Erin Geiger: 0:10

Welcome back to Clover, everybody. This week, I am so excited to have my friend Kara Mandeville join us. She is a powerhouse, everybody. So you're going to be you're going to love her story and how she's grown her career. Kara, thank you for coming to the show and welcome Excellent.

Unknown: 0:30

Thank you. I'm excited to be here.

Erin Geiger: 0:32

So, Kara, I always start the show out the same way. You know, everybody has a story, and it's, it just resonates with so many when they kind of hear the backstory of, kind of, backstory of, kind of like, how you got from point A to point B. So would you mind sharing, kind of like, your journey, you know, professional and what was happening personally to you as you, you know, navigated and navigated your career

Unknown: 0:56

absolutely well. I'm a military brat, so I did grow up kind of all over the world. I was actually born at Fort Knox, Kentucky, but really can't ever claim that I've lived there, because I was there for for just a short amount of time. But my parents moved to Texas when I was about 11 or 12, and I lived in Killeen and went to high school there, and when I was thinking about what I wanted to do for college, really, my life's passion had been horseback riding. Was really into horseback riding, and I really didn't know what I wanted to do in college. And my parents really were really great and supportive and saying, You can do anything you want and go anywhere you want. And you know, so I was applying to colleges that really had an equestrian team, because that was really important to me. And at the time, I thought, maybe I'll do equine science as a job. And as it narrowed down, my dad ultimately ended up that if I went to the University of Texas and I majored in business, that they would pay for it, and any other option was basically me paying for it. So Surprise, surprise, I did go to the University of Texas. I actually graduated from from there with a degree in marketing. And I really graduated really just still not knowing what I want to do. So now that I have kids that are in college, you know, I think, you know, it's hard to know what you want to do when you haven't done anything yet. So I really started from a place of letting other people kind of decide what I was good at, and that's really how my career started. I my first job out of college was selling, and I was fortunate enough to end up in selling technology sales. At the time, it was for a telecommunications company, and I think that gave me the foundation. It was always an enterprise sales. Was always selling company to company, and in kind of large enterprises and big businesses, and I was working for large companies. So my career, you know, unlike I think some of the other people we've had is, you know, been in large company space. So started off in corporate sales and in the telecommunication space, and I stayed in that role about five years at the first company, which I think is really a good run, and leaving your first company is always super hard, because that's the one that's like, you're kind of your first journey out. But I think what I learned at that time is that, you know, I had a couple of different roles there, and I was feeling pretty comfortable and confident. I had a colleague who who had left and called me to my next company. And so I left, I left I left that telecommunications company, went to a second one, and at that time I did it because someone called me and was like, we think you're great. You should come over here. And I really followed. And I ended up staying at that company almost 12 years. Had my kids there, had my first opportunity to be a manager and leader there. And leaving that company was really the first time that I feel like I took control of my career. It was the first time where I chose where I wanted to go next. And I ended up leaving the telecommunications industry, and I went into kind of a system integration background. I worked for a large system integrator, and that was kind of a big career move for me, because I was leaving almost 17 years of telecommunications and moving more into this kind of computing, hosting, data center, managed services, kind of space, and it was the first time in my career that I chose to do that, and I was I was selective on where I went, and I did that role for about five years, and and then ended up about 1111, years ago here at Microsoft, which is where I'm at today. And that was also an intentional move. I was wanting to get more out of the infrastructure side of business and more into the software side of business, and this was a great place to do it. So I think when I think back about my career, I think a lot about the things that I was learning. And I think at the beginning of your career, you're kind of figuring out who you are and what you're good at. And I think at some point in your career you need to shift to doing what you want to do and pursuing what you want to do with much more intention. Yeah, no,

Erin Geiger: 4:55

I love that. And so when you moved over to Microsoft, I mean. It's like, the enterprise of all the enterprises, I feel like, what was your trajectory there, right? Because you've been there for, you know, 12 years, and so it's like, how did you grow within a company? So you just got there, you know, kind of like, how did you navigate growing within such a huge organization?

