Name: The Edge: The Leadership Engine: Building, Measuring, and Scaling Talent in Today’s SMB
Uploaded: 2026-04-15T19:10:28.270Z
Duration: 40 min 12 s
Description: The Edge: The Leadership Engine: Building, Measuring, and Scaling Talent in Today’s SMB

Transcript for "The Edge: The Leadership Engine: Building, Measuring, and Scaling Talent in Today’s SMB": Thank you for taking the time to join us today. As AI becomes more present in the workplace, many small and medium sized businesses or SMBs are evaluating leadership readiness, workforce skills, and how teams are adapting in practice. In this session, we'll share perspectives on workforce transformation and a human centered approach to AI adoption. Please use the chat to say hello and help us welcome TriNet's chief talent officer, Kathy Manginelli, executive director of client HR consulting services, Jackie Breslin, and director of organizational development, Kristin Russom. Hi, everyone, and welcome. Thanks for joining us today. We're gonna be talking about AI talent strategy for small, medium sized businesses. How do we close the skill gap, in building an AI ready workforce? Couple of housekeeping before we get started. This session is being recorded. The replay will be accessible with the same link you entered today. We have companion resources available for download in the docs tab on the right side of your screen. I want you to feel free to ask questions as we go through this. Put them in the q and a tab so they don't get lost in our chat feature, And we're gonna hopefully reserve a little bit of the time at the end, but I know we've got lots of questions for our panel today, so we may not get to them all. I also have a couple of polls because I really wanna understand what you're feeling out there as it relates to AI. My name is Kristen Russom. I'm the director of organizational development here at TriNet. We work with our clients specifically on how to attract, retain, and engage their employees, and our focus is every day helping our customers to do better. I wanna get started. This conversation is really anchored on an HBR study, which was sponsored by TriNet, and we see a really clear study. AI adoption is accelerating really fast. 76% of SMBs are planning to increase AI use in the next twelve months, but there's a big readiness gap. Only 19% feel highly prepared to acquire the AI skills they need, And nearly every SMB anticipates meaningful impact. So 78% anticipate evaluating how and where AI can be used, 49% expect changes in existing roles, and only 3% of the entire population that we talk to expect to have no impact at all. So today, our conversation is about moving from interest to execution. And specifically, what are those talent strategies that will determine whether AI becomes a multiplier in your organization or creates additional frustration? So before we get started, I've got a quick little poll that I wanna ask. Where is your organization today with AI? Got a couple of options. Are you exploring and learning? Are you piloting in one or two areas, using informally across your teams, operationalized with clear processes, or not started. No wrong answer here, and I'll give that a few seconds just to get some responses into the queue. I know it's tough when we think about AI because it's so new. And if I have were to ask this question six months ago, your responses would be vastly different. And I'm certain if I ask in six months, your responses will again be vastly different. Alright. So we're seeing some responses come in. Again, no surprises. What I hope everyone can glean here is that every organization is somewhere on this journey, and so you're not alone in how you're approaching AI or even where you are in your journey. I wanna talk then to a couple of our panelists that we have on here. And, Kathy, how about I get you started if you'll introduce yourself, and then we'll go to Jackie. Sure. I'm delighted to be here, so thanks for having me. My name is Cathy Manginelli, and I'm the chief talent officer here at TriNet. Wonderful. Thanks, Cathy. Jackie? Hi. I'm Jackie Breslin, executive director of client HR consulting, and super excited to be here today. Wonderful. Well, Jackie, I'm gonna put you on the hot seat. So Alrighty. Yeah. Already. Yeah. Let's jump right in. What's one part of talent or operations that AI has changed most in the last twelve months? Okay. So this is a, you know, a great question. Not an easy one. One that I did into. I think it's what we expect people to be able to do in their existing roles. And over the last year, SMEs haven't really been creating lots of new AI jobs or roles. Instead, they're really expecting employees and managers to work differently. So AI is becoming part of how the job gets done, which what we're really seeing is it shifting the mix towards judgment, oversight, and knowing when and how to use AI responsibly. Mhmm. I think that is that nails it, Jackie. There's still so much ambiguity right now around this, and every organization is doing things slightly differently, I guess. For sure. I yeah. And we we're seeing that right in the poll results. Right? So folks are kinda telling us it runs