Value said, my name is Caelan.
I'm part of the learning solutions team here at Home, which really serves as the kind of consulting arm of our organization.
I get to work with, prospective customers and customers to really align on how Home can be a really great partner in your learning architecture. My background is in industrial organizational psychology, which is quite mouthful. Any other IO psychs in the room feel free to give me a shout out in the chat, would love to hear from you, but my interest in passion has always been in learning and development. So I've been in this space for the last ten years and have really been on all sides of the house. I've been a facilitator, program creator, worked in client services, and so really bring all of that to the work that I do here in consulting on L and D.
I would love to go to Kevin next.
Sure. Hi, everyone. My name is Kevin King. I oversee global learning development and talent management here at Crunchyroll. If you're not familiar with us, we are not a sushi company.
But if you know anime, you probably already know us. We're one of the biggest names in anime across the world, which is really fun cartoons out of Japan.
Fantastic product. And so I'm thrilled to be a part of the company helping people learn to fuel fandom, and part of that is using AI to help grow leaders and new hires.
Kevin, Kelsey, we'd love to hear from you too.
Yeah. If you're not familiar with Crunchyroll, it is the number one anime anything, so I highly recommend you check it out. But I'm Kelsey Botna. I am the learning and performance lead at HowNow.
And much like Caelan, I manage our professional services team. And what that means is I essentially work with our customers as a consultant to make sure that your learning strategy connects with your business objectives, particularly when it comes to AI. My background is in learning science and education, but as essentially how you implement that in technology. So very happy to be here. I'm very excited for this conversation.
Yeah, and we've got some fun connections on the line in terms of Crunchyroll works closely with both Hone and Hau now. We may have some other shared customers on the call. And, before you got online, other people might have seen that we announced a really exciting integration too. So making sure that, both of our products work really well together.
So it's fun to also be together online, in the in the wake of that announcement. Announcement. So excited to all be here. I am going to stop sharing screens so that we can just have a conversation.
This is gonna be very just dialogue conversation heavy. Again, drop drop things in the chat so that we can hear what is most important to everybody in the room.
We're gonna jump right into our first question. My first one is a little more rapid fire. Get us started, get us warmed up. Would love to hear maybe Kevin from you first. In one word, what's the most exciting culture shift that you think AI is bringing into your workplace right now?
Discovery.
And I'm gonna explain it using more words than one, of course. So like AI is flipping on the light switch and, like, uncovering kinda, like, dusty processes and procedures that maybe aren't documented. And if it's not documented, it can't be automated. And so it's really showing us, like, what's working and what's not working and what we really need humans to be doing and what we probably don't.
Like, do we need to be sifting through and prioritizing emails all day? No. We don't. AI can do that for us.
Amazing discovery. Kelsey, how about you?
I'm going to say empowerment. I think much like Kevin, I'm going to say more words than one. But I think we're seeing a shift from AI being viewed as a replacement essentially to becoming more of a copilot and I know that's what a lot of people are talking about right now, but I think that empowers people to offload the repetitive tasks, which is kind of like what Kevin is saying, but I think it's the eightytwenty.
Offload the eighty percent of tasks that are just taking time and so we can focus on the twenty percent that actually drive value.
Yeah, I think we're gonna have some themes here. My word is innovation. I would also love to hear everybody else's words who's on the line. In one word, what's the most exciting culture shift AI is bringing to your workplace right now?
Feel free to drop it in the chat. Mine is innovation, and again, because I think of that eightytwenty, right, where we get to offload those tasks that do take up so much of our time, it really frees up that human capability to be creative, to think more strategically, to get excited about parts of our job we maybe haven't been able to dive into because we've had to be taskmasters historically. And so really loving to see the possibilities that are opening up as a result of AI.
I think there's ways that you can kind of reduce it to, you know, just another tool, but I think as a lot of what we're seeing, even just coming into the chat, focus, culture, creativity, it's been an unlock for a lot of organizations in some pretty cool ways. So yeah, feel free to keep dropping those words in the chat. I'm really loving to see what's coming in so far.
Alright, that's our warm up question.
Then we're gonna get into the meat and potatoes of it with that kind of inspiring us as our start. And Kelsey, I'm going to come to you first.
I think it really goes without saying, obviously we're all here to talk about it, but that culture has always played a major role in any type of organizational success.
And as we all noted in just even that opening question, AI is changing how we work. And so I'm curious to know from you, how are you thinking or rethinking about what your company culture looks like in this increasingly enabled workplace?