Unknown: 5:19

Well, when I first got here, I did move over here as a manager. So I've been a manager position my Microsoft career. And, you know, I think part of it is learning the company. So I think a little bit of it is taking time in a large organization to be pretty good at a thing you're good at and and some of it depends on the company culture. But I think it's a lot about finding people who believe in you and who who you work well with, and then waiting for the opportunities in the organization. So I did benefit, I think, a little bit here from Microsoft's reorganization and having opportunities in how we were organized, or how we were changing to work in different places, which gave me an opportunity to be more well rounded, but I think also in a larger company, have to be have a little bit of patience. You know, it might take you more than one year, six months, or two years, sometimes even, to be really good at a role and then, and then think about what you're learning in the role. It's not really about the job title, per se, but it's really about the skills and being intentional about what kind of skills that you want?

Erin Geiger: 6:25

Yeah, no, that's so true. And so we've had kind of, like, the gamut of people on this show, from enterprise to startups. And it's so, it's so it is so different you're right, like, you know, as a startup, you kind of wear all the hats, and you can move around. It's nimble. You can move around quickly, and, you know, that sort of a thing, but in a large enterprise Corporation, it does take some time, and there's teams that do specific things, and there's red tape and all the things and so, but you have always been in the sales organization. Is that correct at Microsoft? At least, okay, got it. And so can you talk a little bit about your leadership style at Microsoft and how it may have shifted or evolved as your your roles have changed, the teams that you've managed have changed. Talk a little bit about

Unknown: 7:18

that, yeah, well, I think that over the time that I've been here with Microsoft to my my leadership style has probably evolved and changed, because you're adapting to the company culture. And Microsoft is a very has a very strong employee culture, and it's grounded in kind of the very strong mission statement for the organization and then some very principled structures around modeling, coaching and caring for employees. So I think that what has been cool is to adapt kind of what was my kind of an high energy, kind of optimistic like kind of heavy collaborating type of style inside more of a structured environment that is the Microsoft framework. And I think that experience, you know, has been good. I think what I brought to the company was a little bit more of the speed, pace, accountability that that came from a couple of the companies that had come from before that maybe had a little bit of more harsh sales cultures than I think Microsoft did when I first got here, because we weren't, we weren't competing in the market in the same way some of those other organizations were competing. And I think, though over the time I've been here, we are competing like that now because we're entering space of AI, where there's a lot of a lot of organization, lot of other companies that are doing really well in this space too. And I think that competing, more accountable mindset, you know, has served me well here.

Erin Geiger: 9:00

Yeah, and how do you so, it's such, you know, it's high stakes, right? And there's a lot of pressure, a lot of expectations on you, especially, I mean, with AI, you know, because everyone's like, how are you using AI? How are you leveraging AI? Like, what's going you know, you know, it's, it's like, so it's like, you're, you're used to complex, high, you know, performing environments like, you know, my gosh, from the cloud, digital transformation, AI, like you've been, I feel like at the forefront of so many of these things, but it's like there's so much pressure and high expectations, and it's evolving over time. But you also have a lead. You have to lead a team through all of this. So how do you kind of keep your team steady, yet excited for what's to come, and kind of quell any fears or concerns they have about maybe how the team is shifting or focus is changing with AI and everything else going going on. How do you lead a team through all of that? I think a little

Unknown: 9:55

bit of it is, you know, slowing down to make sure that you have time to listen. I. I think my husband teaches baseball. He's a coach for baseball, and there's a baseball like experience that I had it with, like eight year old that has really translated to my work as a leader. And what he did is he had two lines for and what the kids did is they threw they they all faced one direction, and the kid in the back, or the kid in the front, is turning around and throwing the ball to the kid behind it, and then he's turning around and throwing the to the ball behind him. And they're trying to have a race of who can get the ball down the line. Now, anytime the ball is dropped or it's overthrown, you have to step out of line and come back in line before he can throw it again. And what was happening, 100% of the time is the kids who turned around and threw the ball very intentionally and simply to the kid behind them always won. And the kids that turn around and hurry up and threw the ball always that line always lost. And I think like this concept of like being slow, slowing things down, especially when there's a lot of change, slowing things down, keeping things simple and communicating is the thing that helps teams make that evolution. I think there is also an opportunity to double click and really lean into being optimistic. I think if you're looking for the good things and change, and you're looking for the opportunity, even if it's a learning opportunity or a challenge or an overcoming or a story that you're going to have later in your in your life, if you once you have those opportunities, and you think about it in that way, I think it's easier to get a team on board.