the gamut. And I think, at TriNet, I can speak from the TriNet perspective. We're also in that same space. So there's some areas that have have gone fully immersed and are using full utility and some that are still testing and learning and some that Mhmm. Probably haven't even touched it yet. Yeah. Absolutely. So even within our own ecosystem, we've got that whole gamut on that pole. For sure. So I'm gonna as the as we go through this conversation, I'm gonna flash up a couple of stats because I think it's difficult for us to keep all of these numbers in our head. But the study found that 76% of SMBs plan to increase AI use in the next year. But as mentioned, only 70 or 19% feel highly prepared to acquire the AI skills, and that's a huge gap. So, Jackie, I'm gonna ask you this question. Where do you see this readiness gap showing up the most? Is it in hiring, training, leadership, or somewhere else that I haven't even mentioned? I just wanna say yes to everything you're saying because it's it's a challenge. But the the readiness gap, it really shows up in skill clarity and I think in leadership confidence. Mhmm. Yeah. Many small businesses are moving quickly with AI AI tools, but leaders aren't really clear on what skills actually matter in the day to day roles or how to coach people to use AI well. And so what we're seeing in as a result, employees are experimenting, but managers aren't fully equipped to guide quality or judgment or consistency amongst them yet. So that that confidence gap at the leadership level is what's slowing can slow things down, you know, can slow down all the rest of it, the training, the governance, and even hiring. So, I'm gonna land on leadership confidence right now. Ask me again in a couple months. I was gonna say, I'll we, you know, we could probably have this particular conversation every other month and have completely different responses every time we think about it. Alright. So I'm gonna go back to the stat that I mentioned earlier. Nearly every SMB expects some sort of meaningful AI impact in their organization. 78% say they're gonna evaluate where AI can be used, and 49% expect roles to change, and only 3% expect no impact. So as we think about this and, Kathy, you you kind of led into this a bit already talking about where it's sitting in TriNet. What is one area that AI is already reshaping the work in a very concrete and practical way? Yeah. There's there's many, actually. And I would say, certainly in my purview and in the talent acquisition organization, we are, using AI tools, chatbots, and and methodology all throughout our life cycle from hiring to onboarding. So that's a concrete way that we're using it through the sourcing selection, interviewing, evaluation of the interviews, all the way through to helping us develop, the job offer and even job descriptions at the beginning of the process. On the business side, we are seeing a lot of adoption on the sales in the sales organization where they're using a lot of, AI capability to prospect, to narrow down the prospects, to understand how to, really identify who that target market, communicate with them, and make sure that it is the most useful interaction and best interaction they can have. So, so we're seeing a lot of places About a year or so ago, don't quote me on that timeline because as you said, days go quick here. But we, TriNet launched what's called AI forward, which is essentially this really interesting initiative across every aspect of our business. If you wanna participate, you wanna get involved, you wanna learn and grow and and how to, you know, get more AI fluency, you can, you know, participate in it. And so through that initiative, we're seeing all kinds of really interesting things pop up and and interesting ways people are using the tools and and integrating it into their into their work. I love it. That word interesting kept popping up. And I think that could also be translated as creative or maybe Totally. You know, sort of out there a little bit. Yeah. One one one person I was talking to this week, you'll appreciate that, they said I'm learning through the struggle. And I thought about that a little bit, and I went, yeah. Me too, actually. I'm a little bit of. Right? Yeah. And so I think that's what it's about, right, is is you have to, it it's it's it's being creative in a completely different way, honestly. I love it. Thank you. Alright. So I wanna just circle this back around. And, you know, we mentioned creativity, but they're also AI tends to create some confusion and some real risk. And I think that's one thing that a lot of folks haven't even landed on, like, how much risk is out there. When you think about this, Kathy, what's the biggest misconception that SMB leaders have about AI and most specifically about talent? Well, I think I mean, the one that everybody hears about is it's gonna replace jobs. Right? Everyone's saying it's gonna replace jobs. Philosophically, we believe that it's going to amplify jobs. Right? It's it's AI and, you know, it's it's human in the loop. You might hear that term out there in your research as well. So, it it's it's gonna change jobs. Yes. And do are we