Yeah, it's an interesting question. I think we are redefining a bit. We're redefining what the culture is and we're shifting from one that essentially rewards knowing the answers which is what we've been doing to one that more so rewards knowing how to get the right outcome.
So I think an AI enabled workforce or workplace, which is what a lot of people are aiming to get to and a lot of companies are aiming to get to, I think culture isn't just about values on a wall essentially, it's about operating principles. That to me at least. I think we're prioritizing experimentation but with guardrails and the guardrails are the essential part of that. So that means creating an environment where curiosity is celebrated and I know Kevin we've talked about curiosity before but I think it's bounded by our foundation first commitment. I want people to have the right foundational knowledge so that we can be curious about what we're doing I think responsible use, things like data security, critical thinking, non negotiable pillars of how we get things done. I think that curiosity is the priority, but we have structure and the guardrails around it.
Yeah, interesting. I think you bring up the, I like the values on the wall as a visual, right?
We have a lot of times in our culture, these very formal practices or beliefs or institutions put in place and that can be a part of culture, but it's also about what's happening outside of those formal boundaries and those informal ways that is supporting those things.
Think it is. It's part of the foundation of our values, but I think given that we're trying to bring AI into everything, we're learning how to be flexible and restructure things, and we need to renavigate it a little bit. Yeah. But I think we have to still be rooted in those foundational things.
Yeah. Absolutely. Kevin, interested to hear some of your thoughts as well.
Yeah. Of course. So if there's two things y'all are gonna get really tired of hearing today, it's gonna be the word values and curiosity. It's gonna come up a lot.
Let me see if I can take a slightly contradictory line to get to the same place. So I would like to think that this is very much a change management style question. It's all about framing and how we are telling that story. I see culture as the stories we tell ourselves about ourselves, and our values are those kind of distillations of how that shows up and the things that we can rally around.
So those words on the wall, when done correctly, are really impactful. And the good news is it really doesn't matter what they are. Like, everyone's values are correct. Like, you you're never gonna go to a company and see, like, a crazy word as a value.
It's always something that we can kinda get or, like, get behind. And so I like to think we shouldn't change our culture because of AI. I think our culture like, when I think of Crunchyroll, our values are courage, curiosity, kaizen, and service. And so our culture already has two of the biggest behaviors needed for AI adoption, curiosity and kaizen, which is this desire to be better.
And those are needed for any tool, whether that is a new process, a new tool, something disruptive like AI.
And so instead of thinking about like what we need to change in our culture because of AI, I would rather think about how we can use the strengths of our culture to maybe leverage something new differently.
When I think about the change manage you're gonna hear me talk a lot about this today. When I think about the change management needed here, like that is the framing for everything that we are approaching.
Yeah. We're hearing a lot about how the change management function though is so much more than just implementing another technology rollout. Right?
It's not just, you know, we've added in another tool or system, it really is the change management potentially of our culture. And again, not culture changing, but how does it align now to this new AI model? We can't just add in a line about AI and expect our company to kind of come along with it in that way. And I think sometimes it can get reduced to that, right? Well, if we just add an AI language to our policies and our procedures, then everything is covered and sorted out, but it really isn't how are we reinforcing those behaviors and things along the way.
Any additional thoughts, Kelsey and Kevin, on this question? I'm seeing some good stuff in the chat too.
Kelsey?
Not not yet, but I'm sure I'll have plenty to say. Don't worry.
I feel like our next question gets right into it.
Yes. It does. Absolutely.
So we'll move right into that next one. So especially kind of from my perspective, I've shared them in this consulting space, so I have a lot of customer conversations with home customers. And we're often seeing that the organizations that are making the biggest strides in their AI transformation are doing this work to connect that adoption to our company goals and culture, right? It's not just adding in that line, it's being really intentional. And so for HR and L and D teams that are setting out on this journey, Kevin, I'd love to start with you. What advice would you give for actually translating those values into specific AI skills, behaviors, expectations for employees so they are actionable?
Yeah. Absolutely. I love a metaphor, by the way. So we're gonna get a lot of them today.
I think we should think of this like a marathon. Like, it's gonna take a long time. It's gonna take a lot of effort. But when you're training for a marathon, it's not just learning how to run.