Erin Geiger: 11:41

Yeah, and I agree with that. And so it's, you know, moving quickly, yet slowing down enough so that you're moving intentionally and you're you're moving in lockstep with your team, and everybody knows what the end goal is, and how to, you know, take that next best step forward, rather than moving forward with your hair on fire, just because, like, AI is the new, exciting thing. We're all supposed to be doing it. Let's go, you know, and everyone's like, doesn't know, you know what the right arm or left arm is doing, and their their piece in it. And I agree with you. I think, I think people tend to get anxious when they don't know their part in something, the role that they hold, and how they can impact moving moving forward. If they're just kind of like, toss something over the fence and be like, good luck. You know, then it's just, it's not great for everyone.

Unknown: 12:35

I like the principle of three things. There's a lot of people who have this three things, people write books about and everything. But I really do love this concept of, like, getting really good at three things. So when things are really overwhelming, and I would say, like, right now, an AI is like that, it's so big and it's changing so fast, it's so hard to keep up with what is open AI doing versus, you know, three months ago, they were like lead dog, and all of a sudden, anthropic on top. And, you know, there we had the, you know, the China organization that was doing, I mean, it's so hard to keep up with all the models and the changes, and I think trying to focus on a couple of things and doing those couple of things well. And once you've mastered those a couple of things, it's the prioritizing of the things that becomes the hard part, instead of the doing it. But it's very hard for anybody to do 10 things really well right away, and you're kind of carving it up into something smaller. Makes it easier. Yeah, that's

Erin Geiger: 13:30

so interesting because it's, yeah, it's moving so fast. Like, I always joke, like nobody knows what they're doing with AI at this point, we're all just trying to figure it out. So there's so much going on and there's all this, like, noise out there. And so, like, how do you as a leader, filter it out? You know? Like, you're just like, you kind of, like, filter the signals from the noise, and so that you can make clear decisions when not everything is fully defined yet, right? And so it's kind of like you're taking that next step not really knowing where your foot's gonna land. So it's like, how do you for yourself and for your team? And then also, like, when you're trying to get stakeholders on board champions of what you want to do when, like, things aren't really defined. No one really knows what's going on. How do you kind of get that buy in from folks, whether it's your team or other people cross, collaborating across the organization,

Unknown: 14:28

I think you are right about kind of this industry right now, and how complex it is and how fast moving it is, and I think that there's a lot of research happening too In AI and what it means for humans for work. And, you know, I've seen, I think one of the stories that resonated most with me about just the environment was the concept of, you know, moving from like the water wheel to electricity in the manufacturing process. Yeah. Hi, Well, hello there.

Erin Geiger: 16:42

That's funny. I think we're still recording. So what you were talking about was, like, the water and the wheel story. So if you just want to, like, start with that, but then we can continue.

Unknown: 16:54

Okay, so, so I like that water one in the wheels, kind of that history of manufacturing it starting with the water wheel, and then it talked about switching to the to electricity, and organizations that just switched electricity out, but didn't make any other changes, only saw like a two or 3% increase in the performance of manufacturing. But if you look at manufacturing over a period of time, and you look at how we do manufacturing today, it's significantly evolved because the processes for manufacturing have significantly changed. Then, if you apply that parallel to information work, which is people sitting in offices, working in an organization where there's an HR department, a finance department, like those, organizational structures really haven't changed in, you know, 100 years, I mean, we're still doing information work in very much the same way, although other processes, like manufacturing and frontline work and all of those have really evolved. This to me, feels like this is the transformation for for AI is is on information work, and it will require all of us to work differently. And you know, for your question about, like, how are you handling this? I think for me, it's about experimenting. It's like about encouraging as many people to experiment, and myself experimenting, you know, and just making a commitment that every day you're going to try a little something new, you're going to learn a little bit something new, and that it's a very even ground, because nobody knows everything yet. So it's really hard to be behind, you know, because no one is no one is truly ahead here yet. So this opportunity of experimenting, we work a lot with our companies that we're working with, and organizations we're working with, and kind of doing the same thing, some of the very best and most innovative ideas on how an organization can leverage AI are coming from people who are doing that work in a department today. It's not coming from an IT organization. It's not coming from the Office of the CEO. It's coming by people like me or people like you sitting in a job role thinking. Man, sure would like to not have to do this as much every week, you know. So those are where a lot of the innovation is coming. I think that there's a huge opportunity for for all of us as humans to really unlock our kind of human ingenuity and our innovative and our creative sides, and our communication and our collaborative and all things are really good and offload some of this things that have become the information work overhead, you know, the last century through AI,

