Transcription
All right, morning everybody. Happy first full day of Eltaon and happy Tuesday. Um, thank you so much for coming to the session. It's going to be a great hour this morning.
Uh, I first wanted to, before introducing our panel and and everybody, just show of hands in the room. How many of you work for an in-house legal department at a corporation? Not oh, one. A a few. A couple of hands. Awesome.
Um, how many of you are at big law law firms? Many. That's the majority of the room. Uh, how many of you are at small medium law firms? Awesome. Uh, anyone at uh, a legal tech vendor? Great. We've got representation and yes, same from Lata. We've got representation kind of across the board that we're going to cover today.
Uh, I am Cynthia Gumbbert. I'm the CMO of LTERA and I'm really, really happy to introduce this incredible panel of powerhouse women leaders across different um, the legal landscape. So, uh, I'll just let you start with Carrie here. Do a quick intro.
>> Hi everyone. I'm Carrie Rumhoff. I'm the director of firm intelligence at Troutman Pepper Lock. Newly merged on January 1. I survived. Anyway, excited to be here.
>> My name is Tanya Kohl's and I'm a principal corporate counsel at Microsoft. I support our state and local and federal business with um compliance. I've been there for three years and I also survived our most recent layoff.
>> Rachel Recart, uh, chief of staff to the CEO at Lata, uh, background in transformation and growth strategy.
>> Awesome. Um, so we've got, uh, large law, big law represented. We have in-house council at one of the biggest companies in the world, Microsoft. And then we've got one of our legal tech vendors represented with um, Lata here.
Um, before getting into the panel um, just the reason why this topic is so important and timely and it looks like we are filling the room and and you all agree with it is that uh getting the tech stack the perfect tech stack, having all the best tools in the world um, really doesn't get you there. Um, it's about the transformation and it's about getting people to actually use what you've put in place. So, we're investing a lot of dollars into technology. Um, we have to invest a lot more into actually getting it adopted.
Um, a couple of stats here. Uh, 84% of digital transformation projects fail. They take years. I used to work at Dell for many years at CA technologies, large tech companies, and I can really attest to this that you're spending so many dollars, taking years, and you're never quite done. Never quite done. Um, and according to McKenzie, 84% of transformations do not do not get there. um, something about small companies under a hundred people uh have 2.7 times more chance of like actually succeeding and adopting technology. So uh, there's something about that that we're going to talk about today. What is it about small, agile, agile companies um that can move a lot faster uh and get you know, advanced in their tech stack more quickly?
Uh, and then this one, as we were prepping for this yesterday, 50% of lawyers fully use the legal technology that they have at hand. Uh, as we were prepping for this, uh, everyone on the panel just said, "That sounds really high. That sounds really high." So that's ambitious. Uh, so how do we get past some of these big headwinds that are working against us? And that is the point of this panel.
So, um, I can leave this right here and um, we're gonna start with Carrie with a couple of questions and um, I will fire away. So, Carrie, you've implemented foundation now twice at very large law firms. Uh, can you share like what factors led to a successful implementation there? And this is not all about foundation, but this that is a huge transformation project and product, and doing that successfully is um, a big undertaking. So, very, very interested to hear your story.
Yeah, definitely. So, I've worked with experience management for about 10 years. Um, and the first firm I worked at, I implemented it twice. Um, so the the first time we didn't involve anyone. We just made decisions ourselves of like, we're going to just build this thing and people are going to come to it. It's going to be amazing, right? Okay. We built it. Nobody came. Nobody at all. Right. Okay.
So, then I heard about this really cool tool called Foundations. This was like, I don't know, a minute ago or maybe 10 years. Um, but but with that um, the technology was really impressive and and um, at the time Foundation had built this platform that people had asked for um, and I took a different approach. I said, I need to include in include all of my staff departments right to come together to say, okay, finance, I don't want you to be threatened by this system, be a part of it. Like, include the fields that you want people to see because like, you know, how annoying it is when the marketing team comes to you seven times a day, like, give me this, give me that, give me this, right? Well, let's give them a tool where they can access that data from the start. If they need to go in depth, they sure they can continue to come to you, but let's give them a high-level piece of information.
So I created a committee of about seven different departments within the firm, right? So it was new business, it was finance, it was um, marketing, business development, it was all of those pieces came together and we defined the system together on what we wanted it to be. And really, it was just just the fundamentals of change management, right? Overcommunicate, involve a lot of people, get them involved. And with that, we did see adoption.
Um, and then with that, I became such a fan of foundation. I worked for Lata for a couple years. So see some of my former customers over there. >> Hi Paul Veneza. What's up? Um, but with that, it was so fun to like share the journey with other customers, right? To say, hey, here's some best practices. Here's what's worked. Here's what didn't work, right? Um, let's learn, get some lessons learned and and do that.
