S02E14 It's a Yes & conversation .. guiding your teams to use AI | Emilie Schmitz | Wired for Wonder

Speaker A: Foreign.

Speaker B: Welcome to Wired for Wonder where we speak to the architects of the future of work leaders who are using AI to dismantle the old grind and rebuild work around what actually drives results. I'm Lori Kirkland, and today I've got someone who is running HR for a 2,500person workforce across 36 states and doing it without the IT infrastructure most people assume you need to do the job well. Emily Schmitz is the Chief Human Resources Officer, Rise Claims Solutions, an insurance claims company navigating rapid national expansion. She came up through operational leadership, not a traditional HR track. She's held P and L accountability, built companies from inception, implemented Harris Systems in 90 days, and secured a 5 million service contract as a primary executive contact. She also holds a US patent and ran the full commercialization of a consumer product from invention through go to market. The through line in all of this is the same. She builds the infrastructure, then scales it. What she's wrestling with right now is one of the most honest problems in AI adoption. Her company wants to use, UM wants to use it, but her people and her people are already using it. And the IT foundation to govern it doesn't safely exist yet. So in a regulated environment where AI cannot touch claim processing, that gap is not theoretical. It's a daily operational risk. And the HR team is sitting in the middle of it all, holding people's data and a lot of unanswered policy questions. So she's not waiting for perfect conditions. She's figuring out in real time. And that's exactly the conversation leaders need to hear. So welcome to the show, Emily.

Speaker A: Thank you. I'm so excited to be here. It's exciting to talk about all of the great things that we have going on and, you know, how we are using the tools that we have and the tools that we are creating to get us, uh, into the future. Um, so it's exciting to be here. Thank you.

Speaker B: Well, good. Well, you are hitting a topic that I think so many, um, you know, leaders are facing, which is you're in a highly regulated environment. Right? Like, you can't just say like, yep, we're going to use AI for this. Everything has to fall within certain parameters. But your employees are already using it, right? You're already using it. So it, you know, for everything else around it. So what does it actually feel like for you to manage that paradox of, uh, we want to use it, but we can't? And how do we, how do you manage the boundaries around it? What's that like for you as a leader?

Speaker A: Yeah, so it's, it's a challenge, right? I mean, because we all know that everyone's using, you know, the shadow AI, they're using their tools. Um, but we don't have yet the umbrella where we can say, okay, here are the rules and regulations of how we use it. Right. We have, um, you know, a very large 1099 workforce. And, um, you know, they are independent contractors. Right. And so we can't regulate everything that they do, but we can set the guidelines of what we, you know, as a business, how we use these things and how we require them to use them. And then for our W2 workforce, it's, you know, setting up the tools so that they can use them under the umbrella of the team and use them the way that we would like for them to be used to, you know, improve processes, efficiencies. But then, you know, a lot of our employees have to have licenses, right? So in the licenses, they have to be certified. They have to go to courses and learn how to do this. And that is a coveted thing in the industry. And so we want to make sure that they're, they're using these tools properly and the way that we want. And so it's, uh, that, you know, setting it up to encourage the use, but then making sure that, um, we have the methods in place to make sure it's being used properly for. Or what we were.

Speaker B: So that's so interesting because it feels like a shift from where, how business has been done. Right. For a long time we've been like, here's the process that rise is going to give. You follow these standard procedures, go out, but with AI, and you're not the only company seeing this. Right. We're seeing this almost that certainty that was once there. Just do this process, don't care how you do it, is all of a sudden like, wait a minute. We have to put a lot more personal accountability on you, our 1099 employees, and we have to give you guidance, which is a lot, um, a lot more flexibility in leadership, a lot more room for building trust, which is great. But then also leaders have to hold it that they can trust their people. But tell me how that shows up for you in the workplace. Right. What does that look like when you're, um, talking with your leadership team around? Kind of the difference in approach from where we were a few years ago to, you know, where we are today?

