passive.
Yeah, definitely not.
And I think that is a key thing. People need the sandbox. They need to try something before they have to go do that. That's the only way to build comfort with these tools, any tool, but specifically these tools.
Yovanna, I would love to hear a little bit, and I know the audience would as well, about this showcase, the award, how that's selected. Can you share a little bit if someone wanted to do something similar at their organization, what they should think about? Because I think that sounds really special and celebratory and makes the learning exciting.
Yeah. So we have quarterly awards for employees that we give every year. One is the values champion. They submit examples of on values behavior because we want to reinforce our core values. One is team impact, so examples of teams working well together.
And then we added AI Champion to that, so it was already a rhythm we had. And employees submit or managers examples of great AI adoption, AI productivity enhancements, something that people implemented that they thought was really cool or saved the company money or saved them a bunch of time. And then we have a panel or a group of people that review the submissions. One is the head of IT, who's really been kind of that main change agent and that by department, him and his team trainers that have moved forward AI adoption. One is our legal partner who works on AI because of what you all just mentioned privacy. And we don't want to get in front of the company and highlight an example that maybe isn't toeing the line appropriately. And then the third is a member of our analytics and data science teams who use AI a lot and kind of have a good picture of the impact to the business.
And we do tie it to one of our core values and then they select the winner each quarter and then they get a monetary prize of it's seven fifty dollars five hundred dollars post tax in local currency because we're a global company. So roughly that works out in terms of tax. So it's not a huge amount of money. It's just a big signal. It's celebration to your point, and it is a bit of a monetary award.
We thought about making it bigger. And I asked some of our executives, should we have a really big monetary award? They said, this is kind of part of the job. I don't want to say we're going to pay for you to use AI when that has become table stakes like the cloud or like the internet.
I would add to what Matt and Nina said about AI adoption. We have also used OKRs for a long time to set expectations. So for example, I gave my team OKRs a year ago to each quarter learn more about AI and come up with one useful way to use AI that's new to you. That was kind of the start.
And then it got more and more, the bar kind of rose. And then we are currently doing our midyear check ins. This is not a formal review. It's just kind of check-in midway through how things are going.
And we are asking managers to give feedback on a couple of dimensions, including AI adoption. So it's kind of continuing to create those expectations and then reward really great adoption in a bunch of different ways.
I assume you have a specific rubric of how you're measuring it so people know what to highlight in their submission.
No. We just ask to submit great examples, and then we pick. Because if you overengineer it, you're going to actually discourage engagement. It's hard.
Right? People are intimidated. Like, don't know. I used AI, but maybe it's not that cool.
And if you do that too much, you actually end up with, like, one submission. And we want to have everything. So just submit anything you've done and managers can do it. Managers can say, oh my gosh, Nina and my team just did such a great job.
I'm going to nominate her. I'm just so glad even though Nina would never submit this for herself because she's humble or shy or whatever. And so I think you want to make the barrier to entry too high. That panel really of quite senior people are the rubric.
They sit there and they go, that's not quite it. And a lot of them know the example where it comes from, the IT leader or someone has worked with this person, and so they can reinforce that. And for example, they chose not to recognize our principal engineer who actually did a lot with AI because that is such a big part of their job and chose to recognize someone deeper in their organization, someone more junior who really was doing something way out of their way to go, wow, look at that. And that's the judgment that we really put on the more senior people who are picking the winner, and we open it up to employees.
And we also have a slide that shows all the nominees names. So you just kind of get recognition for just doing it, like getting on the journey, putting yourself out there. I mean, and this is like a quick couple of minutes. It doesn't take up a lot of time.
It doesn't create any friction, but it's just kind of a feel good in a world where there's so much pressure to use AI. We're all trying our best, and it's just like it's never good enough or whatever, or AI screws up something you want, you thought it would do well. Let's just kind of celebrate it and say something positive.
I love that. And even if you don't win, you still get that recognition piece for doing something a little outside your scope, trying something new. So that's and and you make a great point about the rubric. You don't want there to be too much of a barrier to entry. You want people to feel really comfortable submitting. So that makes a lot of sense.