Erin Geiger: 19:35

yeah, it's interesting because we had, I had a woman on she's also in Austin. Her name is Bree Whitehead, and she does a lot with, um, she her thing is, like, AI, can bring humanity back, you know, which I think most people are like, what? And I was like, I love it, you know, because it's, she was like, it's pure to your point. It's taking the stuff, the mundane tasks, or stuff that we don't necessarily want to do. Yeah, and or stuff that's holding us back. You know, if we didn't have to use time for that, we could be more innovative and strategic over here. And, you know, kind of think about the future, but it's like, oh, maybe it will. If you allow AI to take care of some of these things, not only could you, you know, move ahead in your career, but also for your own wellness, like, maybe you could take a walk, you know, maybe you can meditate, maybe, you know, you can spend time with your family, you know, because you're not, you're not doing all, you know, all of, all of these things. And so I think you know, to your point, we're kind of all in the same boat, and we're all kind of experimenting, and we all kind of realize where we are, where we were all in that same thing. Of like, we don't know where the next step is, and so it's like, you know, as far as kind of getting buy in when everything's not defined, it's like, it's almost like accepted. Now, you know, of like, Yeah, we don't know. Let's see how this goes.

Unknown: 20:56

And I think, you know the concept of, you know, like, when you're when you're building great, great teams. One of the principles that has been around a long time is the concept of, like, Will or skill. People say that in a different way, like, when you're hiring a person, are you hiring for the skill? Are you hiring for, you know, the drive that the person has. And, you know, I think it's oftentimes a balance of those two things. But the fact is, the skill can be learned, and leveraging and using AI is a skill that everybody can learn. And I think that that is a huge opportunity. The will piece is, is the mindset of people who are going to, I think, really take advantage of what this new opportunity could be, because it's people who are embracing that experimentation and trying over the next few years that have an opportunity to advance. So I think you know, if you're following a lot of research, Microsoft publishes research called the work trend index. Probably about a month ago, I was up at Harvard, where Microsoft was doing some joint research with Harvard Business School. Like the concept of Ai plus humans together is a better together story and but I think there is going to be some fundamental potential restructuring and how information work is done. And I think there's a few terms that kind of, I thought were kind of interesting concepts. One was the concept of, you know, systems of work, insist of systems of record. A lot of companies operate around, businesses around systems of record. Your financial services are all in a financial Oracle or an SAP. And you know, manufacturing systems or and organizations are even structured around like the systems of record. And how they execute things is based on these moving more towards systems of work, which gives a lot more flexibility for how business can be organized, which I think is really interesting. I think the other thing is like, instead of org charts, preparing work charts, so this concept of really restructuring work, whether it's in systems or whether it's in people, the concept of a work chart like the best, the best way to kind of, I think, visualize or explain that would be, you know, today you're in an org chart. I'm in sales. I'm reporting to a sales Vice President, you know, eventually up to a chief revenue officer. But in a work chart, people are pulled together, like a movie set, like when you're making a movie, you might have all these different people that you pull together the best of the best for that specific movie, and at the end of the movie, they all disband, back to the roles. And a sales pursuit can be done that same way, right? A sales pursuit needs technical resources. It might need marketers. It might need, you know, engineering people, and it needs sales people. And you come together on a pursuit, and then you could disband and move to another pursuit. So, like, this concept of work charts, I think is really interesting and facilitates some of that.

Erin Geiger: 23:48

Yeah, yeah, no, sorry to interrupt. I, I was thinking along the same lines. It's perfect segue, because, you know, the idea of an individual contributor, right? Like an IC might be going away, you know, kind of to your point of, like, the org chart, right? Because, like, now the research that I'm reading is you're going to have agents. So everyone's going to have a team, everyone's going to be managing, you know, maybe hundreds of agents that you know, do you know, a segment of of their role, and so that everyone is going to kind of be elevated to almost like a manager or a leadership role, in that they are managing all these different agents that are doing all these different things. Have you kind of seen the same similar, yeah, yeah, I have.