Um, and then I've been with Troutman Pepper Lock now for two years, which has been so fun. There's my Troutton people over there. Shout out. Um, um, Troutman has such a spirit of innovation. Um, so I stepped into that role where the firm had had foundation for eight years. Um, so I just came in to sharpen the pencil, like, hey, let's just refine it. Let's take a look at it. Let's see what we can do better. Maybe maybe I can create a committee again, right? Engagement from all these teams to say, why do we have this tool? You know, why was it built, you know, four mergers ago, right? Let's get the get the new people in there and using it.
Um, so really, the key to adoption is people, right? So sure, the technology can do what it can, and I love our legal tech vendors um, but the hardest part and probably 80% of the work is like change management, people management.
>> That's really interesting and that, you know, you're saying the job is never completely done because you go through internal changes and reorganizations and you can't just assume that people are going to continue using it if they're, you know, different folks coming through. So you had to implement things twice.
>> Or or three times. So it's it's an ongoing process.
Um, Tanya at Microsoft, uh, we you're seeing we're seeing a huge AI, Gen AI transformation and that is technology adoption at a whole different level and a very recent development of all of the AI innovation that's come into play. So, can you talk a little bit about, you know, how that compares to traditional or, you know, I guess traditional technology adoption and um, how you went about that within Microsoft?
Yeah, I think with traditional adoption, you know, if you look at, you know, when PowerPoint was rolled out or Excel or or Word, that was it. You know, that was that one um platform that you had to learn and everybody went ahead and learned it. And there were books, you know, Word for Dummies that you could go and and buy and and look at and do all that. But, you know, AI has been a little different because, you know, they came out and said, "We have this, you know, relationship with um chat GPT and we're gonna we're gonna go ahead and do this." And I was at our annual conference. It was October two years ago. And Brad Smith, who is really way up there in the company, he rol he came and said, "You know what? We we're doing things a little different and we're rolling out co-pilot to the legal staff first." And so for the whole company, our legal team got it first. And um, and I look at this stat where it says only half of lawyers fully use technology. They wanted us to learn it. And so um, we got the the beta versions and it keeps changing and getting better and better, but I think that was how it was done a little different. And I've and our we have legal teams embedded in all of our product groups and and across the company. So, there are a lot of legal staff within Microsoft and I think it's interesting because I'll be on a lot of things and I'm like, "Oh, maybe we should try recording this and do a transcription. Maybe we should do this." So, I think the legal team is actually providing input to the rest of the company because we've been using it longer, you know, and so as things roll out, we're able to pick up and start adopting them faster than the rest of the company.
>> That is great. It's so great to hear that because that's probably not the case everywhere where the legal team gets the most advanced technology first. So really, really, really exciting.
Um, Rey, so at Lata, us as a legal tech vendor and AI um marketer, we are both marketing and selling new technology and AI and also internally adopting it ourselves. So we're going through this transformation of having new products to talk about um, but needing, you know, to use it internally. So how does that dual factor affect our approach to transformation and adoption?
Practicing what we preach is a core element in coming up with our adoption strategy because Bangga at Microsoft talked about this yesterday that being customer zero gives you a lot of insights that you wouldn't normally have around adoption. Um, I think that we at Latia using these AI tools are then going through that same change management cycle that Carrie mentioned where we are learning on the job and then using that to apply uh to our products. So, those of us that are legal uh tech vendors here, I I would say that the most important thing if you could start with the best case, it's using the interface for adoption. Having to put together adoption programs and training and teaching people all of these things. If you can leverage the interface and make it so easy to use, that is the first hurdle to ensure high adoption. If you can't do that, um, then understanding that change management life cycle and really understanding that people are going to um, it takes a while to change a habit. They have to have a a different mindset about adoption and understanding um, that people are approaching this from all different angles and different walks of life will really help in defining that adoption journey.
>> Well, that's that's great. Um, yeah, it's it's it's a lot. We're all like transforming very quickly at the same time.
Um, Carrie, back to you at law firm, especially big law. Um, it is a risk-averse group of people who who we all serve as um, lawyers. And how does that nature of law firms and lawyers being risk-averse themselves impact technology adoption? Um, how do you address any concerns that come up with using something new?
>> Well, we always look for those early adopters, right? Someone who is eager or someone who is super angry, right? And they are like so irate about some business process that just isn't working for them. It's like, "Oh, I want to find something to make your life better." Right? So, it's like they're in the moment. They're focused on it. Um, I try to solve their problem, right? That's what I like to be is the problem solver. Um, and I try to give them something better, right? Because if they are irate and angry, like they are ready to look at it, right? So, um, a lot of my role in firm intelligence is around data capture, right? And all data is dirty, like all of it, right? As me like as much governance as I put in and as hard as I try, like I'm going to have dirty data.
So what happens when we do bring an attorney into a process, right? Their first thing is, is this isn't right. Right? So that that can be so deflating to my team of like, oh, I worked so hard on this for months and then, you know, I'm getting this negative feedback. So I've I've taught my team feedback is good. Like you want feedback, good or bad, because that tells me they actually looked at what you sent them. Like they actually logged into the tool, they actually looked at it, right? It's like, well, then let's work with them to come up, well, you're right. We're missing data here. Well, how can you help me get the data in there, right?