Okay, so we started at sort of high level overall organization. We went into more strategy piece. We've talked about some ideas. Now I wanna talk about the HR function specifically. So we have certainly talked a bit about what you all have been doing in HR and some of the learning and development and enablement pieces. But when you think about the HR team as this either leader of AI transformation or partner to IT and the senior leadership, what has been changing on the HR team specifically?
Matt, maybe you could kick us off.
Yeah, the experimentation and the empowerment to try new things. One example is, and I had someone present earlier today, if you're operating in several different countries, we have a leaves program, and there's statutory and compliance pieces, we have different providers, and it becomes quite difficult to figure out who's coming, who's going. And so I had someone build out a leaves tracker. And so we know exactly who's coming, who's going, where they are in their sort of leaves journey. Pay accuracy has improved greatly since this person started to play around with using an agentic solution to this.
And it's easier to then communicate with business leaders and also our business partner team around where we might have some gaps in the work. And so rather than relying on tracking it just in Workday or relying upon your leaves provider, like a Tilt or a Sparrow or a Unum, is we can just take control of that data and we can really better understand where things are at. That's pretty cool. And that experimentation would never have happened.
We would have just been stuck with the same old challenges of trying to manage it manually.
Yeah, or through a behemoth like Workday, which doesn't give you necessarily the visuals that you're looking for or the exact data in the way you want it. AI becomes a new interface.
That experience layer has completely transformed. I mean, ideally what I'd like to be on Workday, I don't want anyone to know we use Workday. If there's anyone from Workday on the call, apologies, but I'd rather have the experience layer be our own product and the backend data sit on Workday. To me, that is the best of all worlds.
Just taking this as a specific example, did this person come up with this interface by just experimenting and trying? Did they go to a class? Did you coach them?
Experimenting, you know, and I think there's a question around like, where is, what's on horizon for people ops? I think it's that, I think it's the ability to think about strategy. It's the freedom to experiment a little bit and to look around corners and how can I make this better? So whether you're in an organization that's growing, so you think about entity expansion or M and A work or if you're an organization that is under a restructure, those folks can be redeployed to support larger organizational changes that are occurring. They're just not stuck as a transactional support layer.
And then for you personally, Matt, as a leader in the HR space, has any part of your role significantly changed? Like how would you describe what's changed for you?
Yeah, I mean, I better get on the train. I better experiment. I better come out with impacts.
I have to understand what tools are out there, where I have a viewpoint of what tools may work better for specific use cases.
I have to interact with the IT team and enterprise data team. So I have to have some competency in the space. And if I don't feel comfortable enough to like, I don't know what that means, or I don't even know where to start. And like Yoavana said, I'm not an engineer, but I have to be able to speak to engineers and I have to be able to translate requirements and use cases into action.
Absolutely.
Yoavana, anything you'd like to add at Rover?
I would say for the HR team, what's worked the best is giving them an incentive through an OKR and then letting them play. And I have been really impressed with what they've been able to come back with. I did give certain ones certain challenges, like I want you to automate this or look into this, but a lot of it has been white space and that's actually been more fruitful because this stuff is so new and they know their areas the best. And so giving them an incentive and then rewarding them leaning in has led to the AI chatbot.
It's led to the compensation analyst automation. It's led to the recruiting coordinator one. We also just implemented a new tool in recruiting, which is a really strong note taking AI tool that's able to accelerate their productivity quite a bit and give the recruiters leverage because they're in so many back to back candidate calls and that they're really excited about and it's quite cheap. I want to say it's like one thousand dollars a year for the entire recruiting team.
I would not have found that. And I wouldn't have had the time to look into something like that. And it means a lot to them and it actually increases their morale because they're like, my god, I don't have to do note taking, which is maybe not my favorite part of my job.
And I get to lean into AI. So I think that's been really great. We also, by rewarding and recognizing it, have made it more of a positive because I do think there's a lot of fear and there's a lot of need for psychological safety with it. And that's also led to some more really interesting adoption.
And I myself model the behavior. I mean, I use AI all day, every day in terms of just as kind of a writing partner or a thought partner or a researcher, and they see me doing it. I think that's been really helpful as well and has accelerated their own ability to do that. And I've seen their proposals get better.
I've seen their presentations get more crisp.