There is a proper way to run, and you have to learn that. There's a lot more to that. And so in you have to know the clothes to wear, the right kind of shirts to wear so you don't chafe, the right kind of shoes, how to breathe, your mental state. Like, there's a lot that goes into running a marathon outside of, like, picking up your feet and putting them down.
Luckily, at Crunchyroll, my team is not the AI enablement team. I don't have to worry about that. They're teaching you how to run. They build all of the stuff about, like, here's some great prompts.
Here's how to make an agent. Like, that's the how to run. My job, my team's job is all of the things that surround that, and those are the behaviors of kind of how to use AI. And that's really where adoption comes from.
That is that is the value. So when I think about it through that lens, curiosity, that is teaching us to think a little bit differently, to think critically, to review all of the outputs and think, like, is this good? Can I do this better? Leading into Kaizen, what can we do better?
What can be automated?
What can we do differently now that we have all of this time from, like, data analysis? We don't have to spend a week doing data analysis. We can do it in an hour.
Courage is one of my favorites. So we have really, really passionate people working at Crunchyroll. Whether they come in as anime fans or not, they are wildly passionate about our content and our fans. And there are certain things that we will not use AI for.
Like, it will not touch our content. It like, it is sacred. And anytime we are using AI in a way that is new, we have people who are courageously stepping up and saying, we can do better. This isn't the right way to use AI, and everything rallies behind them.
It is a really cool thing in our culture of people speaking up. And then service, like, how can we be better to each other? We have a lot of interdepartmental services within Crunchyroll, and AI kinda makes that easier to manage at scale, especially as we come become a global audience. And so what we're teaching in l and d, talent management, whatever your department is, is really how to think and behave around AI.
A lot of that is critical thinking, but we could take this in a bunch of different directions.
Yeah. And, Kevin, is that happening in informal spaces? Like, you have learning tracks dedicated to these? Is it more informal social learning? What does that look like in practice?
A little bit of both. So we've got we've got some formal things that are being built.
We have a lot of, like, one off bespoke things where we go into a team. We learn what they're doing. We host, like, workshops or webinars or, like, build content with them specifically for their use cases because every we are a one culture, but, like, there's a lot of little subcultures in that. There's a lot of intersectionality there.
And so we're kind of taking it almost grassroots as the big things get built, but we're working in tandem with, like, our communications team to make sure that the storytelling is correct. And we're working with the AI enablement team to make sure that those tools actually exist. Like the mindset doesn't matter if you don't know how to run. So like that all exists and the infrastructure is in place.
Yeah, it's really cool to hear all the teams that are involved in this. And I think from previous webinars that we've hosted, see ITs involved, some people have true AI evangelist teams involved, but it really becomes, you know, your engineering team might be involved in helping socialize things, it really becomes this entire company wide effort, which I do think helps propel that culture.
Kelsey, would love to hear how are you seeing customers translate that work? Right? It doesn't just happen overnight.
So how are we translating values into So I think one of the things that I when I'm working with our clients that I focus on the most is making sure that we're not treating AI as just you know a training initiative not a tick box exercise and I think we need to think of it as more of a an operational shift, more about strategy, a strategic operational shift.
I think my biggest piece of advice is to move away from the generic AI awareness programs and I think basic literacy is useful. Like I said, we need to start with the foundation but actually what I always push and the question I always ask is what is the problem we're trying to solve?
Of the things I always say that people are kind of like is you wouldn't buy any other piece of business software because you like the color or it's shiny or whatever and then retrofit it to the problem you're trying to solve. You need to know the problem you're trying to solve and then how can AI help you solve that problem. I think that's one of the biggest issues that I see with people we work with or not even now just at HowNow but generally speaking, I think that's what people are trying to do. It's really a tick box exercise.
So I think we need to instead align AI skills directly with your company's business objectives, your KPIs, your specific business problems. I think you need to translate your values by operationalizing them. For example, value, you have a value of innovation, I think a lot of people have that, don't just talk about it, train your teams on specific prompting frameworks that require them to challenge their own assumptions. So being the devil's advocate of prompting or the Socratic method of prompting.
If trust is a value, can bake your data security protocols or rules or guidelines into every workflow that you have so that responsible use becomes a daily habit, not just a theoretical idea.
One of the values we have at Hau now is we zig when they zag. It's the innovation of thing and I really love it. It's probably my favorite one. I think when we think about AI use and AI protocol and how we implement this, we're trying to not just do what is baked into any kind of AI literacy program. We're trying to be innovative. We're trying to solve problems in a really new and novel way. So whatever your values are, I think you have to really operationalize those so that people really feel and understand what those are and then understand how anything else we implement, particularly AI feeds into those values.