So, when I first came to Troutman, there was this philosophy of we're going to get every practice group, you know, profiling their matters and foundation, right? They're going to get in there. They have so much time on their hands to just like go in here and like profile my matters. Here's my judge. Here's my court. Okay, I got realistic. I was like, they're not going to do it. They're not. I've accepted it.
So, I came up with ways of like, well, how could I get it during the matter life cycle or is there a third-party tool that I could integrate with? Like, give me the data from somewhere else because lawyers are so good at refining things. If I pull together some stuff, right, and give it to Tanya and be like, "Hey, this is the case you did," like, you're more prone to come in and say, "Oh, well, you you you were 70% right." Right. And here's the rest of it. Versus giving someone a blank page.
And you mentioned, you know, sometimes things are deflating when people say, "Oh, none of this is right." And it is hard. You can't forget that kind of wellness aspect of those of us who are working to to gain adoption. When you start to see things falter or just slowed down. How have you overcome that slowness in the past?
>> Yeah. So, I've engaged um my staff departments, right? So, our business development team knows the practices the best, right? So, I always look as them to them as my liaison, like how do I best interact with this practice group? I just look for help. I look for peers, right, of collaborating of, you know, okay, this attorney said this. What is their personality like? How can you help me? What do you know about them that we could get it together? So, I try to put the effort in behind the scenes and then go to the attorney like, "Hey, I met with intake and they said this and I met with this and right, and then it shows I made effort, you know, I did some homework before I just called them and said, well, you need to fill this out. Good luck to you."
>> I think understanding Sorry. I think understanding the right you talked about setting your team's expectation. We roll this out, we get feedback, but also understanding the adopters or helping them set those expectations out the gate goes a long way. I talk about the phases of change from a psychological standpoint. Everyone is going to have uninformed optimism. That's what we all do when AI comes out. This is going to change our lives. And then you get it and you have uninformed pessimism where you go, "This can't do anything." And then you go through the stage of informed pessimism where you're like, "Okay, I'm starting to learn. I'm not sure it can do what I thought it was going to do." And then you get to informed optimism where you are a power user. You have worked all of the things out. And understanding that that life cycle has to happen every single time a user comes into the game also helps our teams that developed the product or that you know put a lot of effort into customizing the product for their users understand that it's not failure. It's a normal psychological cycle that everyone has to go through for adoption and for change.
>> Yeah, that's so true. When we like announce a new product or a new feature, like I overcommunicate these are the positive things it's going to do for you and this is what it's not going to do, right? Let's just go clear out the bat, like like this is not going to be there like we wanted to get you something up and running as a prototype, get you in there.
>> We have ideas for future phases, but I didn't want to wait before I gave you like something of value.
>> Love that, love that. Um, when we were prepping for the session. Uh, Tanya, you also mentioned that learning AI, learning Jan AI is like learning a new language for many. Can you elaborate a little bit on that? It was such a great conversation we had.
>> Yeah. And I think when you're when you're talking about informed and being depressed and all that, I don't think he is depressed, but that's sort of how I was feeling. Um, I think I we they rolled it out to us and started doing everything. And at a certain point, you know, prior in a prior life, I went to school to be a high school Spanish teacher before I went to law school. And um, I of course had to learn a foreign language, but I didn't go into class the first day and they're like, "Here's Doniote. Have a great day. Let's talk about it tomorrow." You know, we started with what's your name? You know, how to say your name. And I think we practiced that for a week, right? And so I think with AI and especially um, learning how to do the prompting and everything like that, it is like learning a foreign language. You have to start small. You you know, it's very frustrating when they come out and and they say, "Okay, everybody, we're going to start, you know, making agents now." Like, whoa. Like to make an agent, you're going to have to have great prompts. And if you didn't learn the prompting one, you know, you're kind of out of luck, you know. And I think for the engineers, it's a good way to say, you know, when you look at math, you have to learn the foundations first. Is if kids haven't learned how to, you know, add and subtract and do multiplication tables in their head, by the time they get into high school and they're doing other things, they're going to be left behind. And AI is the same way. If you don't start doing the simple things, you know, have it try to draft an email for you. That is like the easiest thing. And I use it constantly. I have like the white paper syndrome where if it's just a blank paper, I'm sort of like, oh, what am I going to say? And it takes forever. Or I know what I say and it just goes on and on and on and then I have to go back and edit it. Well, I find I just do that on and on part in the chat portion and like draft it and then it creates an email and then I go from there. And that's like the simplest thing that everybody can do today, you know, open up if you're using um, whatever it doesn't have to be C-pilot, whatever one you're using, but just go out in your in your mail program and just every time you draft an email, use Copilot. You use your AI and draft it that way and it'll be amazing what you see and you'll find you're you're saving time doing just that.
>> That is great. Um, and Tanya, just a a quick follow-up question, which is kind of the elephant in the room for a lot of people adopting Janai, especially in the legal world. Um, how did Microsoft address concerns about um, just data privacy and security um, when confidentiality is so paramount in this this industry part in particular?
