Transcript for "Data and Dollars: 2025’s CLM Survey Trends You Can't Ignore": Great. Thank you so very much. Appreciate it. Welcome, everybody. Very excited to have you here. And welcome to the State of CLM webinar where we're we really try strive to understand the mindset around CLM, you know, who's using it, what they're doing with it, you know, maybe who's not using it, why they're not using it. And, of course, we're gonna cover AI because that is always always a subject of topic that we wanna discuss. Jennifer's already kinda gone through who we are. Laura, you wanna go first and just tell us a little bit about yourself? Yeah. Super happy to be here. Thank you everyone for attending and for CCBJ for putting this on. I apologize. I'm a little out of my normal element. I'm in a hotel room, so if there's technical issues, bear with me. I'm traveling for work. But I am the general counsel and corporate secretary of Agiloft, and also just a person who really loves and believes in legal technology. And so, with my empirical background, because I also used to be an empirical legal scholar at UCLA, doing things like this is, like, right up my alley of interest. Interest. So I'm excited to geek out with you all. Great. Danielle. Thank you. Excuse me. Danielle Hogland, senior director of Global Alliances. I came to Agiloft, by way of a, long and windy road starting as an antitrust and complex commercial litigator. And I've been at Agiloft for about four and a half years now, so consider myself a bit of a veteran, at least an Agiloft veteran at this point. And I'm really looking forward to the session. Thank you to CCBJ for conducting the surveys that survey that we're going to be talking about today. Thanks to the respondents for taking the time to respond to the questions and providing us valuable insights that we can all use to shape our collective CLM journey. And thanks to Allison for pulling out altogether. And finally, Laura, I did not know that about you, that you were a, what what was it? A scholar? Scholar. Yeah. Empirical legal scholar. I I feel like this has been the week of me revealing things in my past that surprised people. Like, I told people a couple days ago, I used to do ventriloquism, and that really blew their minds. And so, we're just gonna let how you hang out on this webinar, I guess. Yeah. We should we should have incorporated those those two things. I'm really glad we did. That would Yeah. I will That would be awesome. So and and I'm Allison. There we go. There we go. I'm Allison, product marketing. Yes. Thank you so much CCB Day for for doing this with us and for gathering all this great data, so that we can compile it and and and present it to you. Been in marketing forever, legal tech for almost as long, and, really enjoy my time here at Agiloft. I've been here, gosh, almost about a year and a half, a little over that. So but, anyway, let's just let's just jump into this, going right into the right into the data. But let's talk about the respondents, you know, who who kinda took the survey and gave us their information. It was really a broad mix of company sizes. You know, it's pretty evenly split from, fewer than 500 full time employees to more than 10,000. So we've really got a good a good subsection there. Also good for job titles, from individual contributors all the way to the c suite, which is nice to see. Mainly, there were influencers, that responded at 39%. Some some of them were decision makers at 23% and users, 25%, you can see there. So, again, pretty well rounded, response pool to our survey. Danielle, do you have any do you have any comments on this? Yeah. So this year, the respondents definitely skewed towards legal, which which makes sense given the audience. But I wanted to look at the number of VP and C suite executives responding, and that's a combined 38, which is a big chunk. Now they may not necessarily work with contracts or CLM tools on the daily, but they are daily consumers of contract data, which is or at least should be captured and dispersed throughout the organization. And I do think that this reflects the growing acknowledgment that CLM has matured beyond legal tech. It is firmly enterprise tech now and increasingly become becoming viewed as a core system. And this is also great news for a lot of departments, many of whom own the contracting function within their organizations. Law departments have long been viewed as cost centers, but more and more organizations are recognizing that contracts really are the glue that holds together all commercial activity, and Savulaw departments, championing championing CLM are leading the way and winning awards on corporate innovation initiatives. So I was really pleased to see the high number of VP and c suite exec execs responding to the survey because they really do care about this. Yeah. Absolutely. I mean, you're right. It's like the no business starts or actually can continue without contracts and contract data. I mean, how else how else does anything else get done, right, within the within the business? So good point. Very good point. Just really quickly, can I just say one quick thing about the last one? And this is just a little side contact, comments, I guess, but it's kind of, getting to a little bit of the identity of the legal department, which I think is a fascinating discussion when we're talking about the future of the legal department, which is really what legal technology is leading us to. So in that last section there about business function, we've got legal operations and attorneys as two separate categories. And I know that there are a lot of legal operations professionals that are non attorneys, and then there are a lot of legal operations professionals that