Yeah, I love that. The phrase that I'm often using and trying to help our customers think about that translation is what does this value look like when AI is in the room?
Right, it's joined us out and you know, we're not changing the values themselves, but how does that translate when AI is with us now? And being really clear about that, I love the use of operationalization, if I can say it all together, but that getting to really specific behaviors, right? That this is what this value looks like in action when we think about this with AI. I love the examples that you gave, you know, from How Now and from Crunchyroll, but I think we have to help with that translation effort. We can't just continue to say, Be curious, and people don't know what that looks like now that we have these new tools available to us.
I think the other part that I, you know, from this training side of the house that I'm really trying to encourage people to lean into that helps with this translation is thinking about these moments that matter, which is a phrase we use a lot, but particularly those moments that matter where things have broken down with AI, right? Someone has produced work slap and it went to a client, someone got an output that they weren't sure what to do about, and we need to rehearse those moments in particular and make those feel safe or at least give people the tools to be able to address those things.
So we can't just view our values in this kind of aspirational or idealistic state, but think about what happens when those, you know, are brought into question with AI and then what are the things that we can do as an organization to help people prepare for those moments. And it might be training, it might be making sure that, you know, tools processes are in place or policies are in place, but I think those micro moments that can actually make or break a culture, right? Those are the places where I think it really can matter.
And we also have to have defined our values in that space as well.
I just wanna say I love, Kelsey, what you brought up to begin with about, like, intentionality.
I I think it's a little bit hard for for some people because AI is still so new. You know? And so when we ask about, like, what what problems are we trying to solve, I think a lot of people kinda just, like, shrug their shoulders and, like, I have no idea what it can even do. But you're absolutely right. That's how should go. But I think what we're what we see a lot in companies all over the place, whether they be, like, small or, like, massive, like, Netflix style companies, is they latched on to this idea of AI and then just bought, like, enterprise chatty p t or, like, quad package and said, figure it out. And part of that is discovering, you know, what problems it can solve, and, like, not everyone is ready to do that.
In a perfect world, we'd absolutely be able to ask those questions. I think maybe we're getting to a place in, like, the AI market maturity where people have that understanding and we can ask that question, which is good, and I hope we do that more. I also wanna mention someone in the chat.
Gosh. Did I lose it? Robert said something about trust is behind the glass. It has a predecessor, like trustworthiness is important.
In case anyone missed that, I thought that was a really, really good comment.
Yeah. I think it all flows together there.
Yeah. I think from that same comment, Kevin, and maybe we can spend a little time here, because I see where this is coming from, the idea that, you know, values can sometimes feel squishy, right? And Kelsey, I mean, you even said they can sometimes just be up on a wall, right? So what is the unlock for making those be really concrete, especially at a time like now where there is so much change and so much upheaval happening? Do we have any thoughts on how we can help make those values be a little bit more concrete? Because it's it's there's some good dialogue happening in the chat about it.
Yeah. I think you you can't dictate culture to someone. You know, like culture culture is a thing that you join that you're a part of. If you're trying to build a culture, that's something that maybe is exemplified at the top, but it's really fueled at the bottom.
And so for instance, when we take this trustworthiness comment, you do have to build trust that those values, those behaviors are something that the company actually wants to see. And that means executive buy in, executive demonstration. Because if we talk about curiosity and then our top leaders do not show curiosity, no one is going to show curiosity. Even if the people at the bottom really want it, the people doing the work, it has to be led from the top or at least exemplified from the top.
So they can't just opt out of the culture. And I think part of I don't know if this is a bad thing to say, but part of our job in HR, working with leaders, partnering with leaders is making sure that regardless of how intelligent someone is and how good at their job that they are, if they are detracting from that culture that we wanna see in the business, like that's something that we need to give feedback, train out.
There's a lot of avenues there, but like that's part of the role of HR.
And so we should be making sure that we are helping to grow that culture.
I agree with you, Kevin. I I think absolutely the direction has to come from the top. There has to be executive buy in. They set the standard, and it has to be clear everyone in the company that that's happening. But at the same time I think the actual execution comes from middle management because that's who is leading teams, that's who's closer to being on the ground and I think that's where really the culture, the buy in from everyone comes from. So yes you need the example at the top but actually the execution that really sets the culture and really sets the example and really makes sure everyone in the company is doing it is from the middle management level.