>> Yeah. I will say that in our team, that was our biggest concern, like when it was first rolled out and I was like, who, like I'm going to ask a question about something I did, like, who's going to be able to see that? You know, who's going to have access to that? It have really was frustrating for me. But I but we've learned that, you know, it comes to your IT department. The IT department is supposed to set up the security. You know, if I share a document with you, but I don't share it with you and you both ask a question about that topic, you may get answers that had answers from the document, you won't because you don't have access to the document. And so I think a lot of it comes back to, is your data clean?
Have you put in the correct security measures? Do you have firewalls? If you're having if you have to firewall off C one customer for another, are they not part of your of that data group? And so, um, and you can create entire groups, like I do post-government employment. So, if anybody's coming to work at Microsoft and they've worked in the government before, we have to do this whole review. Like, I have all the documents associated with that in one vault together. And when I ask questions, it's just looking at those documents. It's not looking at stuff all over the company. It's just looking at the data I want it to look at. And so, um, I think it's important, you know, to make sure when you have agreements with companies, you know, are you training the the the model? You don't have to be training the model. That's an option. And so, you have to make sure that you put those things in place. And I think once our team figured out that I couldn't see things that you didn't share with me and my that document that I asked it to look at and answer questions about now does isn't being used to answer questions for everybody in the company. Um, like my stress levels went far, far away, like I was like a like, oh, okay, now I can ask questions and I can do things and I don't have that fear. And I think that that's a big thing to avoid is fear.
>> Great. Uh, Rachel, when uh, again, when we were preparing for this and as we're rolling out Gen AI quite a bit, you've compared it to training a new employee. Can you talk a little bit about that?
>> Yeah. >> Yeah. I was talking about um, how a lot of times as you're exploring a new product, right, because there's so many out there today and they all have different strengths and weaknesses. Oftentimes I'll get halfway down a path and realize like this would have been faster just to do it myself. And it made me think about, wow, that's the mindset a lot of us have when we need more capacity and we're like, yeah, I really need a team underneath me, but just training someone is going to take just as long as it would to do it myself. But as soon as you find that prompt, you find that right tool, you finally unlock that use case, your capacity skyrockets, right? So, it's just like with a new employee, once you put in the time, the short-term pain for the long-term gain, you do see that burst increase in capacity. Um, but you have to come out the gate with that mindset of, listen, I'm learning a new language or training a new employee. It is not going to solve world hunger on day one. It is going to be painful to learn and to teach the tool how to work with you. But as we've all seen with AI today, the more that you interact with it, the more it learns about you, just like an employee would. So they learn about your style, they learn about what you're looking for, and they produce better results each time. That's what these tools are starting to do. I think that's the case for just any kind of transformation where everybody has their way of working. That's probably the biggest hurdle. They have the way that they know how to get things done and having a new tool in front of them is it's like an inconvenience for a while. And um, just getting past that to the end state is better than where you are now, but there is a hump to get over to get to that end state, right? Um, and um, yeah, that's something, you know, we've all talked about a little bit. Um, and you know, Tanya, you mentioned like there's catalysts from different groups. So I think show like handholding people through that transformation. So they don't go to the training, see the new thing, and then just go back to the way they've always done things because that's just easier. Um, how do you get those catalysts, just catalyst to change so the change actually sticks?
>> Right, yeah. I think this statistic here in the middle, the 2.7, like the smaller organizations are easier to get to have adoption. And I think what we did is our groups is we created smaller groups. So I was one of those people who was really excited about it, you know, Carrie would have been like, hey, I like her, right? >> So, um, I became like a C for AI catalyst. So I became someone that would help train my team. And so when I would have team meetings, I'd have my five minutes, you know, um, I was one of the people who was selected, you know, Microsoft did a LinkedIn campaign with videos for for legal one, you know, and they pulled from people in the company and they asked if I would do one. And so we do different little bits, like I I I take it on for myself to read. There's this one person that sends out these emails once or twice a week with prompts and I'll look at them and I'll read them, like, let me try that one, see if it works. If I like it, you know, I'll share it with my team. I might do a LinkedIn post, like, try this, do this, see what happens. And so I think we started with smaller groups and we helped to train ourselves, you know, train the trainer type thing. And um, I think it's really helped. We've also had competitions amongst groups to see who could have better adoption. Um, and we've said, you know, all you have to do is that one email a day. Do that one. Jack that one email and you get credit for the team. And so that has helped with adoption as well, but we've started small. You know, yes, they rolled it out to this huge room of 5,000 of us, but we then became smaller groups to help learn together because you learn better in a small classroom.