Have our CEO's named Brent and we built a Brent bot. And Brent bot will review your deck because all the executives are like, you give the same feedback every time when I'm making a board deck, can we just make a bot?
And so one of them, one of the executives made Brent Bot, and I've shared Brent Bot with my team, and it's just like these little moments of like, the the fact that we all smiled, like, we can do this.
It can it can be productive. It can also be kind of fun. And it's, I think, made us, all a bit better off.
I you for for comp analysis in the chat, we use Claude quite a bit. That's probably our strongest one. But for our chatbot internally, we use Atlassian because we're on confluence, and it just searches the database where you already are.
So sometimes it's the lowest hanging fruit that works the best, but Claude has just kind of been an analytical horsepower unlock for us.
I feel like Claude has usurped ChatGPT for a lot of organizations in this usage.
Because we have so many HR folks on the line, go ahead and put in the chat how has AI transformed your team, or what are you thinking about in terms of this moment in HR? And also, have about twelve minutes left. We have some time for questions. So if any of you have questions, feel free to put in the chat. I love when we can learn from each other. So how has AI been transforming? How you are personally doing on your team?
Would love to hear a little bit more. So Matt, you kind of touched on this, but it is pretty big consideration when it comes to HR. People are worried about their jobs.
We see the restructures in the news for a lot of major organizations. We see mass layoffs in the technology space. This is just the reality. Some people don't want to use AI because they're scared AI is going they're gonna get too good at it and then AI is gonna do their job for them and that's a real thing. So I'm curious to hear from all of you.
Nina, maybe you can start on how AI is affecting jobs and just your leadership perspective and what you've been seeing in the the industry.
It is obviously natural for people to feel very uncertain about the future every time we have a big or small change like this. And, you know, from my perspective, AI is changing roles. And we've we've heard a couple of examples where from your honor and Matt around how whether it's impacting headcount or it's redeploying resources to other bigger projects. You know, I can take on more of those repetitive or time consuming tasks like we've been talking about and the work.
So for me, the work within the roles is evolving and we're placing more emphasis on other human skills like the judgment, creativity, critical thinking, relationship building. And I actually think that's exciting. I know it's obviously very disruptive and concerning to a lot of people. I think the challenge for organizations is with that, how do we ensure employees have the right skills and support they need through the shift?
So it can be less about restructure and more about reshaping and upskilling and building those capabilities. And I think we just need to be honest with our employees about that. There are opportunities to evolve roles and how do we do it? And not everybody will have the right skill set, right?
But how do we support and make sure that we can bring them on the journey with us?
And we talked about managers and leaders earlier, but I think they have such a huge role to play in this as well. I think the shift definitely is from simply encouraging it to really helping using AI with purpose and setting the context, like what problems are we trying to solve for, what tools are okay to use, what data is appropriate, Where we want that human review and judgment and where accountability is still required.
How do we create those conditions for that growth and the responsible experimentation?
And as we talk about roles shifting, managers, of course, need help with defining those critical skills as well needed for the future and what does that look like. So I think, yeah, there's a lot of reason to be concerned, but there's a lot we can do to help support that upscaling and supporting their teams. And I just wanna double click on something that Ioana said earlier, which I thought was really meaningful and great. Like, the way that you're recognizing AI as part of an existing recognition framework that you have, I thought was I think it's brilliant because we always talk about not reinventing the wheel. So how can it not become this huge thing that we have to do and create? It's just another part of the way that we work. So I'm I'm actually curious as to how many people on this call are also doing that, looking at their current recognition programs and incorporating AI into that as well.
Yeah, feel free. Everyone on the chat, are you incorporating this, or is it something maybe based on this webinar you might think about?
Would love to hear any additional ideas.
Thank you, Nina. Yovan and Matt, anything you'd like to add?
I think Nina mentioning those critical skills, is gonna be really powerful. Critical reasoning, root cause analysis, those enduring skills that are really, really useful in any context in a business environment.
How do I identify AI slot? It's going to be a new one, I think, as well.
Making sure that if you are using it to look at compliance or laws, that they're citing sources. And so that really becomes a really useful tool because that critical eye only makes you a much more valuable employee.
And I love that Nina bravely kind of goes into how the roles are changing. And I'm here to learn because I think this is such a hard space to understand. And so I love hearing from other leaders on how that looks for your organizations.