are attorneys. And so, just a question I have is, how are people identifying themselves? And, like, what does that mean? Are people who are attorneys but in legal operations function seeing themselves still as more of an attorney, or are they seeing themselves as a legal operator? But I do think this is interesting enough to note just because I think as the legal team dynamics and functions change over time, that identity part will become a big thing that we should be considering as we're we're asking these questions so we can better understand, how legal departments are organizing themselves. Absolutely. Very good point. And that's another thing is that as we do these surveys, you know, this is our second year, we learn it's like, you know what? We need to we need to finesse this question in order to better understand what, you know, what we're asking. So that's I'm going to make a note. I guess that is a very good point. We'll have an we'll have a vote. You know? It's like, how do you identify, you know, as as legal ops or attorney or both? Because it could be that you're like, well, I'm I'm both of these things. So very interesting. Absolutely. So Okay. Yo. Let's go back. Keep going. Oh, I just wanted to riff off of something that Laura had Yeah. Said about, you know, legal operations professionals and some of them are attorneys, some of them are non attorneys, and we can set aside non attorney. I we still haven't figured out, like, the right word for that. But it the the legal operations function is interesting because it draws people from a variety of backgrounds, from legal backgrounds, from operations, and more business backgrounds. And that lends diversity to the law department that I think is helping law departments kind of get more business forward because they're really drawing from more diverse organizations or backgrounds, and skill sets. You're right. And that's probably helping to drive this whole data first thing of the the the contract data doesn't need to stay locked in a in a drawer somewhere in the legal department. It needs to be dispersed throughout the business. And so these business people people are coming in as legal ops and saying, no. This stuff is important. Get it out to everybody. Right. Great. Okay. I'm not gonna move off this slide. Are we done yet? We're I'm done. Moment. Okay. No. This is great conversation. I wanna keep it going. I just didn't wanna go back and forth again. Yeah. This is awesome. Okay. So let's actually get into what we found with the survey. How is contracting handled? So half our respondents use oh, actually, over half use CLM for their contracts. This is excellent news. Right? Of course, the other half of that story is almost half our respondents rely on spreadsheets, manual processes, you know, for their contracting. So, you know, when we look at the size of the companies that responded, remember, only 25% of them had less than 500 FTEs. So that's, you know, just a quarter. Right? So that means there are companies with more than 500 employees out there that rely 100 on human accuracy for their contract tracking, their obligation management. I mean, isn't that pretty frightening? I I don't know if frightening is the right word, but it was Good. Surprising. More in light of the and I know I'm getting a little head to the to the pie chart to the right, but more in light of the response that, you know, really, just about half of them either, are maybe going to or will be implementing a CLM in the future, and 40% are just saying no. And so I I love to try to think about, like, what does that actually mean? Does it mean that these manual and spreadsheet things are working? Well, having come from a large company, I can tell you, it doesn't work very well. I mean and maybe maybe if smaller companies or if there's a very streamlined process or or they're using, like, non CLM tools in a CLM like way, perhaps that would work. Right? Because then maybe that's not being identified as CLM, but really it's, like, covering that that core functionality that they're looking for. But the problem with spreadsheets, right, and, manual processes is is human glue. That's what we always called it at one of my old jobs. And there was, like, the person who knew the spreadsheet. And, you know, on one hand, I think they felt very indispensable. On the other hand, there was a lot of fear around, like, what happens if the person who truly understands this spreadsheet or this one off process leaves. And so I think when we're looking at responses like this, maybe we're not doing a good enough job of explaining to people, like, what part of the value of CLM is, which is you're taking, human processes, human knowledge, and you're implementing it within a system so that you're less reliant on individuals and you're more reliant on something that is more scalable and you can basically knowledge transfer more easily between individuals. But then the the other question made me think, if they're not thinking about getting one in the future and already don't, or or they're, like, on the fence, is part of this because of the rapid development of technology. And so I I think that legal professionals might have this, perfectionism. I mean, there there's, like, a lot of research out there about perfectionism in the legal function. And I think, what we see is a lot of really fascinating new technology and advances, particularly in AI, agentic AI, generative AI. But there there's some things about it that aren't quite right yet. So I wonder if part of this is legal departments are are really hesitating to invest in technology and tell it's the right technology. And I think there's some risk to that for legal departments if that's if that's the cause of this