And so when I work with our clients at HowNow looking at their learning strategies, most of what I do, talk about all kinds of strategy, but one of the first things I ask is how are we going to involve the management? Because that is what sets the standard. That is who's talking to people day to day. That is who is setting the example for everyone.
So I agree. You you must must have buy in from the top, from the executive c suite leadership, whatever you call them.
But I think in the day to day, the people who are executing on values are the people in the middle because they set the standard for their teams and they need to exemplify it and that creates the standard for all of the people who report to them.
To build off that just a little bit, I wanna clarify executive buy in. That isn't just like, you know, your SVP of IT and security rubber stamping, yeah. Cool. I like this. That is actually creating a space for it. Like, the the top leaders are the ones who create the space. The leaders in the middle demonstrate it, and the people at the the rest of the company get to, like, do it.
But if we say, for instance, that our our value is curiosity, and so we wanna learn new things. We wanna take time to maybe fail a little bit and try something different and, like, step out of our comfort zone. But we don't actually create a space at the top where we're letting things move maybe a little bit slower so that we can try something new or we create dialogue so that people can ask questions and be critical in the way not of criticizing, but really asking the questions like, how did you come to that answer? Why are we doing it this way?
What is the problem we're trying to solve? Like, if the executives aren't showing that, then it like, they create the space. And then the you're right. Middle leaders are the ones who, you know, role model.
You're really good at this, Kevin.
Oh my god. Thanks. I should be on the panel.
No. I love that. And I I it's it is a it is a complex, you know, system that we're working within and I love the levels that we're talking about. I love, Kevin, the role that you talked about we play as HR and L and D leaders in terms of naming some of those things and that being a responsibility perhaps that we need to hold a little bit closer in terms of naming when we see values misalignment or that there are spaces where our values are not able to show up. How do we enable those leaders to signal or model those values better or unblock spaces where values can, and they might not know, right? And so how can we help be those people to influence at that variety of level so that it can happen a little bit more smoothly? Because yeah, if we're saying we value judgment, but the actions that we're showing actually value speed, that starts to get a little complicated, especially with with something like AI.
At that point, we might as well at least just say, hey.
Our value is getting **** done. Yeah. You know? Change the value if if that's gonna be Yeah.
Exactly. And that might be that might be the solution. Absolutely. But being able to have those conversations, and I love naming the role that we have in that.
I do, Kelsey, want to go where you were headed, which is to talk about middle managers next or just managers in general, which I do truly think to be the unlock we've heard from other leaders in this space like Josh Berson, this idea of a super manager, which is that the role of managers changed in this day and age. They're playing obviously critical roles in any change initiative, but especially in one like AI that's really shaping roles and expectations and truly the architecture of how work is getting done. It's it's different now. So Kelsey, love to start with you. How do you think we can help make leaders better ambassadors for AI change and equip them to model what good looks like?
Yeah. Yeah. Good question. And we love a Josh Berson quote. Are we in a tech convo if we don't quote Josh Berson?
Gotta come up. Yeah.
To answer your question, I think leaders or leadership can't just be cheerleaders for AI. It can't just be like, Kevin was saying, it can't just be like, woah, worth it. Yay.
I think they have to be the first to use it and then the most transparent about how they're doing that, what that looks like, what it's doing for them. I think we need to shift managers from being the information gatekeeper, to speak, to performance coaches. And as a learning person, really learning shifting, learning and development is shifting into performance enablement and that's what we need to be able to do. So I think equipping them with the, I'd say the specific data they need to be able to coach on AI adoption, not just the completion stats or whatever, but insights into how their teams are using AI to solve specific business problems. I'm always going to come back to what problems are we solving because otherwise I don't see a point.
But when a manager can sit down with a direct report and say, I personally use this tool to streamline my reporting process, let's look at how you can do exactly the same thing for your project, whatever it is.
I think you turn leadership into the primary engine of AI adoption, and that's what we're trying to do. So I think that's a huge, huge shift we need to see in Teams.
I love I love everything that you said. And so I'm going to say yes to all of that and, like, put that aside because, like, I I don't wanna reiterate everything you just said because you are a million percent correct. I think the other side of it, and I'm I kinda wanna think about, like, intergenerational workforces. So we have we have people entering the workforce who are kind of growing up in their career with AI.