I think the number of the small groups, but the point you just made as well about just sharing like what works, what doesn't, >> builds a big community for adoption. So, it works a lot better in small groups to say like, "Hey, here's what works, here's what doesn't." When I talk to someone about a tool that I like or don't like, and they're like, "Yeah, that's all I use it for, too." Or like, "Yeah, I only ever use that tool." That builds a little bit more loyalty, a little bit more like, "Okay, I'm going to go back and try it again. And I'm going to keep using it, etc." So I think the sharing and the feedback of like in if you can create groups that will share what's working and what's not working um, you will drive that constant adoption.
>> Yeah. I think the other thing that's an issue though that I see is that all these small groups are creating everything and then they're like, let's put it all in SharePoint. Then it's like, then suddenly it becomes overwhelming again and I'm just like, oh, I can't look at that. It's too much. Like I just want five prompts to start with. Don't give me a website with 5,000. That's too much. I'm not going to be looking at that, you know? And so, I think, you know, you also have to think about how to do it and keep it under control. Like, don't go crazy.
>> Well, it also opens you up to like having a growth mindset, right, of like sometimes try it. Like when I first tried our chat thing and I'm like, nope, this is not for me, right? But then like two months later, I'm like, okay, I should get on the bandwagon, right? So like trying to be open to it, like find make space for like to to be open with it or call a change agent like Tanya, be like, what are what do you use this thing for? Right? Okay. I'm going to start drafting emails this way. Um, so I think that the grassroots effort is always always a good approach too of versus the five, here's 5,000 prompts, right, that have nothing to do with my job. And then maybe not just use it at work, you know, maybe use it in your regular life. If I think you start using it regularly in your regular life, like my husband and I have these little competitions about meal things. I'm like, I'm going to try my co-pilot recipe. You try yours. Let's see what happens, you know, and or I was visiting my parents and my dad has a Samsung and I had no clue and he is 86 years old. He's having problems. I've got my co-pilot up and I'm companion and I was talking to it. It was talking to me. All of a sudden, he was like, "Who are you talking to?" And I was just, "Oh, no. Oh, it was just AI, Dad, just the computer." That was not a computer. I heard a person's voice.
>> I said, I know. I said, it's my companion. Um, I I can talk to it like a regular person. He's like, oo, I need one of those, you know, and so, you know, things like that. So, my dad's 86, you know, and we have luckily at Microsoft, we can share um, stuff for a very small amount to like multiple members of our family. And my dad uses it now to just chat with it. My mom's like, "I hear your dad in there talking." I was like, "Has he changed the voice? Who's he talking to today?" You know, but you know,
>> Your mom should be thankful.
>> That's right.
>> He's occupied.
>> He's not asking her how to do something.
>> My 84-year-old dad talks to chat GPT all the time and he comes back with, "It got this piece of your resume wrong." So, I've told it to correct it. It's really funny. I think, you know, there's there's ways people are finding to use it, you know, at all all stages of life.
Um, Rachel, how important is it to get to the underlying why people want to change and the psychology around what is what are the motivational factors that you want to dig out when you're going through a transformation?
The only way that you're going to get people to adopt a tool is to understand their why. Honestly, because everyone's why is going to be different. It's why there are so many tools out there today because people are building them for different use cases, different strengths, different um, ways to even interact with an agent. So, for example, um, we use AI a lot in Lata. My boss Avanish loves C-pilot. He swears by it, he uses it for everything. His use cases though that he, I think he spoke to this in the um, company update yesterday, are to be able to attend 20 meetings at the end of his day and say, co-pilot, tell me what I missed here, etc., etc., etc. I love Claude. Claude is my like, I don't know how I would do my job without Claude today. But my use cases are more to help enhance my thinking to say, hey, I need to build out this entire plan. And here are the points I have today. So, help me build out an adoption plan or a uh, we just rolled out new core values at our organization and I wanted a a whole launch plan and I can give Claude four key points and it rolls out an entire white paper plan for me, different use cases, different whys. Oops. Uh, his why is productivity and time savings. My why is to enhance, I mean, it's a little bit productivity and time saves, but honestly to build out on concepts that I haven't had time to fully think through. And there are different tools for your different whys. So understanding people's why will help you select the best tool, which is why I think it's the most important part of adoption.
>> Yeah, I completely agree with you on that. You know, I use co-pilot for email, for creative stuff, for everything like that. But, you know, our team is also looking at third-party products, you know, and our legal team has been um, working with Harvey AI because it's designed more for legal. It has a whole legal background. It's it's taught differently than co-pilot. And I find I go to that for a completely different reason, you know, to help assist, to help do stuff. I, you know, I had to draft a training program and um, we did it last year and I put in last year's script and I said, "I need to update it. I need to add some stuff on CUI. I need to add some more stuff on travel around this area. Rewrite the script for me. Just rewrite it. Make it sound make it sound better." And then I just hit and it did it right. And then now I just have to edit it because I'm a really good editor. But um, it's so much simpler. But I last year we used Copilot to create it because we didn't have Harvey. And this year I used Harvey and Harvey has that legal background. So the script is even better. So yes, know your product and know your why. Are you using it?
>> Pro tip. Let has Leto. So come over and try that. Try that over Harvey. But that's just me.