Speaker A: Yeah. So the conversations that we are having are more around how can we rebuild with AI as, as part of the conversation. So it's not really, hey, this is, this is where ASI is going. How do we mold to fit AI? It's, how do we rebuild it from the beginning and incorporate AI in our daily functions? So it's really more embracing it as a whole for our teams and saying, okay, here is how we are going to use AI and we're going to give you the training and we're going to give you the tools and, you know, we're going to give you the framework of how to use this in our systems and then, uh, in external systems. But it's not. We're not having the conversation around how do we adapt and how do we fix. We're having the conversation around, all right, how are we going to rebuild and integrate AI at the core of how we operate? And not how are we going to, you know, start using it over here and using it over here? And it's really those conversations that we're having around, how can we just from the beginning use AI properly for us, for our clients, for, you know, for all of these things? And it's really the rebuild that we're having the conversation around. And it's really exciting to be a part of those conversations, but also can be daunting because you're not just looking at, okay, well, let's start using this tool for these four things. It is, how can we rebuild completely how we operate so that we can work with efficiencies and, you know, integrate with our systems, keeping AI in mind at all times. And how are we, you know, it's almost like looking at the book from a new perspective of, okay, how are we going to redo all of this process that we do have to follow. Right? Our clients have very specific guidelines around what is allowed and what is not allowed. And so that's not driven by us, that's driven by our clients. Right? And so we have to stick within this framework, and we want to stick within that framework. But then we want to say, okay, well, how can we use these tools to give our clients better data? Right? Um, how can we use AI to give a better quality product to our clients? And that is the rebuilding of, okay, let's, let's take it all the way back. And if we were going to kind of rebuild this, how are we going to rebuild it with our clients in mind to give them better quality, better service, better, you know, excellence? And that way in using AI to, to help us get.

Speaker B: Wow. And you just really kind of named something that I think is really relevant to most people is one AI is not is not the solution. It's a tool to help you think with. But I think you just really tapped on something big that is happening for us as leaders, which is that even if the circumstances don't change, how do we look at the same situations differently so that we can see more possibilities, we can see more opportunities, knowing that, hey, this is here. We had decided on these were the right workflows, which were right for the time, the circumstances of the time. But now, right, the circumstances are the context in which your business is operating is changing and for the foreseeable future will be changing. But you're identifying it as an opportunity to say, actually, let's. Let's not even just replace this one little bit to get productivity. Let's actually rethink if we still still need all these steps before. Is that what you're saying?

Speaker A: Yeah, yeah. I mean, we're kind of looking at, uh, it as a whole to say, you know, this is the process and the framework that we have to stick in, right. With our clients, how. And this is how we've gotten there in the past. And so we are doing analysis on job tasks and analysis on, you know, time, time analysis, process analysis. Right now, uh, to talk about, okay, this is how we're doing it. Where are the places where maybe there's bottlenecks or maybe there's potential process improvement that AI can come in and reformat, or AI can come in and help us to, um, pick out different things that maybe we didn't see or where are those things. And we don't actually know the answer to all of that yet. And so we are right now doing these analysis on our teams to say, how can we work more efficiently with AI and come out with a better answer for our clients? Um, kind of readjusting maybe the process that we have now and then making it a little bit more efficient to get us to a better answer than what we had before with our, with our more manual processes.

Speaker B: I'll say, and you're speaking to, right. Something that is a reality is, is that, first of all, every single one of us is changing. But when you go to your employees and you say, hey, how can we get this better? How are you guys dealing with the fear that every single person has, Right? Like, oh my gosh, what if I'm not valuable anymore? How are you going in and approaching that? Because that is. I don't care what level you're at. That is a real. The fear is real for every single one of us. Right? How are you addressing that when you go in and talk with your different teams.