Like, I I know some younger people at the at the company who, like, in their personal life, like, everything gets asked to AI. Like, they use it everywhere in their life. And so when it comes to doing work, they also, like, are really good at that. You know?
And sometimes, like, leaders are overwhelmed with work at every company. Like, find me a leader who has nothing to do. And, like, I don't know any at least personally. You know?
Like, they're all doing so much. And it can be really hard to be like, okay. I'm gonna stop everything that I'm doing, and I'm gonna go learn this new tool. And you've got some that will, and they'll influence others, and they'll be your early adopters and your early majority, and we gotta, like, prioritize them for sure.
But I think the thing that, like, we can focus on in L and D is teaching leaders to be, like, humble and curious. Right? So, like, admitting, hey. I don't know how to solve this problem.
Does can anyone help me do that? Like, I don't know for well, I do. But, like, maybe I don't know how to run this report better with AI. Like, my entire career has spent, like, doing these reports in a really manual way, and it's really difficult for me to start a new a new neural pathway and, like, learn a different way of doing this.
Can anyone solve this for me on my team? Like, are you able to do this, like, in our one to one? Like, hey. I I delegated a task to you.
I think it should be done this way. Would you approach it differently? Do you wanna take some time to experiment? Like, maybe we slow down a bit and you come to me and teach me something.
I really like to take it with my team that way. Like, my team has taught me so much. They **** ** away sometimes with the things that they, like, pull out of thin air, and I'm like, I didn't know we could do this. And I think teaching leaders to be a little bit more like that where we're coaching we're coaching our teams, but also admitting that we don't know something, I think really builds trust. Like, if I show up in a room and pretend that I know something I don't talk about, no one's gonna trust anything that I say. If I lead with, I have no idea what I'm talking about, who wants to take this, I think that welcomes everyone into the conversation.
I am gonna go to the other side. If if y'all haven't noticed, Kevin and I are really good at agreeing and then saying opposite sides of things.
I think one of the other I I again agree with everything you're saying, but I think part of the other side of that. So we at How Now, we have the L and D Disrupt podcast, which I'm a co host of, no big deal.
But one of the things that I talked about recently on the podcast was exactly that, about how people who are entering the workforce who are earlier in their careers are really good at AI. They've grown up with it, they know it well, they are much better at it than I am or oftentimes middle managers, senior leadership, what have you. But one of the things that is important to think about especially when it comes to values but anything is the skills we're losing. Like I was saying earlier, it's those foundational things where we have to be careful that they're not missing out on that.
Those foundational level skills. I think one of the things about AI that I'm always talking to our clients at How Now about is the quality control and I use AI all the time but I've been in my career for a very long time and so when I ask AI to do something I might say oh this is crap.
I assess it and especially when it comes to something like values that's really how we operate as a company.
They won't necessarily have that yet and so I think everything you're saying is correct, but I do think it's important for us to think about when we have newer employees to the workforce who are very AI educated, but don't necessarily have the foundational work skills to be able to assess the quality of what they're doing.
Yeah. I have I know someone who is a she's a graduate professor, and she has students coming in, and they're they do coding and engineering and all these things, and she's like, they spin up all their code and AI, and it doesn't work, and they're having a really hard time being able to identify why it's not working because of that gap of, you know, well, we didn't do the manual work to get there, so we don't necessarily know what parts and pieces are broken. So she's sharing it's a very interesting journey for her figuring out how do we help kind of bridge that gap when that experience is so influenced by AI.
Yeah, and it's an interesting one when so many of us have curiosity as a value and we want to encourage experimentation and innovation, but how do we make sure those guidelines are there? I think it's a really interesting problem to solve.
I have not seen that anyone has a brilliant answer yet, but I'm I'm if if someone has one, I'm very open to hearing it.
Someone's got it. Put it in the chat.
I I feel like I feel like not to, like, skip ahead.
We have a question about, like, the clash of Let's do it.
Like, I I think I think we're already starting to, like, answer it a bit. And, like, there is a point where, like, AI can absolutely clash with culture and values. And Kelsey was totally correct. Like, curiosity, I think of that all the time because, like, slop in, slop out.
I I think I think we have all seen work that was so clearly made with AI, and you're just like, wow. That's garbage. And while AI really, really can accelerate curiosity, it also can be like the death of curiosity. And so, like, not not to, like, throw frameworks at people, but I I see it as this, like, twenty, sixty, twenty distribution.