Um, Carrie, um, you mentioned kind of full circle, going back to data quality, which is where we started, that just implementing foundation exposes that there's some there's always some data quality issues. When you layer Gen AI on top of it, it amplifies exposing >> what is going on underneath your data because you expect, you know, AI is going to come up with a perfect answer, but if there's something going on underneath, it's going to come out with not a perfect answer and people will just say this, you know, it they don't really associate the two, just the AI is completely wrong. So, how do you deal with that elevation of there's there's data stuff going on that has to be fixed before the AI works perfectly? Um, or just setting the expectations that this is this is going to happen and it's okay.
>> No, absolutely. We're getting ready to launch. We built some AI tools over top of Foundation at our firm. So, we're excited to kind of launch it out, but it's over like the attorney bios, right? And um, so we have our pilot program out. We have some attorneys looking at it and they're like, "Well, what about the attorney that has something in their bio that's like something they did 20 years ago, right?" Because on your external presence, you're like, "I'm amazing. I've done all these things my 20-year career. I spent five minutes on this 20 years ago, right?" So, it's kind of raising awareness of maybe you should update your your bio, right? Or what are the new things you've done that your bio is missing? So like in that specific case, we partner with marketing, like as we are rolling out this skill, we are also rolling out the business process of, hey, you need to update your bio. Like you want to be found for like experience you've done or you don't want to be found for experience you've done, like update your your your bio here, right? So AI, if anything, has really accelerated my data cleanup plans because now people see it, right? Whereas before, it was data cleanup was like a nice a nice to have, right? And I was like pushing the boulder up the hill of like, we need to clean this, we need to do this, right? But now that it's ex being exposed at such a higher rate, I can quickly say, well, this partner found this and it doesn't make any sense and we need to fix this all the way upstream. Like it it's really expedited the change within the firm, which has been pretty exciting because it's like I've been saying this for 10 years, like we should be doing this the right way.
Um, but also I educate, like as we are rolling things out, as we are using things and people are frustrated, I I listen to them. I said, I'm frustrated for you. I understand, right? Like, but help me get to a better place, right? Is it is it the biotechs we have? Is it this piece of data we're not capturing an intake? Like, you help me figure out this process of how to make this better, you know, for you and that'll impact everyone else. I think that's very important because if your data is your underlying data has problems, then your results are going to have problems. And I really do like that many of the um options provide, you know, links to where it got that great bit of information that you want to quickly delete. And so, you know, a lot of times I they'll say, I read the policy on this, but I found this with Copilot. I'm like, "Great, send it to me so I can delete it and then you won't have that link anymore." And so, um, but you know, I like to get the information so I can say, "Yes, we have a problem here." Like, where's this stuff coming from? You know, and sure enough, you know, we created SharePoint and then we created all these SharePoints and we created more SharePoints and more SharePoints. And so, I'm glad now that, you know, every once in a while we're asked, would you like this SharePoint site to continue? And some of them I'm like, please just delete it. Don't ask me anymore. And so, um, I think it really comes down to cleaning up your data, which is like pushing a boulder up a hill. Yeah. When people see the bad data, they immediately want to get rid of it. But, you know, to say, "Hey, let's have this great project to get rid of old data." Nobody wants to do that.
>> Amazing. Um, all right. We actually have a bit of time for audience questions. If anybody wants to ask our panel some questions, I'm going to stand up because this podium's got one here. That's right. I mean, yes, of course, if it's easy to make it easy. I think if people didn't hear, he said if you're doing adoption, it's not just making it easy. It's having it's making it easy to do the right thing. And and I agree with that. But I think you have to have like guard rails in place to make that happen. I think a lot of times with AI, it's just like it really is like an amusement park, right? And you have to choose which ride you want to get on. Do you want to start like with the little mini one or do you want to take your kid down the cannonball first to choose, right? How's your day going to go depending on what you do, right? And I think AI is a lot like that. Pick your pick your ride, but you know, go slow, right? Start with something easy like email.
>> Uh, question, blue shirt in the back.
>> Um, I think you made a really interesting distinction with something like the vast majority are not things are using. What are some key points?
>> Um, I can repeat that question as well in case you didn't hear it. What are some of the key things that you have found that help drive adoption outside of Gen AI, which is accessible in your personal life? Most of the core technology we use in law firms and legal departments are are not something you use in your personal life. So any anybody have uh some hope for that?
>> Like how to drive adoption to create to create things within your work environment >> that are only available in your work >> that are only available in your work.
>> You know, I I think a lot of times you have to have that brainstorming session with your group, like, what do we need help with? Like, what are we doing over and over and over again that we need help with? And um, I think there were only three people here who were um, in-house counsel, but in-house counsel, we do a lot of different things, but then there are are those distinct projects, maybe we always send to outside counsel to do because we just don't want to do them or we just need additional assistance. And I think maybe looking at projects like that and seeing like, what can you what can you do and try to and I will say the go ahead. Sorry, but to follow up on that, I think there's a slight difference with tools that aren't necessarily your mentioned earlier. I have my work ready. Yeah, it's cumbersome. I'm not getting. Where do you find the balance between what do you guys know?