I would say I feel like I know less now than I would.
AI feels to me very much like two steps forward, one step back, two steps back, one step, it's very iterative. They are definitely gains. You heard from me some of them. I definitely feel more productive in some ways. I also sometimes feel really frustrated because I'll spend an hour with AI and then walk away with something I have to redo because it didn't quite get what I was trying to do.
Or AI slop has become such a good term. It is real. It is everywhere. I think people have gotten way too comfortable sending over like a three page thing that AI just spit out and I don't have the time to read them. And so creating that organizational discipline, I think is important. But in terms of how jobs are changing, I don't know. I think the things I do know is the expectation for a business impact and productivity has gone up because we are now more productive.
I talked to a principal engineer at Meta and I was trying to understand how are things changing for you all? And she said, we're writing more code, we're spending more money, but we're not shipping any more products.
And so what's happening is people are handling a lot of low hanging fruit. So they're going after what's easy and not actually solving the big problems because it's like that quick fix. I did a thing, AI helped me, but at the end of the day, they aren't moving the needle. That's why I think the bar for business impact has to go up so that you incentivize everybody to kind of have the right goal ahead. And then I think the need for judgment has gone up.
Leaders need to spend more time thinking through that, think individuals. And I think the way roles are going to evolve is going to be in those veins. It's going to be more judgment, more business impact, and probably wider breadth, but I don't know when or how. It seems like teams of several might become smaller where people wear more hats.
And I think this is going to look different at scale. So we'll look, Rover only has a little under six hundred employees globally, FTEs outside of all the outsourced talent we have. It's going look very different than it will at Warner Brothers or some other really large organization or Google or wherever where they have economies of scale. And I think that's what makes it exciting, but also a bit confusing.
And it's a huge opportunity for us as HR leaders and HR partners to figure out what that means for your company and shape that future. I like to use Spider Man. Great power, great responsibility, I think is at play here. But it's a really amazing opportunity for us to add a lot of value to our business.
One of the things I just wanted to thank Sorry for interrupting you, but I just wanted to share a very quick example.
So as I said, there's a HR academy that's being rolled out around different types of training specifically for the HR team. And one of my team members had said to me when I asked him how how did that go? You know, he was like, it was good, but, you know, that's not how we would normally do this. And it was related to org design and using AI for org design.
And, you know, my feedback was it's it's not intended to make what do faster. It's how do we look at the way that we're working sometimes, and maybe that is what needs to shift. Because, actually, the dataset that was being plugged in to help with your design are actually the same pieces of information of questions that we would typically go and ask a leader as we're initiating those early conversations when we're looking at org design and restructurings. So it was just a different way of getting there.
So I think it was, you know, interesting moment that just popped into my head as as Yovana and Matt were speaking of, yeah, we have to think about what could shift and it's not just about making things quicker for us.
The way it's been done is not necessarily the way it needs to be done in the future, right? We can rethink all of it. And just one overall theme that I heard from all three of you, which has always been crucial for HR is how are we supporting the business imperatives?
What is the context? Nina, you mentioned this a few times, what is the why and how is this moving the business forward? Not just, Yoavana, the little quick wins, right, which we know are gonna happen too, but how are we really leveraging this to bring us into the next phase of our business? So we are coming up at time. I do want to say a huge thank you to the three of you for spending your time with us and to all of you who joined out of your busy days. We always appreciate having such an amazing audience.
As last to do item, we'd love to give you a free home class for anyone on the line who hasn't had an opportunity to try one of our AI fluency workshops, now is your opportunity. So feel free to click on the link in the chat and we can chat more about your goals and we can get you signed up to experience a real class.
Again, Nina, Matt, Yovani, it has been a pleasure. Your insights super valuable. It's really interesting always to hear how different size organizations and how you're handling and where you are on your own transformation journey. So sharing your perspectives is always helpful. And I look forward to seeing all of you on the line at Forward, our virtual conference coming up in September, and our next webinar in a couple of weeks around AI and the change associated with it. So feel free to click on the links in the chat there too. And with that, thank you all, and I hope you have a wonderful rest of your day and week.
Thank you. Thank you.
Thank you so much.