Unknown: 24:37

I have seen those type structures where you, you know, you you every person will have those personal assistants to help them do their jobs. And then I think what will happen in organizational hierarchies is they can be flatter. So if you're watching the news, you are seeing a lot of the tech companies taking out kind of some of the thicker middle management layers, because the work groups can now start to take advantage of so. Of the technological advances like this, so that the work can be done in a flatter way, which I think is interesting and, you know, and it's honestly kind of relevant now, because of where we are with especially in the mature markets, with, you know, an aging workforce. A lot of really developed nations in the next five years are looking at some of their most experienced workers retiring, you know, and this is an opportunity for those organizations to capture that tested knowledge, you know, and help future work groups take advantage of that skill, but through more of an agent technology than maybe in the ways that we've been doing it.

Erin Geiger: 25:38

Yeah, no, for sure, it's going to be really interesting to see. You know, we have a front seat to it. That's pretty incredible. What are you seeing like when you're talking to customers? Are they kind of, I wouldn't say they're getting stuck in adopting AI? I think everybody realizes this is the train that we're on, but it's, are there kind of like stumbling blocks that you're kind of seeing them go through when they're trying to adopt AI to kind of support their goals or their teams.

Unknown: 26:09

Yeah, I kind of, I put customers in a couple of different classes, and I'm thinking about like our large enterprise customers. There's there's customers who see AI as like a strategic initiative, and those customers are aggressively pursuing agentic tools, capabilities, ideas. They are kind of the front, kind of the front runners, and they see a competitive advantage to being an early mover in this space. I think then you kind of have the big middle of customers which are still trying to figure it out. I see most every organization doing something with AI, I really can't say I see any organization, really, what I'd say, falling behind, because I think everyone is trying to figure out how to use it. But I think what I see for large enterprises is, you know, a little bit of am I getting the value for cost? Those types of questions still coming up, where organizations know that when they give Aaron a license, Aaron's going to save two or three hours a week. They know you're going to be happy. They know you're going to be more productive, but they don't know how to translate that into dollars for the business yet, because they haven't really thought about any of their processes. It's kind of like back to that wagon wheel and electricity, you know? I mean, they know you're saving time. They don't know how to turn that into more output for the business. And I see a lot of organizations still trying to figure that piece out of how do they light open time? And a lot of that means if, if I'm getting saved, you know, a couple hours a week, you're getting saved a couple hours a week, and someone else is getting a like before. You know, might be three or four of us that are saving a couple hours results in one human but no one job really was removed. And it's a percentage, 1520, 30% of everybody's job is removed, but not 100% of anybody's job so that that goes back to that work. Restructuring is like, some of the work will need to be restructured. And there was another really great example that was shared around law firms, because law is like a is like a hotbed for for for AI, because it's so document and reading heavy, and there was a law firm that shared their story on AI and how they were adopting it and what the impact was on Junior associates. So these are the people who come into a law firm out of college and work 10 years and hope to be a partner, you know, eventually. And the work that those associates are doing now is significantly changing, because AI can help a lot in the things that they used to be doing. And one of these law firms was talking about how, how they are actually getting more billable hours now out of the associates than they were previously, because the tools are helping them with more advanced skills than they would have been eligible or able to acquire in a shorter amount of time. And then secondly, they're enhancing their capabilities with client relationship opportunities, which normally is preserved for the partners, although they recognize that some of their partners aren't really good at it because they it, because they might have been attorneys for 1015, 20 years before they were a partner, and they never had to do it. And now they're mid or late, later in their careers, and they're having to learn this new skill of client relationships. So they're having an opportunity to start that with their associates. But it gives you, I think it's a good i gives you a good example of how work is true, could truly change. And an example of an industry that I think will be disrupted in some in some fashion with with these

Erin Geiger: 29:50

tools, yeah, it's so true. And so it does kind of give people a way to evolve their skill set, whereas they wouldn't have had the opportunity. Before, and it kind of opens up opportunities for different roles, or, you know, goals within their their careers. Another part of it, too, is securing AI, right? And so it's like, so a couple of things, so you touched on ROI. So it's like, how to compute what we're getting out of it financially? How is it impacting the bottom line? And then also like, how are we making sure it's secure, like, in a world of like, cyber security madness, threat actors and all the things, you know? And it's also kind of like, okay, we're moving quickly with this, but there's a lot of holes there, you know, that we kind of have to to plug in as well as as we as we go. So there's so many things. I mean, with any kind of new technology, it's, there's a lot of gotchas that I think we're all still figuring out as well, and I'm, and I'm sure, with an enterprise as large as Microsoft, that's a huge concern, you know, as you move forward with copilot, and any anything else that, you know, the AI that Microsoft allows within their walls, virtual walls,

