How do you leverage GenAI to pivot your leadership journey? Because technology is still male-dominated, how does a woman executive in insurance embrace the latest technology and lead in the transformation of her organization? What considerations are important in the decision-making process for implementing GenAI? What learnings should she have? How would allyship support her journey? This session will touch upon Leadership development, innovation, mentorship, and allyship.
Transcription:
Peilin Corbanese (00:08):
Morning everybody. I'm Peilin Corbanese. I've been told I need to establish my gravitas per my mentor, one of my mentors. So I work for EXL. I'm the VP of Analytics and we are a 55,000 people, $1.8 billion company. We're a management consulting firm that has 530 insurance clients globally. But that's really the boring stuff. The more interesting stuff is that I'm a three time award winner for leading digital transformation data strategy and for champion women and minorities in our industry. So today my purpose is to make this session meaningful to everybody that's in the audience because at the end of the day when everything is said and done, all you have left in this world with people is how you make people feel. So let's get started.
Jamie Warner (01:08):
Hi, I'm Jamie Warner. I Lead Cloud and Data Science Pricing for Plymouth Rock Assurance, which is a regional, small but mighty regional insurer in the New England area.
Tatjana Lalkovic (01:21):
Tatjana Lalkovic. I am a Chief Technology Officer at Definity up from Canada.
Gina Hardy (01:27):
Hi, my name is Gina Hardy. I run the beach in fair plans. In North Carolina, we insure approximately 160 billion of property and in premium we write about a billion dollars in premium. I also have the privilege this year of being the board chair for pso, which is an organization of all the residual markets that serve in the United States and also on the board of IBHS, which is working with resiliency.
Peilin Corbanese (02:01):
In the prep session, I asked him to share one story that the audience can take away. So I am going to insist on one of those stories, Jamie.
Jamie Warner (02:13):
Sure. So I think in terms of talking about AI and leadership in AI, I think the biggest thing that I like to take away is that we all kind of get to be the intern with this type of topic because a brand new topic, and even for those of us really deep in it, right? I've been in the data science field since they started calling it data science, which albeit is recently, but we all get to really step back and ask a lot of questions and be really curious, and it's okay to be the dumbest least knowledgeable person in the room right now and really lean into that because it's changing really fast. And that's what I would like everyone to take away is this is the time to lean in and ask the questions and say, I don't understand. I don't know, because it's changing so fast that even the experts really don't.
Peilin Corbanese (02:55):
So I'm going to go back to Jamie still. So how have you pivot your career by leveraging Gen ai?
Jamie Warner (03:03):
Sure. So I mean my career kind of has always been a little bit of a pivot and a pivot and a pivot. I love math. That's what I like to do. I like to use numbers to tell stories, kind of like our initial speaker talked about. At the end of the day, as much as I love numbers, I know everyone else, and so we have to find the story and the numbers, and that's a lot of what insurance business is. And so as the technology has changed, this has just made it easier and easier to tell that story. And the cool thing about insurance is there's so much rich data and information, and the terrible thing about insurance is it is so hard to get that information. And so the place where I really see a lot of these new AI technologies is not some shiny, exciting predictive model necessarily, but actually getting access to all the information that we haven't been able to capture until now.
(03:51):
And that's the stuff in PDFs. I love this story. The former chief data scientist for the United States actually said right after he finished his tenure, he wanted to go into insurance and make a difference in the space, and then he started looking at the data and realized it was in PDFs and backed away and picked a different industry. And that's how hard our industry is. And things like gen AI can allow you to scrape that information and actually collect it in a way that can make it actionable for our claims adjusters, for our call centers, and even to be used in predictive models. So I just think riding this wave is going to make it easy for us to be lazy at the things that we hate to do and really succeed at the strategy and the thought leadership and driving a difference in our space.
Peilin Corbanese (04:34):
So Tatjana, when we talked this morning, I had a prediction that in the next five to 10 years, if insurance carriers do not adopt generative AI, many of us may lose market shares. I want your opinion on that and what you have done with your organization in leveraging Gen AI to lead.
Tatjana Lalkovic (04:55):
Thank you for that question. Maybe I can start a little bit with my story to give a little bit of a context. I did a very short intro. So my background is in technology and math. I am recovered banker and many of you started in insurance, stayed in insurance, I love it. Now, one of the ladies coached me last night saying, you did not go to the dark side, Tiana, you went to the Jedi side. So I'm taking that and owning it, but I spent a lot of my career in digital banking, lots of innovation there. And when I was asked to join insurance industry and finity, what was exciting is to find the industry that is financial industry still. I can leverage my knowledge and skills but is ripe for disruption. And so that's what attracted me as a transformation leader to go there and do these amazing things.