seeing out in the workforce some job impacts as a result of having new ways of working? Of course. I don't think that anytime we're we're introducing I think about the Internet. I'm old enough in the workforce to remember when the Internet When there was a job. Yeah. Right? And so, you know, people were it was sort of the same psychology. People were really afraid of it. They didn't really know what it meant. They didn't really know how it was gonna change the way they're doing things. And I think we all can stand here now and say we're we're better for it. It just took a minute for us to, learn through the struggle. And so I think, you know, I think it's that's one of the biggest misconceptions. The other misconception I'm hearing out there is that it's a tool. Yes. It can be, but it's also bigger than that. It it it it's it's rethinking the way that you work and having something enabled working alongside you, right, in a in a different way. And so, it's it's not it's not Google two point o. Right? It's not something that is you just you know? I think I think it's okay if you're using it like that to start and to learn and to to test. But I think, you know, that's a a misconception. And and to your point around governance, anything that is new to us can be scary. I think about the first time I went down a roller coaster. I was not excited about doing that. And my daughter I'm sure there was, Kathy. Totally. My daughter convinced me, and then I was like, can I go again? You know, it's just it's like that. Right? So it's it's making sure that you've got your safety belt on. It's making sure you've got someone to hold on to. I held on her hand really tight. It's making sure you kinda understand what's coming in front of you so that you can anticipate and put the right governance structures and guardrails and and, you know, to something that Jackie was saying as well is, like, you have to kinda help people through this journey a little bit and and bring that clarity because the more clear you can be about the what, why, how, and where, I think, I think the more comfortable you'll be and the more successful. I love that. I love the roller coaster analogy, Kathy, because it it makes me think. My mind always goes to risk mitigation that, you know, roller coasters aren't just the wild, wild west. I mean, they've got safety protocols, and you have procedures and processes and things that you do. And I think that that I mean, we'll touch a little bit about that, a bit later, but, you know, having those guardrails up around appropriate and inappropriate use of AI certainly is something that we're gonna have to see evolve rather quickly. For sure. Yeah. Alright. So we know adoption, moving fast, but the clarity on what skills are necessary is still very lagging. The study shows skill definition is a top barrier. In the study, 56% of SMBs say their biggest challenge is determining which AI skills they actually need. So, Jackie, I wanna turn to you, and I want to think about or tell me what how you think that SMBs, you know, the leaders should decide what AI skills matter the most without getting lost in this hype or over engineering it. Oh, and everything's so seems so tempting too. And Let's do it all. Yes. And this afternoon. Right? Mhmm. I I think that leaders, SMB leaders, like, they really may wanna start with the work, not the technology. And and what I mean by that, instead of asking, like, what AI skills should we train for, that's important, but it's not the first thing. But asking really, like, where does work slow down? Where is it breaking down? Where could we use better judgment, you know, in the work that our employees are doing and really define the skills needed to support those moments. So in in most cases, that means focusing less on techno technical skills, but really more on practical capabilities, like knowing teaching employees, like, knowing when to use AI, how to review the outputs, how to apply judgment and accountability. And and I think, like, if leaders were to anchor around these skills around real workflows and decisions, it it prevents, like, getting caught up in the hype and the shiny objects and over engineering things. But really thinking about today, when you look at your team, what is slowing us down right now? You know, that that expression, Jackie, you know, like, the go slow to go fast Mhmm. Seems so appropriate right now while it it seems like you you know, you're already behind the the, you know, behind the curve when you haven't started your AI journey, but maybe that's not a bad thing. Maybe you really do need to have a little more planful approach to it. So we see the talent strategy shifting fast. And my next stat that I have is 56% of SMBs expect to train or develop employees differently, and 37% expect to change the skills and experience they look for in those candidates. So, Jackie, I wanna stay with you still. What are the biggest skill shifts you're seeing, technical and as well as human, like the judgment, the communication, adaptability, ambiguity, all of those all of those words? So on on the technical side, it's less about deep AI expertise and more about practical fluency. I