Speaker A: Well, I think it's twofold. I think one, it's addressing it right up front where you're saying, listen, we're not doing this to replace you. We're trying to make, you know, make things more efficient. We know that there are problems in your workflow. We know that things are not efficient. You know, we know that, you know, you could probably have three more people on your team. Um, and so we want to find, we don't want to replace you, you know, we want to find maybe this, you know, and I'll give a personal example. On my team, you know, we do reconciliations every month. And so that at one time, when I first started with the organization was taking about eight hours of time, time to do. It's a very long process, not efficient. Built a chat. Um, I've, I've built an agent where it still maintains the security and the compliance for all of these things. You know, hr, I'm very concerned about the security and the compliance, but it still maintains that. But it gets the same task done in about five minutes. Right. That's also a task I didn't enjoy doing. And it was a task that nobody enjoyed doing, which is why it took so long to do because it was tedious. It was, you know, a lot of data merging a lot of different spreadsheets together. And so it was a really challenging task. And so that being able to show those real world examples of, hey, we can take out those tedious things so that you can actually focus on the things that maybe got you interested in claims in the beginning. Right? It was helping people solve problems. You can focus on that because we've got something to help with the letters or the drafts or things like that that maybe take up a lot of time but aren't added value. And then this is almost personal, um,

Speaker B: pain for those, for those people. Right? Like, let's get rid of that so that you can do, use your critical thinking, all your human skills like creativity and really just, you know, that value with human to human.

Speaker A: Um, absolutely. And then I think the second really important thing around AI with our teams is offering that training with it because I think it's very scary for people when they don't use it or maybe they're only using it at one level, you know, kind of that entry level use of it and they don't always see how far and how, how helpful it can be. So I think it's offering that training to say, hey, we're going to start using Them just. We're not, we're not committed to this yet. Uh, but I'm just going to give it as an example. You know, we're going to start using cloth, right? And here are the ways that you can use cloud in our account. Here are the prompts that you should use or that, that you should, you know, this is how you should prompt it to help you versus kind of figuring it out. Those early adopters of AI kind of figured it out and got there a little bit. But then I think to help people realize that it's not there to replace me, because once you get into it, you know that it's not actually going to replace critical thinking and replace the people side of it. Um, you start feeling more comfortable with it. And so I think the training is also a critical component that also helps develop our workforce for the future. Because this is where the future is headed and we've got to develop our people to help, uh, help come along that path.

Speaker B: So how are you doing that? Do you have curriculum? Do you have lunch and learns? I mean, you know, when you think about your, you know, reaching all of your, your 1099 and W2s, is this a voluntary training? Is this a voluntold training? Like. Right, like how give us just maybe a little bit of the tactics that you're using. Um, yeah.

Speaker A: And what say, you know what? Sorry, I would say that that's what we're, we're planning to use, um, is, um, you know, we, we do have ah, LMS system. Our team is really great. And actually they're using Notebook LM to help create some of these trainings. Right. And so I think it's, it's. We plan on doing trainings, we plan on doing conversations, you know, and we have to separate it from our 1099 workforce and our W2 workforce. Because our 1099s, I can't necessarily mandate training unless it's client focused, that this is how you have to do your job. And so, you know, with our 1099s, it's going to be more voluntary. Right. Hey, we offer this if you'd like to attend, you know, if you'd like to do this with our W2s, I do want us to get down the lunch and learns. I do want us to do, you know, we're, uh, we're in a lot of states, we've got a lot of employees geographically dispersed across the United States. And so I want us to come together as a team around this because I also see it as a team Building. We're learning together, we're doing this together. And, and here's how, you know, I personally use it. And so being able to just kind of have those conversations, it. It's, It's a really great way to embrace it, but then also takes the fear out of it.

Speaker B: That's so great. And I mean, uh, to everyone out there, address the fear, right? You got to address the fear head on, because it's out there no matter who it is. So I love that. Um, I love your, your plans and kind of how you're approaching this and the holistic thinking that you're giving. You're saying, hey, I want to give you tools, and I want to give you some psychological safety to understand that everybody is changing. Nobody has the answer. Right? But we can do this together. So I really admire, um, you, how you're doing that. So you had. Just before the call, um, Emily had told me that she just had a leadership team meeting yesterday where the topic was AI, can you share, you know, don't give anything personal, but can you share any of the big topics or big concerns for the leadership team around?