(05:55):
And FIN was getting ready in 2021 to Demutualized and we had a second largest IPO in history of Canada, which was very cool to be part of. So AI comes as one of the mandates that I have and that I'm super excited about as an opportunity in the industry and in the world. I know there's a lot of concerns. So going back to really your question Peilin, I think that the companies that already don't have a plan, how their business model is going to change, how their workforce is going to change with AI and generative ai, they're probably already late. But what I mean by that, you need to be thoughtful. That doesn't mean you jump right into it and everything is generative AI and ai and we don't have people anymore. I don't mean that it's really being thoughtful as to what does it mean.
(06:53):
I do believe the generative AI replace tasks, not people. So the idea is figuring out what are those tasks that you can replace and be more productive, more effective, make an impact, improve your customer experience by leveraging generative AI. And so we started with foundations like Jamie said, and then leaned into numerous use cases. And we started with not the scary ones, the ones that people go, there's a risk of hallucination and bias and all that stuff. You can start small but meaningful and find things that will make a big impact. So Jamie mentioned call centers. That's where we started. We implemented last year call summarization, and it sounds really simple, it's listening to your call. There's a translation voice to text, and it summarizes, and we gave it to the agents as an assistance tool and allowed them to edit if something is not correct.
(08:04):
And what we measure is four minutes per call saving immediately after the launch. And we thought agents will have to spend a lot of time editing, but guess what? It actually was more accurate and more concise than agents were doing. And now we have agents that can focus on really assisting our clients and really supporting them, providing great experiences, not frantically taking notes, putting it in a CRM system following up after that. And so it created that freedom, but then we expanded beyond that. I talked way too much, so I'll stop there. More to come.
Peilin Corbanese (08:49):
Thank you Tatjana. Gina. So what have you done and what are you doing to leverage generative AI to continue your leadership journey?
Gina Hardy (09:01):
I think when I first took the role as CEO 13 years ago, I walked into an organization with green screens and I was like, wow, this is going to be a very interesting role. And so we worked very hard to start our transformation journey and then a couple of years later, because first we had to shore up, we didn't even have everything backed up into a data center somewhere else. We're talking various lowest level on Maslow's Pyramid. Then in 2019, I had the privilege of actually keying Guidewire. And for a residual market, CEO to be the keynote of Guidewire was unheard of. But we had done such a great job with our transformation journey. We actually transformed our systems. Within two years of us starting the process, we did spend a year researching. And so as I look at how we did that is really, I learned a lot of lessons when I transformed our main core systems and we went into the cloud right away.
(10:06):
Some companies are not yet in the cloud and our expense ratio is lower than the ward's top 50. So we understand that we need to lean into technology and that our technology is really paying the benefits for us in terms of extremely low expense ratios, but we also need to be responsible as we implement that technology and thoughtful as we implement it. For example, about a year before I was going live with our main policy administration policy claims and accounting systems, the insurance commissioner of North Carolina levied the largest fine that had been levied in the state against a health insurance company because they rolled out their system poorly and caused such havoc in North Carolina. So here I am, I have at the time 60 plus percent market share on the outer banks and barrier islands. I have 40 plus percent market share in the 18 coastal counties, and I'm about to roll out a system and I want to stay out of the headlines of the news and observer.
(11:18):
That is the goal of my career. So I have my main technology manager and he comes into me and he goes, we're ready to go and we're going to go big bang. And I was like, no, we're not going to go big bang. I said, go talk to my operations manager. I said, he understands my plan. And so this guy kept going back and back about how wonderful it would be to this big great big bang. I had already talked to our insurance commissioner and we had agreed that we would do beta tests, we'd roll out to certain agents and then more agents and then more agents. Yes, it was not exciting. It was not a super big bang, but as a result, we got great press. I ended up ultimately keynoting Guidewire because of our great success. But all of that was because we were very thoughtful and cautious and I learned a lot by watching what happened to the other insurance company that got the highest fine in our state.