think, Kristen, even, like, you and I having conversations about this topic a year ago, it was more about, like, our clients were telling us, I need to find people with really deep AI expertise. We don't have it. We're gonna hire for it. But I think a year later, here we are. It's really about practical, like, knowing how to work with AI tools, understanding data basics, recognizing when outputs need to be questioned or validated. And then on on the human side, it's it's back to that idea about about judgment and communication still. AI takes on more of the task, and people are being asked to explain decisions, like why is the data this way, applying context, and really adjusting and and evolving. So, like, let's make sure we're helping our employees being able to communicate what's coming out of AI tools and and explain it. Yeah. It it sort of gets that honesty too, right, of being able to be candid about why I used AI for this, and and here's what I did with that as opposed to maybe passing it off as their own, you know, independently curated work. Right. Or embarrassed about it. Right? Too. Like, like, let's open up the door too to to be you know, once somebody's using an approved AI tool in the organization, then, you know, like, saying that you did. Like, that's okay. Yeah. Yeah. There's a there's a framework that I've been using with my team quite a bit called Vatt, v a t t. I don't know if either of you, are interested. Yeah. You know, it's it's just like I don't know. I'm a I like acronyms and stuff, but it it it really speaks to what I think the two of you are talking about. So so the v in that stands for voice. So when I am using AI, it's it's it's learning me. Right? And it's gonna learn me more because it is machine learning. So I have to, first of all, be nice to it. Nice to thank you. Right. But but also, give it the expectations and context. The more you can give your AI partner context, the better off you'll be. Mhmm. And then audit. So I have to look and make sure that what it's what it's the inputs and the outputs are, representing that voice, that tone, what I want it to, to complete, how I want it to complete it, what I'm looking for in terms of, the output. And then the the last two, which is what I I'm hearing both of you really talk about, and I so agree, is transparency and trust. So it's the transparency around, what I what I instructed it to do, what it did, how we're working together as a partner, and then trusting in that partnership. And so it's interesting when you talk about the leadership skills and kinda training our our people managers for, how to how to support, you know, colleagues, employees through this. It's it's supporting machine learning as well. And and, you know, I'm also the head of talent acquisition in my role, and I when folks tell me, you know, they they wanna hire this expert, they wanna hire an AI expert, there's not many out there yet. I have to be honest. And part of it is because we're all still learning it. Right? And it continues to change and evolve and and move faster and sort of the you you have to learn faster than the pace of change, I guess, field adage. But, so it it's it's not like there's some golden key box. Even these certification programs that are out there, they're good, But what they're gonna teach you is how to learn. They're not gonna teach you, AI. They're gonna introduce how to learn using, a a sort of different methodology. And then, you know, staying curious at the end of the day is, to me, always the best the best skill you could, you can have and and and question everything because you that's where the innovation, really lies. I'm so excited listening to you, Kathy, because you're painting this great picture where we become we we have our expertise, whatever it was before AI. And then but what if we could be both? Like, right, what if we could keep our core discipline that we know and maybe love so well along with increasing our a r AI expertise? Like, that, I feel like is makes our role so much more exciting even. It it it I I look at it as augmentation at the end of the day. Mhmm. Right? So how can I just do what I'm doing better, more efficiently, more effectively, with with a partner? Mhmm. Right? Yeah. I love that partnership word. You know, Cathy, you mentioned this. You know, one of the things that we do on my team is we research. What are the trends? What should we be doing? And we had AI as one of our trends last year, as sort of a wrapper. This year, it actually went to number one, but we the caveat being that we needed the human element in AI as our primary driver. Like, you can't lose the person and and think that you're going to be able to just completely turn it over to this partner who can do everything without oversight and judgment and, you know, that perception on things that are working or not working. I love it. Yeah. Alright. Yeah. 100%. I I vehemently agree. I've got another fascinating find, and that is that 52% of SMBs say that if they could hire one employee, they would prioritize industry specific experience over AI expertise. And 37% say evaluating AI skills in candidates is a top challenge. Like, they don't