Speaker A: Yeah, so it is. And that was. I, uh, you know, it was more operations focused. How can we, you know, we kind of touched on it earlier in this conversation, but how can we, you know, improve our processes? How can we use some of these tools, tools that we already have some, you know, we have a really great quality tool. Um, and so, you know, we. How can we improve on that? How can we keep going down the path of, of this Rise Qai tool? And so it is. How can we expand that into other areas? And it was a great conversation because that's where we got into the details of, okay, well, where are the bottlenecks or where are the training opportunities for the team? Or, you know, how long is this process taking our team to do different aspects of the operational job now? And then, you know, how can we. How can we use different tools to help us, you know, increase that and improve that? And so, you know, it's. It's that productivity of, uh, where can we get more productivity? But then it's also at the root of the conversation was the quality. So, you know, quality for us is such a huge, and any business, really, it's such a huge component of, you know, making sure our clients are happy and making sure that we are providing that service to them. You know, that it was kind of the conversation is, how can we use AI to improve our quality, but then still make sure that we are, you know, following the guidelines of what we need to stay in. And so it really was a great, um, and I, I kind of sat back and listened. And so we had it on it. We had our CEO, we had our coo, we had a couple of the other, you know, big leaders of the organization just to have kind of a brainstorming session around where do we want to go next? What is the part of the business that we really want to focus on and get some operational wins with AI because that's where we can also provide that value. And so that was the conversation that we had yesterday. And it was, it was great because there wasn't this, well, we can't do that. Right? Or, well, we can't do that because of X, Y, Z. It was, can we do this also? And we had to almost throttle ourselves back a little bit to say we can't do everything all at once. So let's focus on what we can. Like, the wins that we can get. Because we also think that the more we can show our company, the more that we can show our workforce the wins around AI, the more that they're going to embrace it when, when the time comes that we can, you know, get to get to all of our departments and all of our roles, I think it's. It's being able to show those wins.

Speaker B: So what was that conversation like? Um, because I'm going to ask you. I just think it's a different conversation that, uh, you know, is being had in the executive rooms these days. Right. It used to be like, okay, we've done this. This is how we've gotten here. We're going to continue doing this. Yes, we might stop and start, but it is a different mindset, looking at, like, everybody kind of having to come together and start looking in the same direction. Um, do you see that conversation yesterday different than maybe a conversation you would have had five years ago?

Speaker A: Yeah, I mean, and I think the five years ago conversation, it was a lot more, how are we going to do it? How do we get there? How do we figure this out? And, you know, we would need to, to pull in it and it would be a lot of IT hours to do some of these reports. Right. And so I think the conversation now is less around how do we operate? Like, how do we get there from an IT infrastructure standpoint and more of a where do we want to start? And, you know, it's more of a yes and conversation, whereas I think 5 years ago it was yes, but. And that's a big distinction when you're Talking to executives because, you know, we would all, you know, we're always looking for how can we increase productivity, how can we, you know, better quality? And those, those things don't change. Right? But, but when it, in the past, and I don't mean to harp on it, because IT systems are great and you have to have a great IT company or great, uh, IT infrastructure. But it, you know, in the past it was a heavy burden for them. They had, you know, a lot of it was coding, a lot of it was, you know, they would need to go develop or you would have to use something else. And so there's a heavy lift for IT to do a lot of things. And so now it's more of a conversation of, do we have the baseline infrastructure? It can focus on the things that, you know, I can build a report now using AI that I couldn't do five years ago. It can focus on the things that are way more high level, way more in depth for the business than. Because we could take that burden off of them. And so knowing that we have more people across the board that can take some of that burden off has been the change in that conversation because it's, oh, well, I can go build that report and bring it back to the table, or I can help set up the, the agent in the system to read the process that somebody is doing so that we can find the biomex a lot faster. I don't have to wait for it to do those things. I can help you with that right now. And so knowing in a group of people who know that, then it changes the conversation because you're saying you're bouncing more ideas off of each other, looking at the positives of how you can get there instead of looking at all the challenges that maybe you're going to hit. And so it was a really great conversation to have, um, with people yesterday because we just really brainstormed on, okay, well, where are we going to focus this for the business and, and where are we going to go focus for first? That provides the most value to the organization and you know, to, to the people.