Like, the first twenty percent of our work should be done by a human. The next sixty use AI, and then the last twenty is the most critical is done by a human. It is reevaluating everything that was done by AI with a very, very critical eye. And when you're in a meeting with other people, and it looks like something was thrown together with AI, being a little courageous and asking the question, hey.
How'd you come up with this? Like, what is your actual thought behind this? And if it's not defensible, it's not good enough. You can tell that they they weren't actually putting the work in.
And that's where I think, you know, l and d really steps in here. At least at Crunchyroll, our l we have a lot of functional departments in the business, but, like, learning and development is centralized in the people team, and we're very behavior based. Very soft skill, very behavior.
And, like, those are the things that we focus on is, like, behaviors around using AI. It's everything in the marathon other than running.
Yeah, and I agree. I would add that's precisely what culture is about is being able to set that standard where you get to ask those questions and you get to say, wait a minute, this doesn't make any sense it is the sloth why are we doing it this way what is this output and I think that is a critical component value whatever you want to call it around implementing AI in your company is the ability to like we're talking about curiosity and innovation and that's super important but to your point around how it can crush that it's really important as we're implementing this to make sure part of that culture and part of our values are being able to say no this is crap.
I think you're totally right. Think that's a huge component and I want to make sure that as we're going through this change, because as you said earlier, Kevin, this is a change management process and a change management piece, that part of that change is making sure our values are related to asking questions and challenging and being able to say, no, I don't think this is good.
Because I think that's a huge part of this. If we skip it, we're gonna probably end up with crap.
Yeah and to your point Kilsame, I think it's it's not always something that our managers have been trained to do really well or enabled to do really well. It's that performance coaching piece that you talked about that I think historically in a lot of organizations gets kind of brushed over your, you know, it becomes task management as task management, right? And the role of that manager has really changed. And not only do our managers have to be AI fluent themselves before we can say, go out and model good behavior and challenge AI slop and do all those things, right? We got to get them upskilled first. Their seniority does not necessarily mean they're ready.
And then we're saying this layer of responsibility on top of it, which is you're a judgment coach, you're a performance coach, you are someone who has to make, you know, the decisions about sending people back to redo work potentially. That's a lot to put on that layer.
And I think that's a huge and important piece, which is that these are building really strong management skills, and AI is part of that. It's it's happening to all of us whether we like it or not. But I think the stronger our managers are, the better AI implementation will happen and the more we can display and show and maintain our values and our culture.
Yeah, I think there's a really interesting study that I came across recently from McKinsey and their newest guidance on this is that successful AI transformations follow this one, three, five pattern. So for every dollar you spend on the agentic technology, you should spend three times that on process redesign and five times that on capability building. Five times that.
Like that shows the investment that is needed at that manager level to make sure that the technology has the return on investment that we think is in place. Like that just gave me goosebumps. I'm like, talk about injecting the need for L and D, you know, into the space.
And so anyway I just think that's a Everyone quote that when you're asking for budget.
Everybody throw that out there.
Okay, I do want, we're getting to the top of the hour already which is wild and so do want us to get to maybe one additional closing question, which is really just thinking about examples. Kelsey, I'm going to come to you first and then Kevin, you can share a little bit about Crunchyroll specifically, but we've talked a lot about how, you know, AI upskilling itself is a priority. So those manager skills, but also just the fluency and being able to use it responsibly, and so Kelsey, would you be able to share some examples of how your customer organizations are connecting their AI learning, and adoption efforts in some meaningful ways?
So Kevin's one of them, so I'll let him talk about it.
But I think primarily our ethos is how now we think we encourage organizations to abandon that one size fits all training model in favor of the role based pathways that map directly to their culture. So we want to understand, like I said before, what is the problem we're trying to solve? How can AI help you solve that? And then we can design learning around that. So for instance, I would say we see our most successful customers move away from those vanity metrics, logins, and that kind of thing and toward more outcome based metrics.
So the ones that reflect their organizational values. What is it you want to achieve and how does that contribute to your values? How does that contribute to your culture? So many of our clients that I talk to really want to have a really strong learning culture and so we talk about what does that mean for you?
How does that connect to your company values? How can we deliver that for you? And then how can we structure learning around that. So we see things like revenue teams connect AI to customer excellence or they want to be able to use AI to draft really hyper personal or personalized empathetic prospect outreach.
Operations teams want to connect it to a value around efficiency, So they want to standardize their SOPs. They want to make sure that they have the automated workflows to do that.