(12:16):
So how am I doing with AI? We've rolled out some similar products and Tatjana has talked about, and then we have a lot of use cases that we're working through and we're working through them in pilot because what we're seeing now with AI is we're seeing big household giants fail. We've seen some household giants fail with using it for screening applications. We've seen it amplify bias. We've seen it then try to overcorrect for bias and then have historical images be incorrect. We have seen problems with it in terms of giving us the wrong information, whether it is trying to get summaries or things that we know. I recently asked my husband to go pick up my prescription at the drugstore. Well, I talked to their AI bot. I sent my husband up there and he comes back and he goes, it says you have to have pre-authorization. I said, well, the AI bot didn't say that. And so we see the big giants failing. And so I think as we implement it, I love your story about what you're doing with your reps because we're doing similar things with ours, which is you're having the reps re-look at what it's typing for you. So you're having that quality control. I think of AI as my most efficient employee, but my least experienced employee that can hallucinate on a regular basis.
Peilin Corbanese (13:56):
So Gina's organization is a very unique wand. I consider it as a unicorn female, CEO, female CIO, who is also in the audience and in the IT department that at least my personal professional experience, it's largely male dominated. And Tatjana is another unicorn CTO of the organization. And Jamie head of data, advanced data science. So I want to ask the panelists here, what is your secret to become so successful in what you do and build an organization such as the one that Tatjana and Gina has built to lead in leadership using technology and have females in your world? We're going to start with Jamie, you're going to start with me.
Jamie Warner (14:52):
I want to start with the powerhouses. Yeah, I mean I think the biggest thing about it is just kind of realizing that the environment is going to be a little bit different and bringing people along. They don't have to go through what you went through to be good at their jobs. And I think that's probably the biggest takeaway for me. I know I had some female leaders in the IT space. It took a while to find them, but some of them kind of made the comment, it was really hard for me. You'll get through it. And I think we're kind of shifting the mindset of it was really hard for me, how do I change the infrastructure so you don't have to go through it? And that for me also was a big leadership style change as I've gone up because I worked for almost all men exclusively in my initial career.
(15:38):
And I know they never asked me how I was feeling or any of those sorts of things. And so as a manager, I actually thrive on that. I love data, I don't love feelings, but I've realized that a lot of my employees and bringing more different types of experiences into the community, it's really important to have a pulse on those things. And I do think it makes it more inclusive because people learn in different ways and especially with technology, there's a lot of self-learning. So how do you get into those communities and get into those self-learning paths and not feel like everyone knows everything that you don't know is really creating a community where people feel like they can ask questions and feel like they can share those pieces of information. So I think a lot of it is that opening the door for the folks that you want to be your peer group.
Peilin Corbanese (16:20):
So Jamie, I have a generative AI solution for you. It can cue empathy when you need it. Good, good. Tatjana, how about
Tatjana Lalkovic (16:31):
I loved it. I think your question is as a female leader, I think I started actually my career as a technology lead in trading technology. And so that taught me something. I mean, I was in a female underrepresented environment. Most of the men are on a trading floor and you learn a couple of things, competence, confidence and inspiring. And what I mean by that is competencies. You learn that all you have is what you bring to the table and how you can make a difference for the business. And you learn that in capital markets very clearly. If you don't understand the business, you can be the best technologist you can be. You're out before you can blink your eye. And so I found the competence being a huge equalizer and inclusive aspect. The confidence something discussion I had at the table last night at the dinner is about that courage. We are not born confident. It's having a courage to try and to speak up and be there. And then finally, inspiring leadership is if you can't inspire people to follow you, to build the teams that will be inspired with what you're bringing to the table and your vision, it's going to be hard to do things. And once you have people that want to follow what your vision is, you can actually make the difference. And so that's, those three were very important to me. And finally do the thing, pay forward.
(18:27):
I have head of data engineering being a woman, I have a lead of APIs, which is really important to us being a woman. And even though under representation of females in stem, they do exist there. We just need to look harder and give them a chance.
Peilin Corbanese (18:49):
Thank you, Tatjana. That's very inspiring confidence. So Gina, you have a very unique organization. Can you talk a little bit about all your female executives that are leading technology?
Gina Hardy (19:02):
Yeah, I think that a lot of it is about culture. You're creating a culture where people want to work and they gravitate towards being able to work. And not every culture is right for every organization, but it's also about seeing people and actually believing in them maybe even more than they believe in themselves. And because I do find that sometimes my male associates have, and I know you've talked about this, that if there's 12 qualifications that's needed for the job, if they have two, I got this and I even see this, the difference between my daughter and my son, my son, typically he will tell me, I've got this and my first alert is probably not, probably need to talk more. Whereas my daughter, I feel like she needs to be amplifying herself herself more. And so what I try to do for people is sometimes I will put them in charge of a very significant material project knowing that they may be a little over their heads, but then employing what I call situational leadership, which is I know that they are on the low end and I need to lean in and I need to lean in a little bit more to make sure they don't fail.