>> Yeah. Are you um, I think that It goes back to again understanding how people operate. So the human element of this planning, not just your here's my adoption plan, but here's my abandonment plan as well. So here's how I'm going to re-engage people because they are inevitably going to abandon. So here's creating a new habit, right? It's like 21 days or 21 times of doing something to create a new habit. Well, if something is frustrating me, I don't have 21 times in me. I am going to go back to my old way. But in these tools, what um, a lot of the vendors are are doing is making sure that they are saving data so that when I do come back to the tool, it remembers who I am, how I worked with it before, what I asked it, um, the context, the settings that I created, etc. So, having a plan to say, hey, how am I going to re-engage people? Because it is inevitable that they will go on vacation and then forget this muscle that they just built. They will get frustrated and leave it and decide, you know, it's not for months later that they're like, "Okay, fine. I'll try again." So, I think that that is also another core element in part of the adoption strategy is just planning for the inevitable abandonment and how you re-engage.
>> I mean, working for big law, I take advantage of a lawyer's personality. Open, but like there's competition, right? So I find the person that is in the system right regularly, right? Reach out to them and say, how are you using this, right? That you could help champion it to your peer across the hall who has nothing to do with it, right? So I like to play on that competition of like, well, Tanya's doing it, but Rachel's not, like, how do we get Rachel on board? Um, that's, I mean, that's the only way I've found to kind of get past some of this adoption.
>> Yeah. And I think, you know, we have and we do have internal competitions.
>> Yeah, we do that. But you know, and I think a lot of it is um, finding their why, like why do you need to do it? Like, you know, how is it going to how is it going to help you? And I think that's really the the most important. You have to be able to to know why you, they have to have a purpose.
>> So much comes down to psychology, for sure. All right. We've had a hand up right here and then I'll you next.
>> to get more specific around AI. Um, I find that when we come to problematic, so the question, how do you get back to schools are such that for those who didn't hear the question was, AI really has a a lot of expectations that come with it where you hear this will save you 98% of your time and and then when it doesn't do that, people will abandon it more when it, you know, it takes a few hours to set up and takes you longer at the beginning, it's not meeting the expectations you had. Yeah.
>> Um, so how do you how do you manage that and then come back to it because AI it keeps getting better.
It's not the same tool it was two months ago. So, yeah, it comes back to communication. Like, so sometimes we'll do like a "Did You Know?" campaign, like, "Did you know this tool did this, right?" and kind of bombard people with, you know, another email that they want to see. Um, or we try to put something on the on the front page of something, um, and say it. Or we try to like get involved in the practice group meetings of like, "Hey, just give me five minutes at your team meeting. I'm going to show you two things that are really cool, right? And maybe a couple of you will pick it up, right?" So it really comes down to change management and communication.
Yeah, and I think, you know, that goes back to the role of the catalysts within our legal team. Is we do, on all of our team meetings, I have like my five minutes where I go over something new that I I heard or I saw, you know, and I do try to post those. And so, um, I think that's what you have to do. You have to truly try to pull people back in.
I think it can also help to set expectations out the gate. So, there's two, um, processes happening simultaneously. There's what the human is going through and what the tool is going through, right? So the tool is evolving every day, and the human, like we said, is going through that change cycle. So in the beginning, the first stage is the uninformed optimism, like I said, and the the tool at its infancy. So like a huge gap. And as you keep going, you guys are getting closer and closer together to say, "Okay, now you're a little more of the informed optimism," and this this uninformed because you're now, you know, you've gone through your pessimism, all the while the tool is getting better and better. And so helping them understand that this is where you are, this is where you're going to be, can get them through that really frustrating growth cycle.
And I think also just, you know, a lot of these the hype of AI of "it will save you 95% of your time." It it's not the case. It saves about 50% after really pushing and using this for a few years. And this is what, you know, we say with Later. It saves you a lot of time, 50 to 80%, but it's still your name on that document at the end of the day. You you have to have yourself in that loop. So don't expect it to like do all your job for you, and don't believe all that hype. It it's a huge productivity game changer.
Huge. But there's still a lot of work. You know, it's your craft at the end of the day. So it's important to just set that expectation. Um, we have the question up here, and then I'll, um, get get back to a couple more hands. Yes.
So, because there's so many metrics that we can measure, when you were doing your co-pilot roll out, what did you decide what success looked like? Was it a certain percentage using it on a daily basis, weekly basis? What? And how did you come to that decision? Who were some of the players that were part of that? I think we have a all up learning learning group that, um, was sort of trying to push this out. Um, and they did like daily user, weekly user, monthly user. Those are the stats that they used, and that's what they would roll out to see how people were adopting. Yeah. Really, that's, I don't know any other stat you could possibly use for that. I mean, I don't do a lot of that, but...