response, because the even if the technology isn't 100% where you want the end state to be, by adopting now for your use case and building it over time, it forces you to take a look at your own processes, to take a look at your own data, which does, I think, help legal departments. And on top of that, you're building out that muscle and that skill of legal technology implementation. So as the technology gets better and better, you're going to be in a better position to take advantage of that leap in technology faster. So those are just my overall thoughts. I mean, that was a lot to digest. I wrote No. And and you know what? With the hotel coffee. My mind boiled it down too, and y'all are just gonna think I'm crazy. But, I mean, if everybody waited, to have a baby, if they when they were ready to have a baby, nobody'd have babies. Right? Allison, that is very succinct and very, that's that's spot on. I just boiled it down. That's that's what product marketing does. We boil it down. That's perfect. Very, very neatly stated. I don't know, Danielle. What do you think? What did you feel when you saw this? Because this was really, like, it was fascinating to me, this particular Yeah. Contest. So as a mom of four, I I did not have that problem. But, yeah, I I was I was surprised just like you, Laura, and it got me to thinking what, what is considered a CLM? You know, because we at a CLM company have an idea of what contract life cycle management is, but then there's this huge spectrum is, you know, is it just a repository? Is it repository plus drafting, and tracking? Is it, you know, and then all the way across the spectrum to obligation management and really leveraging contract AI to drive business or contract AI, CLM to drive business initiatives and strategy. So I wonder if there was some interpretation in the question, that folks were thinking, you know, what is the CLM? Maybe we don't have the CLM, and, you know, I'm gonna consider everything that I house in, SharePoint or Teams as as my CLM strategy. So, I I agree with you. It it this one definitely puzzled me a little bit, especially the 40%, like you said, that aren't planning to implement, CLM in the future. Yeah. Interesting. Very interesting thoughts. Yeah. Okay. Alright. And this kinda kinda leans into it. You know, is it planned and budgeted for? So the ones that said no. Nope. No plans to implement. So let me look at my notes here. Mainly companies with fewer than 500 FTs, but there were still 59% of respondents that had 500 to a 10,000 employees that are, yeah, relying on the the human accuracy, which is scary. Danielle, you had some interesting thoughts when we were writing up our report on this. You had and and, by the way, this is just a little these are little sneak peeks for a good great report that we're gonna have out. But you had some thoughts on this, with I don't know if you say v u c a or if you, like, pronounce the acronym or not. No. That's a great question. So so I recently came across this term, VUCA, v u c a, volatility, uncertainty, complexity, and ambiguity. And it like, when I say recently, like, when the within the last few weeks, and those four words certainly describe the current state of business and geopolitical affairs around the globe right now. And one of the best mitigating forces against VUCA is ensuring processes are in place and data is organized and managed in a way that allows companies to respond quickly to unexpected transitions. Right? And that's exactly what CLM is designed for. So, I think on the slides, there it it shows that those who are interested in buying CLM, like, they want it fast within, you know, the next few months. Yeah. So with with VUCA reaching peak levels, CLM not only makes contract management more efficient, but also allows companies to respond proactively by minimizing contractual risks, ensuring compliance, maintaining operational continuity, which is huge, and ultimately leading to faster recovery times and a more resilient business strategy during and after resilient business strategy during and after disruptions. So it's not a surprise that those who want it, like, they want it now. They want it fast. Yeah. Yeah. The 43%, seven months to a year, and and nobody was beyond three years. So Mhmm. This is interesting. That is such a great point. And when was this, Allison, when exactly was this survey conducted? Do you have that in recent January. It was, Okay. Yeah. We got it, Feb yeah. February data. January break. Because I was also just thinking, like, you know, timing is everything on when you pose these questions. Right? Mhmm. And I know that one of the big lessons from the pandemic, was on supply chain. And so a lot of companies that were very heavy on supply chain and manufacturing. Right? They, were looking around for contract life cycle management solutions because they were like, oh my gosh, like this event happened. And all of a sudden, I need to do some work so that I can move faster the next time something that's incredibly disruptive occurs. And so I do think, you know, we've all learned that lesson personally too, like who stocked up on toilet paper before COVID? I mean, now I always have, I can't even tell you the amount of toilet paper I store in my house now because of that, right? So I think our environment does change what we prioritize and how we action. And so I'd love to actually, survey these same people today because I do think we've had two solid months of a lot of, kind of chaotic change. And and I wonder if some of these actually would be changing in relation to that. And I do think though that sometimes we wait for investment until we have something that's pressing enough for us to do it. And that's not necessarily a bad