(20:22):
Because if they fail, I fail. The organization fails. And speaking of my female CIO, which I'm very proud of, tequila's in the back of the room, tequila came to our organization as a, and it's all come full circle. She started as a computer science major in college and then she changed her major. She then had a very successful career in underwriting and marketing and I hired her in our company as the director of underwriting. Well, we were starting to make the Guidewire transformation and I decided that we were not going to use an SI that we were going to learn to do it without an SI and just occasionally use companies to support us in those areas where we didn't have expertise. And so I divided up the staff half went over to the IT half stayed back in the working organization and she was the underwriting manager that went over to put in our underwriting system.
(21:17):
Well, she did great job. And then I put her over my bas and then I put her over my programmers. And so now she ever saw herself as becoming a CIO, but she is the best CIO I've ever had and she is fantastic. She knows the business really well and I'm really proud of her. And that being said, we have someone else that we're grooming right now, but her cultural aspect has been taught not to speak out. And so what we're trying to help her is we want to hear your voice and sometimes we'll talk to her even before meetings. We really want to hear your voice, please speak out in the meetings and also teach her to understand that it's not a safe space that she might be going into, that it's a courageous space. And I think for all of us, that may be the one that's different in the room that if we think about it not as being a courageous space, not as being a safe space, but as being a courageous space, it helps us to brace ourselves when sometimes we get the eye roll because our opinion is a little bit different or that we're looking at something from a different perspective.
(22:34):
So I think that that's how we're trying to cultivate it. Both have an organization that people try to get people into a multitude of ways of recruiting and then trying to put people into projects. I also sometimes will put people in a role without first giving them the title in case they try it for a month or two and they hate it so that I can easily move them back so that it's not a reputational risk that they realize this is something like with tequila kind of edged her up to CIO as opposed to putting her in her role where she wasn't ready to do that. And so I think that that's the strategy as well.
Peilin Corbanese (23:17):
So when Gina said that it's not a safe place you are going into, it's a courageous space, my scalp just tingled. So having said that, this is actually not on the script. We did not rehearse this. We should talk about the differences of how you build allies in your organization because there are a lot of words I've been mentioned here, mentor, this is my mentor, she's my mentor and she's my ally. These are the kind of things that we need to talk about. We need to know who our mentors, allies and sponsors are in the organization and how you build them. So let's talk about that. And I'm going to start with Tatjana.
Tatjana Lalkovic (23:56):
So I think I have a particular passion to improve where I feel there's a huge importance and opportunity to improve. And that is women supporting women. And I think we have something to learn from our male colleagues. I often say you would have a discussion about an opportunity and you would right away have one of the men say, oh, my body knows that and let me introduce you. And in a minute there's like three or four people that they would name. And I think, I'm not saying we are not doing it, but we have an opportunity to be way better at that. I talk about mentality of abundance, so there's enough for all of us to be successful and progress in our career and generosity. And so at the earlier panel, what really inspired me talking about finding those connectors, be a connector, connect those women to the opportunities that exist out there because sometimes that's all they need an opportunity to be introduced and given a chance.
(25:15):
And I think we need to do more of that. Recently I joined the circle of women. There are different industries, different backgrounds, they're not all in technology and we spend a lot of time on a regular basis together. And at the end of the dinner when if we have dinner together, we would say, what is your ask of the group and what is your offer? And it's such an empowering discussion and there was so many great opportunities to came and learn that came out of those conversations and I think we should do more of that. So that was my passionate statement about allyship. Doesn't explain how I build all of it, but this is my mission to do more of that and kind of pay for it.
Peilin Corbanese (26:10):
I was told not to touch the mic, so I couldn't do that thing. So when I met Jamie, your LinkedIn network isn't your connectors, they're just connections. They're not really your people yet. Until Jamie was doing yoga exercise, her feet was up on the wall while she laid down on the floor. So I walked toward her, I said, whatcha doing? And she told me what she was doing. She said, I'm relaxing my back. So then I laid down on the floor, I put my feet up and we started talking. So Jamie, tell us a little bit about how you build your allyships.