Unknown: 31:09

the ROI thing too, is interesting, because ROI is one of those things that when things are starting, or traditional businesses, especially in it, think about this return on an investment concept. But the fact is, oftentimes, once a technology is adopted, then they move away from that. It comes infrastructure of a business. So think about, like, probably the first round of laptops any company ever bought their people. I wanted to know what was going to be the return on these laptops that they're purchasing. But today, you would never go and work for a company and not get a laptop, or not be expected to have a laptop. And that has moved more towards infrastructure, instead of needing a return. And I think you know, as like you, you brought up kind of the Internet has evolved, and how fast things are moving. I feel like, over even the last two years, many more organizations are starting to think of AI's infrastructure, you know, and less of them are as stringent on the ROI. Are willing to invest, knowing that they will get it, and also knowing that eventually you're going to have to get there, or you're not going to be able to attract the same market talent, you know, in the workforce, then you're not going to be as competitive. It's gonna be too slow, too long, hard to catch up. So for sure. And then the security piece, boy. You know, there's a lot going on the security space, I think, and and I think it's gonna be very interesting to see how it unfolds. I think if you know, Microsoft has a very excellent story in this space, especially for large enterprise customers, because of most of our a is accessed through tools we already are providing security for, and I believe we have 35,000 engineers dedicated to security. So it's really hard for any other organization, if this isn't your business, to have that type of manpower entirely focused on this, but as a consumer or as a smaller business, I think about, yeah, just the risk of, you know, not knowing what's real. And I had attend an event here in Austin, there was a lot of discussion around like, should it be more regulated? Does it need to be less regulated? Is it, you know, what are the rules that other organ countries, you know? What is the rules China is playing by versus one of the rules us is playing by as it relates to AI? And it is, it is scary. But one of the examples there that really stuck with me was talking about, like, skepticism and like, how that can be a good thing in the age of AI. And it talked about like, if you're on Facebook and you see a video, the percentage of people now that are like, is this fake or is this real? And that concept of the skepticism coming up in all of us is probably a good thing, because, you know, years ago, we would have just believed more, you know, and then the era of AI, we're more skepticism. We have more skepticism, which will allow, I think, the reputable organizations or organizations that are doing responsible things with AI to come to the surface and be recognized in the same way you used to check the URL and make sure you go to the right site. You know, those kind of things that were early internet, things that made sure that the internet wasn't going to be, you know, a way for all these imposters. It's kind of the same concepts, I think, with AI,

Erin Geiger: 34:29

yeah, no, that's so true. And even with content as well, like, how to regulate that, right? So there's some people who want their content scraped by AI and want to be included, and like, AI overviews and results and that sort of thing, other people don't at all, and other people do, but they want to get compensated for it, you know? And so that's a whole other thing that you know, trying to figure out as well. So it's like, for you know? Because when you go and you get, like, an AI overview answer, it's like, gives you a summary. And you're like, well. Cool, got what needed, you know, moving on, you know, and then you're not clicking through to that website. You're not checking out their other content and everything. So it's kind of figuring that as well, right? The SEO, AEO, all of that is kind of been turned on its head. And it's interesting, you know, when you were brought up, the point, people are like, is that real or not? Even smaller, like, local things like, you know, our local high school has a really competitive marching band, and they were on their way to the state competition last year, and a train actually hit their semi, you know, on the way to San Antonio. If I haven't showed you the video, I will, but people were immediately like, that's AI that didn't really happen, and really and it actually it did, you know? And so it's just, but it looked like really a train hitting a semi. Come on, you know. But you're right, you know that that layer of skepticism is there, and I do agree that it's a healthy skepticism, because there is, like, there was a gentleman I was going to interview for a different show, and he declined because he said, I'm really trying to keep my voice out of the public domain, you know, because of those impersonation breaches, you know, and so. And it was the first time I had heard that from a potential guest of it. It was a different show, but I was like, oh, okay, so I'm probably gonna start hearing that more often, you know. Yeah, it is really interesting