strategy. Right? Like, I'm not saying that there isn't some sense in that, but I do think this might be a time where we see people going out there and looking for solutions that can help them, deal with the with VUCA. VUCA. That that's what that's how I'm saying it. I I love it. I think it's it's great. It's a easy way to kinda put that together. But I do think, I think it's it is a a possibility that we see an uptick and a change in direction given, the instability. Yeah. Absolutely. Yeah. A lot of things changing and, yeah, anything with stability is probably a little lifesaver for anybody at this point. Mhmm. So let's talk about roadblocks. You know, there's some people again that they're like, nope. We're not doing it. It's like, what? Well well, let's let's try to poke around this and ask why. We did have a very interesting one from last year. I didn't have the the statistic up here, but from last year, the number that went down the most was vendors to choose from. There was that was as a robot. There's just too many it's too much going confusion in the marketplace, and that went down from 39% last year to as a reason to 4% this year. I thought that was pretty interesting. Mhmm. So, Danielle, you had some thoughts on that, I think? I was just gonna say, can I jump in here? Absolutely. Jump away. Yeah. That that jumped out at me too, Allison, and it got me to thinking, why? So, you know, we haven't really seen significant consolidation in the market. So one of the conclusions we can draw from this is that there are a few CLM vendors that are cutting through the noise. But, again, why? And one possible answer is that the market is becoming more stratified with point solutions on one end and enterprise contract management solutions on the other end. And I think that consumers of CLM are getting smarter and recognizing the potential financial impact an enterprise contract management solution can have on their core business. So there are only a handful of solutions that can achieve that at an enterprise level. So I think it narrows down the number of options. But, you know, these are these are my musings about, the why of from a, you know, 39% to a 4%. Laura, I'd love to get your take on it as well. Gosh. And as a as a statistician, right, in my background, I'm like, there's so many reasons this could be. Right? It could be how we sampled. Like, there could be any number of reasons. But I I get it. I do think, there was a definite kind of opening of the gates on CLM, and maybe there is a little bit of kind of shaking out on the top contenders, especially for larger organizations that have more kind of complex data needs. They're really looking for an end to end solution so that they don't have to, have the complexity of a solution stack that just continues to grow and grow and grow. Right? Because that's that's where other enterprise solutions have been successful is is kind of limiting that that creep into, too many solutions. But I don't have a good answer for this really because I'm not even sure we're at that point yet in the wave of CLM. There's so many, and I think we saw it from the last one. Like, we're still, we're still changing minds and getting people smart about CLM. So really hard to know what to make of this. I don't want to also ignore the big orange elephant in the room, which is budget. Budget. Yeah. And this goes back to my surprise about the number of no's on do you plan on implementing CLM ever? Because I'm like, ever? Okay. And and, I think something that, like, it made me start to think about is okay. So maybe people are saying ever because they're they're thinking about the budget environment that they're in now or the needs of the company now, and they're kinda thinking, like, yeah. We just don't need this. So they're not even, like, saying an actual never. It's more just a, like, now we're not really considering this. Right? And so if I look at that, I think one thing that all legal departments and departments that are really heavy in contracts can be doing, whether they intend to implement CLM or not in the near future or whether they're just considering it, is do the prework. Because a lot of the prework is very budget friendly. Right? So Yeah. I think there's a lot of great materials out there on CLM readiness. We have some I know other vendors have some. I know that, like, a lot of people who do implementation have these resources. Clock has great resources. CCVJ, I'm sure, has I mean, like, the resources are out there. And start to look at that and think about, like, okay. Maybe I don't have budget, but what readiness steps can I take so that, I'm ready for when I am going to commit to legal technology, whether I wanna call it CLM or not? And then also those are the same things that are gonna help your legal department get better at the manual processes. Right? And so even if you're not doing that investment for CLM, you're still doing that investment for the benefit of your department. Absolutely. Yeah. Yes. And and I I talk to customers quite a bit doing, you know, our case studies and things. And that is a resounding theme is that do the prework because once and because it will uncover things that you didn't even know. It's like, well, that's a waste of time, and why are three people doing this instead of one? And way before you get to the technology, they can it really is do the prework, and that just it makes the technology piece just go that much sooner once you're ready. So yeah. Great point. Yeah. It's it's actually played out in real life. Another thing is doing that prework can help you, scope your legal technology implementation project to be more budget friendly. Yeah. So by doing the prework, you may actually be able to cut down implementation