know what skills to ask for. So I've got another poll for the audience. Can't wait to hear where everybody is on this journey. And the poll is, how do you balance domain expertise versus AI capability when you're building teams? And practically, how do you evaluate whether a candidate can work effectively with AI tools? So our four choices are industry specific experience is a priority. There's a balanced emphasis in your organization. Maybe AI fluency is the primary driver for that. Or d, kind of that middle of the road. It depends on the role and the maturity of the team. So as we wait just a second for those responses to come in, I have a feeling, I have a gut on where this is gonna land, so we'll see. Alright. So as these as these responses come in, I mean, you know, again, I think if we were to ask the same question just like the first poll, if I ask this in three months, the question or the response could be vastly different, but we're really, you know, primarily sort of weighted in that D category. It depends on the role and the maturity of the team, that sounds perfectly reasonable to me because not every role is well suited to AI right now. And the team honestly may not be mature enough to start to establish and roll with things. We know that the skills are very much evolving. Acquiring them can be challenging, but let's talk about hiring and upskilling in the real world with some of the constraints that our SMBs face. This study is really blunt about difficulty and cost, and the top challenges include determining skills needed, 56%, training and upskilling employees is 49%, And evaluating candidate capabilities is 37% with talent scarcity and expensive courses intensifying it. So as we think about those constraints, what are the most practical ways that SMBs can build AI capability or fluency, particularly when they don't have these expansive enterprise budgets? So I know, Jackie, you've you've looked at this, and I wonder if you could share some of this with us. Yeah. Well, the I mean, the most practical path really is to focus on the upskilling from within and and keeping it right keeping people very close to the work. So, like, I agree with what this you know, with what's being said, and I could see it from a practical side. Instead of sending people to expensive courses or trying to hire, you know, the rare AI talent, When leaders really identify a few, like, real use cases, giving teams some basic guidance on how AI should and shouldn't be used and then building skills through hands on practice, and it can lead that can lead to success. I mean, Kathy talked about, right, our AI forward initiative here at TriNet. It's like, right, giving some practical use cases. That's part of the things that are talked about in AI forward or people who are discovering things within their own roles. So then you can pair that practical on the job use with some low cost learning, short courses, back to internal knowledge sharing, and really clear expectations about accountability. And it's not about doing everything at once. It's about building skills incrementally in ways that actually stick. And our study, you know, that we're talking about today cited a few resources to begin with up to processes including LinkedIn courses and and YouTube as a, you know, as an example. Yeah. I think, underrated some of the free online courses. I know, Kathy, when we were talking before, it's like you can do a search and get a a host of classes that Yep. You know, maybe they're not gonna go as deep as you think you need, but at least it starts to test the waters to understand, like, where do we need more expertise without having to spend, you know, excessive amounts of money or budgetary funds to achieve that that knowledge. Yeah. 100%. I mean, it gets you in the pool. And Mhmm. I think that, you know, universities are doing a lot of, free seminars. There's a lot of, different economic development type of areas. Like, I I live in the Greater Atlanta, Georgia area, and there's a ton of, web free webinars. There's a group that meets on Saturdays. It's called the AI Saturday, coffee coffee coffee chat or something like that. Right? So there's there's a lot of places where you can kind of meet other folks that are on the learning journey. And I and I can't underscore what Kristen said or excuse me, Jackie, what you said enough about the the internal knowledge share. That's huge. If you can make internal community where, you know, hey. Have you tried this? Or what did you what was the result when you tried that? Or I'm trying to do this. Anybody have an ideas for that? That social learning that happens amongst your your peers and your colleagues within the the context of your work, that's brilliant because you you you know, these outside courses are really, really good, but they're not within the context of of your organization. And culture for learning is is huge to understand, again, the context of how you're gonna be using it and where you wanna kinda dive in and what work processes you need to streamline. So I think I would definitely put my vote to start there. I I love it that you know? And and you hit on that word culture, Kathy, that