Speaker B: Oh man, it sounds like you guys are, are ready to go off flying. But I have a question for you too, also. Around the energy in the room. What was it like when people could see, oh, we can have an idea and I can immediately start contributing to it and then to bring it to it, or I can bring an idea to fruition in, you know, a week or two weeks instead of three months to six months. What was the energy like in their room. As you guys started discussing all the

Speaker A: possibilities, I think that everybody, you know, I think we have to throttle ourselves back a little bit. Uh, like I said before, because we want to, we want to do it all. And luckily we have a very patient CEO who's saying, hold on, like, pause. Let's focus on where we can really drive the metrics and then we can get to everything else. And so energy was exciting. Right. I mean, I think that we were all excited about where we could take things and all excited to hear about it and contribute. But I think there also is. It makes it easier for, you know, I'm hr. I, uh, I don't, you know, I don't always know the processes in the operation side. So am I the best person to help with that? Probably not, because I don't know. You know, AI could say something to me in this analysis and I'm not going to know how to read it. Right. I'm not going to know how to poke the holes in the system of, you know, the agent in order to know that it's the best way if it's an HR topic. Absolutely. You know, I can poke holes in that. I've had. It helped me with different tasks where I've been, you know, turnover data. I've been able to analyze five years of turnover data in a very short period of time. But I was able to question the AI agent in, in order to make sure it was accurate. I can't do that with operations. So I think that conversation changes because everybody wants to help because everybody gets excited. At least our leadership team. Right? I can't say everybody in the world, but our leadership team gets really excited about how. What we can do and how we can do it. But it's also now making sure the right people are the ones doing it because, you know, we have to make sure that we are able to still use critical thinking and question what is being done and question what we're doing, what we're given, being given, in order to make sure that, that we're, we're not going down a path that's, that's not.

Speaker B: Yeah. And I mean, you are also highlighting a distinction of. I like your yes, and I'm going to jump on that on your yes. And like, yes. Now leadership has, you know, more information, can analyze more, can do that. But you also have this intellectual capital for, from each person who is in your organization that knows, you know, knows their, their kind of piece of the puzzle really well. Like, that's also this cool opportunity to be like, wait a minute, we don't have to, as leadership have just the answers anymore. We can actually support these people to, you know, have them use the critical thinking to really do the analysis so that it's not on a small group of people. Instead it's on actually the whole organization moving right towards the bigger picture. Um, did you guys land on any values in your meeting last week? Around, uh, or yesterday? Around AI or just maybe in general around. What are the things as an organization in changing times that you are kind of going to lead the organization to? Like this is what the company values.

Speaker A: Yeah, I mean, I think for us, quality is still number one, right? So anything that we are going to use AI for, we have to make sure that we maintain the quality or better now, or better. Right? So, so we have to still maintain the quality around the claims for our clients. That is, you know, the number one thing that we are at the core of us using AI, we have to make sure that we maintain quality. Um, and so I think in, in that everything else spurs, right? Because, you know, you can keep quality at your, at your core core of using the systems, then that helps make sure everybody is in alignment, right? That makes sure everybody is using the right tools that we are going to give them for it. Because our quality standards remain the same. And so I think that is the biggest thing of. Okay, well, if we're going to go down the path, and I can't give out all of, all of what we're using it for, right? But if we're going to go down the path of this department to go use AI over here, how do we make this transition and uh, not lose any quality in our processes? Because, you know, just because we're, you know, changing the foundation of how we do it, that doesn't mean that's not going to, it's not just like you flip a switch, right? You have to test it, you have to make sure it still maintains the quality. You have to still do the product development side of making sure that it works and that your output is still equal to or greater than what it was before. And so I think that, you know, that is where we are. You know, we're going to focus on, you know, a large part of our business and then we're going to focus on our quality, um, and just continue to, you know, we have, we have quality processes in place around the claim. So it does impact all of our clients. Right. And so I think that's where we are going to just continue focusing it. And so, you know, we are going to set up different corporate accounts with different systems. We are going to set up, you know, different ways that we can provide users. Instead of using the shadow, you know, shadow AI, we're able to actually set up users in a, in a corporate profile, which allows us a little bit more control and security. And that's ultimately what we want to make sure is, um, that, that the tools that are being used are under our umbrella to make sure that we're, we're all rowing in the same direction with AI in the boat.