But I do think the most successful teams that I work with have a really clear connection to what is it that their business objectives are trying to achieve, how do their values influence that, and then we can design how can AI solve those problems and then we design learning around all of that.
Yeah, like the idea of building kind of backwards into those things and making sure there's continued alignment rather than just reactive, you know, builds like, oh, well, everybody's building agents now, so we need an agent.
Well, that's how a lot of people come to me and I say, no, no, no.
Slow it down.
No, Let's let's go back. What is the problem? And we work our way back from there because we can use AI to solve these things, but we can't like like I said before, you wouldn't buy any other business tool. You wouldn't buy a CRM because the color is pretty and then retrofit it to your problems. We need to know what the problems are and especially the values as to how you work as a company, how you work as a team, then how can AI solve those problems, and then we can construct learning around that.
Yeah. I did buy my first car at like seventeen because it was blue. And I was like, oh, it's blue. I love this.
Awful car. We learned the lesson.
Paying way too much for it. But, like, yes, you're absolutely right. That is that is the wrong reason to implement something. So at Crunchyroll, there's a lot of we're owned by Sony Pictures, and Sony Pictures is, you know, a big entertainment company, is also very, like, old school, conservative, like, in their practices, risk averse. And Crunchyroll is the, like, you know, innovative thing that pushes the envelope. And we we work together a lot with, like, PlayStation and Sony Music and Sony Pictures, which is very cool.
But the Sony environment has a lot of really strong what what do we not want to use AI for. And, like, there's so much guidance on what we will not use AI for. Like, it's which is very important, I think, because sometimes acknowledging the constraints helps us be a little bit more creative. You know?
Like, when you're when you're playing a game, having the rules and the win conditions make winning easier. You know? So, like, we have so much guidance on what AI will not touch and what we cannot do with it. And then I don't actually do the enablement of AI because we have a very, very talented team that is not part of HR that that is driving AI adoption.
But one of the things I really respect about their approach, step number one, IT creates like, builds the tools. You know? Like, they get them out there. If you build it, they will come.
That gets you your your early adopters so people can, like, play with it and have, a playground. But that playground doesn't necessarily give you a playbook of how to use it. That's what your early majority is for. And so we're kind of in that mid early majority stage, I would think right now at Crunchyroll.
And our AI adoption team started by building a whole bunch of, like, here's how you build an agent and, like, all of the, like, broad spectrum training that you would need to learn how to run. And now they're doing, Kelsey, really what you talked about, which is they're going department, sub department by department and being like, what do y'all do here? Like, what what is the work you're doing, and how can we help you with that work within the guidance that we have as a company? And I think that's that's being really effective.
Because if we try to tell everyone in the company, make some agents. The work I do in l and d is so different than other people in HR, in talent acquisition.
Compare that to the go to market team, the business development team, they're wildly different. And so you can't just train them all the same way. And I really love that the enablement team is going department by department.
First, to train them on, like, here's what AI could do for you, then let's hear what you're doing currently, and maybe here's some ways that we can help, which takes a while. You know, they're a small team. It's not gonna happen overnight. It's probably gonna take a couple of years to really solidify the culture, but culture doesn't change overnight either. You know?
And so, like, that, I think, is being very effective.
I think what's interesting that you said, Kevin, is that one of the things I haven't thought about with the teams I work with is what won't AI do? What won't we allow anyone to work with AI?
And while I always take a problem first approach, I think that's a great question to ask because it is a very specific line. We need to think about all we can do all these things. We have values of curiosity and innovation and that's all lovely and wonderful. But I think we do need to have a really clear line about what won't we do with AI and I think that's a really important question to ask and something that's really valuable to teams who are trying to implement it.
Wish I could take credit for it, but I can't. It's just where I live. Yeah. It's a really cool thing that Crunchyroll does.
Well, wanna thank you both so much. I think we can kind of end the conversation with, know, Kevin, I love that you said culture does not change overnight and these AI transformation efforts are not going to be over overnight, right? This is going to constantly be an iterative and discovery based process for all of us. I think everybody who's on the line, you're out there doing the work on the ground and, you know, are helping to pioneer this space and create best practices that all of us are learning from. So thank you all so much for being here, such amazing participants. Thank you so much to Kelsey and Kevin for being on our panel today and for sharing everything that they have.
Best of luck to everybody out there and we'll see you on our next webinar space.
Thanks everyone.