that gets me because I know that there are some organizations where, you know, internal sharing and internal learning may be not part of the the normal vernacular. And so it's an opportunity to maybe even revisit some of your values to create some of that that playbook so that, you really try to foster the environment where people feel okay to fail, particularly in the space when it's brand new. And, you know, you're gonna have the the span of folks who don't even know what AI is to folks that are doing it for all of their activities. I think that's amazing. Alright. So I've got another question that really sticks with the upskilling piece because, Jackie, you hit on it. And I know that internally when we have clients come to us for compensation benchmarking and they're looking for AI, like, it's really tough to even benchmark compensation because there's not enough there's not enough out there. So it sort of lends itself to how do we upskill our employees to give them what we need. What do you think is a low lift, I guess, training that actually sticks? And and maybe you've already covered this, but would love to hear if you've got any additional thoughts. You know what? I think it's, I think it's the idea is, like, it's not a one time course or a big program. It's showing employees how AI fits into what they already do and what they're accountable for. Like, I really, like, I really like that practical idea about a real case situation they're actually working working on or could be working on, you know, not something just aspirational, but, like, a literal way in which something that they're they're focused on. And so taking these, like, short term learning moments, sharing examples, reinforcing managers, managers making it part of a team meeting, you know, bring to us what how AI has helped you or how it's hurt you. I mean, if there's a you know, an AI fail can be as interesting as something that made you successful. Oh, I have a lot of those. I have a lot of those AI fails. Right. And that feels that feels real. Like, that right? Because not everything is all per AI is not perfect and shiny. Right? There's things that it makes you know, maybe it makes mistakes, and catching a mistake is kinda fun. Right? Because then Yeah. It's like that's not right. And and you know you know more maybe than AI does, and that feels good with all the right? With everything we hear. So I I would stick to practical examples, real versus aspirational things that could be and would be done, like, you know, specific studies applying to that to that employee in their in their work. Yeah. I mean, I I think about my journey, right, my own personal journey, and I just started with, can you summarize this meeting? Like, I I I started real basic. Like, can you is it you know, what are the themes that came out of this meeting or this meeting summary? And then I was like, oh, I don't have to take pages and pages of notes? Interesting. Even though I love to take notes, I was like, wow. I don't know. Gosh. I mean, you get some of your day back just by doing that small that small task. Yeah. In my memory, you know, it's not as sharp as it used to be. And, it's too much to remember. That's why. I don't know about that, Kathy. You know? Alright. Well, Kathy, I wanna ask you another question. And you mentioned this earlier when people, you know, afraid about, you know, AI is gonna take their job. But how do you encourage adoption and experimentation without, you know, overwhelming everybody or creating this mass panic around job security? What where's that where's that sweet spot? Yeah. I I I think we were just hitting on it at the start of it. Right? Is is just start small. Find find those moments where it does make you more productive because the fact that I didn't have to sit there and and go through my meeting notes and and then, you know, produce the email, it does it all for me. It's like, oh, wow. I can actually focus my time on more value perceived value added work in this other way. And then I actually I mean, I use it personally as well. It was like, well, I'm gonna have a team on-site meeting. What would be the best way for us to do x, y, and z? And it it kinda gave me a draft agenda that I could play with so I didn't have to spend time thinking through some of those pieces. And so I think number one, leaders gotta jump in that pool Mhmm. Or go down the roller coaster, whatever the metaphor is you wanna use. Like Mhmm. I think they have to start role modeling because if they're role modeling and talking about what they're learning and how it's helping them, but also those mistakes they're making, they will create an environment for people to feel like it's okay. Like, I can I can get in there and and play around as well and start to look at efficiencies? And then, from there, just start to to continue to storytell and and grow, and you will see the power of it. I have quickly become an advocate. I was a skeptic, now turned advocate to, you know, really driving it, using it as my as my partner. Sometimes therapists, sometimes project managers, some, you know, and and all and all the things to continue to help, you know, drive