costs and be able to, like, figure out the low hanging fruit that is gonna be the most valuable for the technology. And so you may be able to make a better budget case for the technological transformation you so desire to make. Exactly. Baby steps. Because there are there are two different ways to do it. Right? There's baby steps. It's like, let's tackle this one type of contract. I've seen that. To Yeah. Okay. We're going all in, all my chips, everything in. So, yeah, to do the baby steps steps is absolutely viable and, like you said, budget friendly. So yeah. Seeing that one Allison, I'm loving this baby theme that we've got after that. Hey. Here's what's funny. I don't have kids. Now I got a dog. I got a sleeping dog. I don't even have kids. For a baby. Yeah. No. I just keep the stomach. The baby and aunt are great. Alright. Yeah. I think this seems to work. Okay. So let's talk about the fortunate ones that do have CLM. Right? So, a lot of different capabilities within a CLM. You know, we can all agree on that. You know? And it benefits not just contracts as we've talked about, but the rest of the business. And I don't think it's unusual that we see mainly some of the basic functionalities and ones that are are being used most here. Yeah. Yeah. And those are usually the things that you're gonna be building everything else off of. Right? And so most, I've seen two main approaches to CLM implementation. One is repository first. Repository first. One is kind of like contract workflow first. Both have benefits and downsides. So it's not surprising to me to see parity on those two because they're amazing starting points for most organizations. You know, I I I think, like, what's really interesting is, like, these steps down, and those steps are pretty much equated to complexity. Right? To, like, what maturity level you're on. It's almost like they're almost even. Right? It's like this much of a step down, this much of a step down, this much of a step down. So this looks right to me. And and, frankly, I think, like, you do have to build a a strong foundation before you can build out some of the, higher, complexity and yet potential to have, like, high impact type of things like data analytics and risks risk, management. Mhmm. So, you know, I I wish I wish as we were preparing for this, I had thought about this sooner, but, we have a, contracts maturity model that is, like, in the shape of a pyramid that we often look to. I mean, this follows right alongside you know, that follows the contract maturity model to a t. So maybe next year, if we get the same results, we can put our contract maturity model right next to it and see, like, see? These things are the same. It doesn't make us feel, like, prescient, like, we really nailed it with the our brains. Yeah. Exactly. Is this all makes sense? So absolutely. So, yeah, you start, you know, because there's a lot of people that are like, well, we have a you know, we we have our repository. We're very excited about that. It's like, but you're and and you do. You have to do you have to mature into the functionality, but there's so much more that it could be used. Sometimes and they even they're already paying for it, a lot of folks. Right? They're already paying for the functionality, and you just gotta take those baby steps, those small steps to just start using start using what's gonna, make most sense for your organization of where you're gonna get the most bang for the buck, you know, the best benefit by by starting maybe introduce AI or, you know, the workflow or automate their con or, templates or, you know, whatever it might be. So interesting. But I also wanna celebrate the people who have done repository track contracts because those that's a hard first step. And there's a lot of prework that goes into it. So if you're if you're at track contracts or repository only, still good for you. Because that is a that's a big leap to make. And, I think the rest of your contract life cycle management journey into maturity will become a lot easier because, again, you started with the foundation. Affirmation. We like those. Alright. Positivity. Positivity. Okay. So, let's see. For our positive out positive outflow. No one for always saying yes. For it. Yeah. Alright. So the ones the things that you wish you were wish you were doing with your CLM but are not. So let's see. Let's see. So what are your thoughts about this? I'm not even gonna get get give you any preamble. Yeah. Danielle, go for it. I I know you and I both have thoughts on this one. Yes. I I don't I don't know, I don't know if it made it into the slide, but I think, there was a huge decrease from last year to this year, and the people that reported being held back by CLM functional functionality, held back, on the things they wanted to do. It went from, like, 61% last year said that they were held back, based on, you know, CLM functionality that wasn't available to them. And this year, it's 30%. And I found that really interesting. Laura, I know you're gonna find it even way more interesting knowing you're I again, I'm learning so much about you. You are a statistician as well. I hope you do. I know. So CLM tools are definitely adding more robust functionality, and, and and I know that we're gonna be talking about AI in some of the upcoming slides, but I do wanna make the comment here that I think that AI and particularly GenAI may be filling in some reported, lack of CLM functionality went to, like, 61% to 30% this year. So GenAI is it's not necessarily adding feature functions tool to a CLM tool itself, but it's creating shortcuts. You know, we all know that the use of GenAI in the workplace and at home has absolutely exploded in the past year or two years. I've