Jamie Warner (26:50):
To be clear, it wasn't at the conference.
(26:54):
Yeah, I think one of the things that is really important to think about is having connections that are meaningful because you can help them and they can help you. And I always like to think, I love in the keynote how she was talking about the value you bring as you, I think early or in my career I was having trouble articulating sometimes I'm bringing you value as well as you bringing me value. And especially in the AI and data space. To kind of tie it back a little bit in, it's really important to have your partners bought in because it's a hard thing to do and you need it and you need all these areas that are cost centers to the business. And so one of the things that's really cool about building those allies is they're building something for you and then you can then show the value that it's adding to the business and tie it back to things like the combined ratio, which they might not be using in their terminology or tie it back to something that's going to make a really big impact.
(27:48):
And those people have been kind of really close. I'd say the other thing is not hesitating to make it personal. I know she just stepped out to get on the next session, but the way Palin and I met for the first time was at a group retreat. Someone, Marissa Buckley recently just grabbed a bunch of us and said, why don't you guys join me right before the conference and let's get to know each other and let's build that women's network. That's the old women's network, not the old boys network. And that really made an impression. All the people that I got to spend time with that week, I had a lot of personal conversations with them and have this really excited energy and connectivity. And they've also really opened my eyes as we started our cloud transformation. I called Gina and she had me talk to her technology people who are solving the same type of problems. And a lot of it is that we're all struggling with the same types of problems and if we can connect to each other. So I think going back to that earlier request from Patricia, if you guys can all meet three people here and start to make that personal connection, whether it's yoga at the pool or elsewhere, that can really start to build a network of allies, not just within your company but outside to help us solve these really tough problems we're facing.
Peilin Corbanese (28:57):
So coming back full circle, since we're talking about gen ai, it's a technology that's here to stay. So how do we upskill? Because many of us, well at least me, I'll speak for myself, I went to school many years ago, so I recently went back to school to update myself to upskill without prompting by the company. So how do we learn generative AI in our day-to-day and build allyship network and still exceed or meet the revenue and profit margin goals? Gina, how do you do that?
Gina Hardy (29:33):
I think that you need to continue to look at experts and you also need to look at those companies that have skinned their knees and what could they have done to maybe avoid that happening to them. So I think constantly learning. I'm a big believer in partnerships too. We do a lot of work with other big clients of the same platforms that we have. And I raised my hand like Guidewire is actually doing a lot of stuff with AI right now and working with vendors and incorporating it. And I was like, let us volunteer. Let us try, let us be on your advisory panel. So I think trying to hold up your hand and Bene Brown said, and I'm from North Carolina, we don't have a lot of ice and snow understand this. And she talks about turning into the ice and snow. So I guess for a lot of us it may be like that. It's like we're constantly trying to incrementally try different things and see what works and what doesn't work, but making sure that we always come back to a business case for it. Because sometimes you can plow a lot of hours into something and it doesn't really make the business case for it. So really what is going to be the best uses for gen ai that's not going to get you in either public perception, hurt, your reputation, there's just a lot of things to consider as you're weighing it all.
Peilin Corbanese (31:10):
Okay, we have eight minutes left. So I'm going to do one takeaway for the audience from each of the panelists, and then we are then going to open for questions. I don't want you to think too much, Jamie. Go.
Jamie Warner (31:24):
My takeaway is go download a Gen AI app and try it if you haven't. That's my only takeaway.
Peilin Corbanese (31:31):
Smart Tatjana,
Tatjana Lalkovic (31:33):
Lean in and have fun with it. I loved how our keynote speaker Jean was amazing. She says, if you're doing something that you know can make an impact, you have something to give and you like what you're doing, you're going to do the great work. And I think that's true.
Gina Hardy (31:52):
There's a lot of amazing podcasts right now that are not only related to insurance, they're related to AI in general. You need to listen to as many thought leaders as you can as you develop your own strategy.
Peilin Corbanese (32:06):
Well, since I focus on gen AI cannot help but give my one takeaway as well. Start small. You can have gen AI use cases. That's the internal facing, you can even put all your data in your dungeon to start. So we have six minutes left. Are there any questions? So we're all ready.
Gina Hardy (32:35):
One down here.
Peilin Corbanese (32:35):
Embrace gen AI.
Jamie Warner (32:38):
There's there.