efficiency. So, you know, that that's where I would say. Just just, you know, start small like any change and and and understand that it is, you know, learning through the struggle. Right? Give grace to folks as they're learning, as they're going through it, helping them give them support when they need the support as they go through. I love it. Thank you, Kathy. Those are really wise words. Alright. So I've got one last stat to show. 49% expect changes in roles and responsibilities as AI becomes more embedded. And kind of the lightning round here, Kathy, where should SMBs approach role design? Where should they start? Job descriptions, workflows, performance metrics? What's the what's the quick answer there, do you think? Yeah. Yeah. That's a that's an easy button for me. I think job descriptions. It it's we it's so much easy lift. It's so quick, to ask them to help you write the job description, and and that sets you up for for performance, goal setting, all the other pieces, down the line. So that gets my vote. I love it. Yeah. Well, that end, you can use AI to help with job description. So it's kind of a win win all the way around there. Yep. Alright. Well, I know that I I was hoping we would have time for questions, but I think we're getting towards the end of our time together. So I've got just a few questions that I wanna run past you. Okay. I'm a start with you, Jackie. What's one AI use case that every SMB should try immediately? Okay. So I think it it should be something to do with your workflow. So look at a workflow where things are slowing down and see how you could you could use AI to help get that unstuck. Okay. I love that because that operationally means things move smoother. You have less hiccups. Alright. So if you think about that, what's one AI mistake that SMBs should avoid if they can? Okay. So don't treat AI as just an off the shelf, you know, plug and play without thinking about clear expectations, guardrail guardrails, and then back to, like, the human accountability we've been talking about also. Because you don't wanna create risk and frustration. So Right. Guys are gonna be perfect off the shelf. So really, like, think think about that full picture with the guardrails and the human accountability too. Alright. Alright, Cathy. I think you've got an opinion on this move. What's one skill every employee should try to build in 2026? Well, I'm gonna I'm gonna say AI fluency, but that's just a very, comprehensive term. I think I'm actually gonna take a piece of playbook from the show Ted Lasso, and I'm gonna say be curious and not judgmental. Okay. Because that is the foundation to what I believe is, folks being successful with their AI partnership, so to speak, is if you're curious, you're gonna continue to explore, explore, experiment, learn, and grow, and test, and pilot all the things. So that way, you will continue to see the power of how it can be your amplifier in in in your work. I love it. Words words to live by. Thank you so much. This has been amazing. I think every time we have this conversation, I learn something new. I learn a different way of thinking. Even just coming up with the right language around what AI is and isn't is, always such a tremendous thing. So we know a couple of things that we've learned today. Adoption is absolutely accelerating. This train is moving fast. Readiness is lagging though, 76%, increasing their AIUs again, only 19% feeling highly prepared. Upskilling is the fastest path to capabilities, figuring out how you can bring your people along on that journey. And then lastly, human judgment is still the differentiator. If you didn't pick up on that on our entire topic today, then we might have missed that. But AI expands, it it creates creativity. It it requires discernment. It requires review and accountability. I love your VAT, acronym that you're using, where it's that accountability and trust and transparency. So thank you both for joining me today. Again, great learning. Looking forward to seeing you in future sessions, and you please look into the Discovery Zone for additional resources that helps you here. And just keep the questions coming, and those that we didn't get to today will certainly follow-up with you. Before we wrap up, we invite you to join us for TriNet's National Small Business Week virtual summit, a free three day virtual event happening May 5 through May 7. The summit features nine thirty minute sessions highlighting key priorities for today's small and medium sized businesses. Day one, smarter work, focuses on AI and productivity. Day two, stronger teams, highlights talent retention and the modern workforce. And day three, scaling and protecting, centers on navigating compliance, payroll, and risk. Register now for TriNet's National Small Business Week virtual summit. We look forward to seeing you there. If you have questions about TriNet that were not answered or if you would like more information including self guided demos, please head to the discovery zone, accessible from the tab on the upper left of your screen, or you can click the yellow meet with TriNet button at the top of your screen, and we will be happy to reach out.