Speaker B: Man, man, oh, man. Exciting stuff in front of all of us, right?

Speaker A: It's very exciting. It's very exciting. It's been great to work with a team who really embraces it. And you know, I had a conversation, we had a team meeting a few weeks ago and you know, at dinner, I was just having a conversation with somebody else on the team and how they're using AI, uh, a little bit differently than I am. And you know, so now those conversations are learning from each other on the different tools that we're using to work more efficiently. It's, it's been great even for me to learn from people on, um, in the organization of what they're doing and how they're doing things a little bit differently than me and, and how I could learn and grow from them around all of this too. So.

Speaker B: Nice. I love that, I love that, that thinking kind of, that inspiration that, hey, we are all, we're all building this together and there's so many different ways we can go. Okay, so for my last question for you, Emily, if you were to give the audience three human skills that you think are key and critical in this rapidly changing time, what would those, what, what advice would you give on, um, this is where you should put your energy into these three human skills.

Speaker A: Yeah. Around AI specifically, I think it is, you know, learning how to communicate with the different agents. Um, the communication piece is the biggest piece that I think will add value more m quickly into being able to adopt AI if you know how to get the output that you're looking for with your first conversation of a request is going to get you there a lot faster. So learning how to communicate because it is a little bit different. It's not a Google search bar. So being able to, you know, communicate is the number one thing I think is great. Closely followed by question and everything. So, um, you know, closely followed with it. Just because it says something to you does not make it true. True. You still have to use your critical thinking. You still have to Question what it says or make sure that you are still, as a human, making sure that what you're putting forward as. As effort and, and as your work or as, you know, something that you're willing to stand by, that you understand it and that it's accurate. Because there are times that you know it, that these agents and these systems will, you know, spit out things that. Unless you've preloaded, even when you preload it with. Excuse me. There's a lot of times that these systems will not always give you the result that you want. And so I think you have to question it and make sure that you know what you're looking for so that when you don't see it, you know, when you're not getting what you looked for. Um, and then the third thing is, I think, to explore to, to, to go out and see how you can use these different things in your. In your life outside of work. Um, you know, see how you can use things in other ways, learn things. I mean, we're at an age where there is literally nothing you can't figure out if you don't just try. And so I think, you know, just going out and exploring with, with different AI tools and systems, it's fun. It's, you know, a little. A little daunting at first, but I think once you get into it, it's. It's really fun to see what things can be done to. To help you, you know, think and move in a different, uh, well, such.

Speaker B: And I just have. Thank you so much for being on this show. I think your energy is contagious and you are thinking in just such a positive way for the future and really being smart and tactical. So it's. I appreciate you coming on to, um, share that with our audience. If somebody wanted to reach out to you or connect with you, where should they go to find you?

Speaker A: Yeah, the best place is LinkedIn. Um, my first name, Emily. E, M I L, I, E. My mom wanted to spell it a little bit differently, and then Schmidt, Uh, S C, H, M, M, I, T, Z. So that's, that's the best place to reach out to me. Um, would love to connect with people and talk AI and talk all of this fun stuff. But, um, thank you so much for the opportunity to be here. It's been great to have this conversation, and I love talking about it, so it's easy for us to have an easy conversation around all of this stuff.

Speaker B: Awesome. Well, thank you for being on the show and thank you, everyone, for listening.

Speaker A: Sam.