Audience Member (32:42):
Thank you. I was a bit in and out, so I apologize if you've already addressed this. One thing that worries me a lot, my purview is really the younger employees with the insurance and attract the next generation. I worry that if we let AI automate away a lot of the entry level work, let's say underwriting, if AI does all of the easy underwriting with the human in the loop for the higher stuff, for the more difficult stuff, how do we train the next generation to be that higher level underwriter if all the entry level stuff gets automated away? So basically, am I wrong and are there any efforts in our industry for what I would call purposeful inefficiency in order to create that effective future insurance professional?
Jamie Warner (33:32):
Jamie? Yeah, I have some strong thoughts. So this is a great question and I think it's really about what you use the AI for and what you use the human for. If I think about our industry today, we really struggle for talent in the spaces of the call center, the junior level employees in terms of pay, and also just in terms of the struggling parts of the job. And we really struggle to train them up to get someone who's really effective in those spaces can be six months, it can be a year, and then they're turning over and going to the next thing. So to me, a lot of it is generative AI can make your training much easier. Where's that doc? What's the condo rule? What is this piece of information? It can really help you with bots and tools to train those people more quickly so you lose a little bit of that training scale.
(34:18):
The other thing is a lot of the things that's taking away are work people don't enjoy doing. So searching through documents for information, taking all the notes at the end of the call and making sure they had them right. And so I don't necessarily think it's that you're getting rid of the junior level employees because you're still going to have smaller claims and larger claims, or you're still going to have less complex and more complex cases. It's getting rid of that busy work around it and making them more effective at actually having the time to spend on the case and see, oh, I noticed that there's an issue with this particular health condition, or I noticed that there's an issue with this house that I otherwise wouldn't have had time to look at because I have five minutes to turn over this call and do all the documentation. And so to me it's an enhancer. It's like they each get an intern rather than it's getting rid of those layers. And I don't know if you guys have other kind of opinions on that one.
Tatjana Lalkovic (35:09):
No, I think you're spot on. And I think what's very important, they say generative AI is going to replace people that do not know how to use generative ai. So training to work and augment your work with generative AI is actually very important. But I think that's where is exactly we are going to go, we are going to be more productive, do more meaningful work and think about tasks that are not value add and that are going to be automated. So
Gina Hardy (35:45):
You saw some of these same fears when we were allowing agents to have straight through processing. So it seems like just the next iteration of that.
Jamie Warner (35:58):
And I would say that those junior level employees also love these tools. They're much more interactive in them. So if you don't give it to them, they're going to find a way to use it.
Tatjana Lalkovic (36:08):
There is one thing that I keep thinking about and I don't have an answer, so if anyone figures it out, please let me know. Studies show that actually people that get more productive using generative AI are people that are actually very good at their job already. So what that makes me think, how does that next generation, the training is going to get easier, but how do they become experts? And I don't have an answer, but that's something that I'm kind of spending time thinking about. What is the way we formed generative AI factory of cross-functional teams between engineers, data and business teams, and their job is to figure out how we best democratize AI across the company and train people to that. So that's one way.
Peilin Corbanese (36:59):
Okay, so I have to ask Gina this question. So for the people who don't want to adopt generative ai, how are you going to help them? Because Tatjana just said that the people who really adopt and become very professional, they're already really good at their jobs.
Gina Hardy (37:16):
I think it's about trying to explain to them that we're not trying to replace jobs that we're trying to become, we're trying to service our customers more. Our mission is to restore lives so that we can process their claims quickly, especially after a hurricane. When we have a hurricane, we could potentially, and we did in 2018, we had a hundred thousand claims. And so when we have a hundred thousand claims, we have to have all the technology to be able to restore lives quickly. And so I think it's really about communicating that vision and that mission down. And we also, if we're going to allow people to work remote and some companies allow two days remote, some people allow five days remote. And what I've told my staff is that we can remain remote as long as we can keep our quantity and quality at the levels that we want our quality and quantity to be at. And so I think they are embracing tools because right now they like being a mostly remote workforce. And so as a result, I can't give them enough tools because they understand that that enables us to keep working the way that they've chose to work. So I have not committed to a remote workplace, although we have a remote workplace, it's only because they are able to have the quality and quantity that we can continue to operate in that way.
Peilin Corbanese (38:42):
So quick takeaways for the audience. Use Gen AI as your intern, right? Change management and threaten them with, if you don't do gen AI, we are not going to be remote anymore and build your allyship. Therefore, ladies network. Thank you very much.
Effective Leadership in the Era of AI
July 26, 2024 2:28 PM
39:12