Unknown: 36:23

each thing to boy, you know, some of the business use cases I love, because I'm in a global world Microsoft, and I'm definitely working, you know, in the Asia time zones or in the EMEA time zones. And where you're you're working with people who are English is not their first language. And the ability to be on a conference call with people and have them listen in their own language. It's pretty amazing. It is amazing. So I think what this does for inclusion, and what this does for kind of leveling the playing field can be really amazing, but it also has risks, you know, of like, you know, somebody reusing your voice, or your voice impersonating you, and you know, it's going to be, it's going to be kind of a little bit of a wild time. I think here it is,

Erin Geiger: 37:12

like a whole other box of things that we need to, you know, be worried about, or, you know, figure out. Okay, so I could talk to you forever, but last serious question, and then I have a fun question for you. But so after two decades of growth, leadership, building this incredible career, how do you define success for yourself now, right? And kind of compare it to what maybe it was, maybe when what it used to be, maybe when you first started out, versus how do you define success for yourself?

Unknown: 37:44

Currently, I think success is being balanced in what you do, loving and having fun. I think you know no above all, if you're going to do something 4050, sometimes more hours a week, you better really love it. And I think success is being in a role, working with people that you love, learning new things and enjoying it, and doing it in a way that it doesn't totally take over your life and make you out of balance, in your in your health, you know, in your soul, you know, or in you know, other parts of your your family, family life, that is probably different than it was when I started my career. Because I think when you're starting your career, you're trying to prove yourself, you know, and you you're willing to put family later, you're willing to put your personal time later. And I don't know, some people will probably disagree with me, but I think sometimes I think that's okay early in your life, you know, but at some point you've got to start making that balance. And like myself and like other people who are kind of like me, it would be really great if we could figure out when to start making that change. I find, though, instead, what most people have, and even including myself, is at some point they have something that happens to them in their life that makes that change for them, they have something maybe they didn't intend it could be like for me. I was just way over traveling. I just totally wore myself out. And health, you know, kind of had some health ramifications from that. And I think people have that or they have that or they have a family member. I've had people who I've worked with had a family member die. That was the thing that made them decide that the balance needed to be done. So I think, I think, I think that's where I am now, and I think for other people who are earlier in their career, is just be knowing at some point you've got to balance in that direction, you know, and don't, don't wait so long that it has a thing that makes you do it, but that you're doing it kind of thoughtfully or slowly instead of abruptly.

Erin Geiger: 39:54

Yeah, I get that, and it's almost like your priorities shift. And maybe. Will see that earlier with more people, especially now with AI, where they can use their time for different things, whereas, like when you and I were coming up, it was just like nose to the grindstone, you know? And it's like you just keep pushing through, and you do those long hours and and that was what it was expected. And it was almost like a badge of honor to be burned out, right? You know, and to be busy, yeah, I

Unknown: 40:22

still see some of that in the large enterprise workspace. I still see that. But who, who pride themselves really working long hours and stuff, and I think, but I've come to see the my best work is when I'm well rested, I'm well rounded, and I'm happy in my life. Definitely, that's when my best work is done?

Erin Geiger: 40:41

Yeah, if people want to connect with you online, what's the best way to do?

Unknown: 40:44

So probably on LinkedIn. I am on LinkedIn. Try to post on LinkedIn. Easy to find. There's not, I don't think there's very many caramels out there.

Erin Geiger: 40:54

Okay, I'll include that link in the show notes. Okay, and the last fun question that I ask everybody, because you know myself, you know my husband, you know we're like, all about music. If you could only listen to one music artist for the rest of your life, who would it be?

Unknown: 41:11

Well, first off, this is so hard, because I like a bunch of but, you know, I really like pop music, and I am a Swift fan. You're a Swifty. I love it. Just really like, so you can cut this part of the show, good stuff. Yeah, you have good stuff. And I even like her old stuff. I like her new stuff, you know, I don't know she, she's, she's probably, she's probably

Erin Geiger: 41:39

up there, yeah, I could see that, because she has enough diversity, like variation in her music, to where you're like, Oh, if I'm in this mood, then I'll listen to this Taylor, if I'm in this mood, then I'll do this kind of a thing, you know? So I get it, I see it, and I like some of her stuff so catchy, for sure. And her as a person, she just seems like a good, genuine person, too. Yeah? So, yeah, that's awesome. Okay, I could talk to you forever, but I do realize we have other things in our day, so I will have to let you go. But thank you so much, Kara, for being on the show and for sharing your expertise. It's it's invaluable for the listeners. Really appreciate it awesome.

Unknown: 42:14

Thank you for having me, Aaron. Appreciate it.