Did you kind of have like, "Okay, if we get 45% of our population this within one month, that's success"? Oh, yeah, they were driving more of, "We needed 80 or 90% you daily usage of our teams, you know," and so, you know, and they, and you could look at the group and be like, "Okay, there's four 40 people on your team and 38 are doing it. Who are those two? Let's go have a chat." And we made actually AI and evangelizing AI is a core priority for our legal team. Like it is one of, I I will be assessed at the end of the year on how well I've done at great events like this. Um, question back here.
Don't you think at some point we're losing our own? So, you know, we missed the person.
Well, I think, you know, it is co-pilot. It's not the pilot. So, I'm still right there. I will say, um, I have one co and I actually did a LinkedIn post about this. I didn't put his name, but I have one co co-worker that I write a certain way, and he doesn't respond to my emails in an appropriate fashion. Like, he's not getting me the responses I want. So I asked C-Pilot, like, "What is the deal here?" You know, and it came back and said, "Well, when you talk to this person, you should write your emails like this." And I was like, "Okay, let me try." And so now every time I go to write him an email, I go to that prompt. I'm like, "I need to send Michael an email about this." And it says, "Do it this way." And it is amazing. It's not how I would generally write, but it's how he needs to hear it for me to get the response I need instead of having to go back and forth with him multiple times. And then, you know, a few curse words in between, you know, I get I get it from him the first time now. So yes, I think maybe we are, but at the same time, no, I think my I think my personality is still there and what I'm sending out because I do edit things, you know. At the beginning, I, one of my big things of all through life has been, you know, you know, just the fact I was an Air Force drag officer, so I'm like, "No, no, no, we're going to go. I need the answer now. It's what it is." And so, um, co-pilot seems to think I need to be like, "How are you doing? How, how are you doing? I hope all is going well." Like, I delete that immediately, you know. And I'm like, you know, one of my things was, I think I'm going to need this new prompt to be like, "Okay, we don't do that. We're just going to get straight into it, you know." And so, but it's funny because, you know, I used to have a friend at my last job who, if I was a really important email, he's like, "Send it to me so we make sure that you don't piss people off." And so, um, co-pilot is now making sure I don't piss people off. Yeah. I use it a lot for that too.
Time for one more right here. So for, say, a 400 law firm looking to adopt a platform, would you recommend having a limited number of licenses and make it where they earn it or the attorneys who really want to have it, you know, they go through the process, they show that they're there, and then sort of manage that where you're not using it, you can give it to somebody else that's in line, or is that something that that type of competition?
I could see how that could be useful. I I do think with with when we're looking at third party ones, I for some reason for the one that we were sampling, I really thought it went out to everybody, but later, um, I found out it just actually went out to the super users. They looked at that daily usage group, and that group became part of it. It just so happened my whole team was on it because I had gotten them all motivated and they were using it. So that's why I thought everybody had gotten it, but not everybody did. And so I think it would be useful to see who are your super users. Start with that group, have them test it out, and then they can evangelize it. Especially if you don't want to like, you know, drop, you know, a huge chunk of money at one time and then not, if this number is accurate, not have, you know, 50% of the people using it. Yeah, I would I would find those super users, get them engaged and motivated, and then over time drive adoption.
And Carrie, do we have carrots or sticks or both?
Um, I always start with a carrot. Like, it's going to be great. But then we have done that. Like our research team is doing it now with like co-counsel, like you, like we only have so many licenses. We're going to give them out. You get it for 90 days. If you don't use it, we're taking it away, right? It's administrative, but like keeps the cost down and it keeps the adoption up, right? The adoption rate looks great because the people in there actually want it, right? Because some people you're never going to change, right? And some of that is you need to accept it, right? They're just stuck in their ways. Like they still have their paper files and their, you know, their diary on a piece of paper. Like, you know, sometimes it's okay to accept it. Like, I'm not going to change him, right? He's he's going to do his thing or she's going to do her thing. And sometimes you let go, and sometimes that's freeing too. It's like, I'm never going to get to 90%. Right. Sometimes you got to let go.
That is great. Um, all right, and everybody try Lata Leto. It might improve adoption because it already has all those skills in there. Um, but yes, there's room for, you know, a lot of wonderful AI tools. Um, we're going to wrap up. Uh, just also want to say that part of encouraging adoption is this human aspect of people at the vendors supplying some of these tools that you're adopting. And, uh, I can speak for us at Lata. We have experience lounge downstairs, which is like the genius bar. Anybody having any issues, come down to that on the booth. We have, um, LEAR labs. We will come to you. We'll come to your location. Any, um, any of the LERA tools that you're using, if you, uh, want support with adoption, you know, it's really about that partnership. So, you know, a little little bit of plug for that. It's important to just push on your vendors. We have resources that help support this internally. Um, all of the other, you know, our peer vendors that are here as well, probably have that also. But just, you know, if you're having issues, come talk to us. We're we're here to help. We're here to support that. Um, and with that, thank you all for coming and for staying for the session. Hopefully, you got something out of it. And thank you, panelists. Amazing work.