used Chad GPT to create trip itineraries. If anybody is going to the Western Canadian Rockies, I have a killer trip trip itinerary for you that was generated from Chad GPT. My daughter uses it to create practice plans for the tier team that she coaches. And like I said, I use it on the daily at work. And and GenAI prompts within c l CLM tools, and I'm gonna I'm gonna plug Agiloft for a minute. Agiloft has a prompt lab within the tool. It allows users to build their own AI prompts to do all sorts of things, like automatically draft contract descriptions and summaries and send that information to interested parties, extract applications, develop risk profiles, draft and rise contracts. So all of these things are kind of short cuts. They're, like, all available within the tools, but Jennifer, I just allows you to do it a little bit quicker. The next frontier, and, Laura, you touched on this, a minute ago, is a agentic AI systems, which are designed to make decisions and take actions independently versus GenAI, which is content creation. And I have a feeling that when we're back here talking about the survey next year, we're gonna be talking a lot about agentic AI and where it's taking us. I hope so. I really hope so. Yeah. And I think I share what you just said, which is a lot of the AI functionality that we are seeing right now, is aimed at kind of being behind the scenes, improving your ability to get these key things done in your CLM. The thing that is really interesting to me though on this, in addition to, thinking about the lens of AI, is that 48% on data analysis and insights. Because if you look at the last slide or in the pyramid, right, data analytics and insights is at the top of the pyramid Mhmm. And is also one of the ones that is the lowest on whether you're actually doing it. So that does explain the 48% because, like, only, you know, but on the other hand, I do think people want to get to the future. They wanna get there quickly. And so I think CLM solutions that can help, and and not just CLM solutions because it's not just the solution, it's the team that you have helping you with your CLM implementation. I think there is an opportunity to help people get to that end state faster. And it can be a very collaborative approach between the CLM provider and the customer to say, like, hey. If this is your true North Star for what you wanna be doing with your CLM, how do we expedite getting you there? Recognizing that there are some steps you're gonna have to take, in between, but maybe those steps become easier with AI. Right? And so then that helps accelerate people to the end state that they want. But the other thing I found so interesting on this is the discrepancy between data analysis and insights and shared data between departments. And I think this is a hidden miss for departments that are focusing on analytics before sharing data. Because the analytics become better and the insights more profound the more data you're sharing across the organization. And so, like, I want to I want like, if I could beat one drum right now, it's like, hey, everybody. Start sharing data because when you get to that data analysis and insights, that's when you're gonna be just benefiting from this juicy, big enterprise wide, data pool, that you're contributing to and benefiting from, and that's when you're gonna get the best information. Yeah. Absolutely. Contract data as as the one single source of truth. Everybody you know, forget data silos. Everybody pulls it and does it. It's like it sits in one place. Everybody's singing from the same hymn book. I got another analogy. So everybody is on this Where are we from babies? No more babies. Oh, no no more babies. Now we're gonna talk. Now we're gonna talk for a little bit. No. But, anyway, everybody's on the same sheet of music. How about that? Yes. I love here we go. So neutral. Yeah. Same sheet of music. Everybody's knows the words. So the but it's it is. It's it's it's centralized. It's it's vital to the rest of the business, and the rest of the business can then analyze all they need to. Right? So you're love it. Yeah. Well, it is from the transformation message that we also deliver, which is basically a legal department of the future is more transparent. And so I think, again, we may see that number go up as people are really leaning into information. Excellent. Excellent. Very, very wonderful points. Thank you, Beth. Alright. Now we've been talking about AI, so let's actually make it all official. So this is a very nice surprise because, if the AI capability is built into the CLM, the over two thirds are using it. Yay. This is great. I love this. Because it is. It's so pervasive in our life. You know? It's everywhere. We you know, you can ask Siri and you can, you know, you know, what was I was just writing something. I had, like, three great examples now. I can't remember any of them. But, oh, when you're on, Amazon and you're trying to buy something, it's like, also, this might go well well with it. It's like, yeah. How did you know what I was doing? So dangerous. Oh, it's so bad. It is. It is. Especially once you pay off your credit card bill, then you're like, oh, yeah. I got room. So but, anyway, it looks like AI really is moving into the mainstream for business, and, you know, that's that's wonderful. Wonderful. Okay. Should we go on to the next one? Because it gives a little more meat. So we'll talk about how AI is being used. Okay. Sure. Okay. So lot of different capabilities. Here we are again, but these are AI specific capabilities inside of a CLM. Right? Mhmm. So what kind of kind they're using, and how would they want to use it? What do you think? I have got to say when I saw that clause library was the number one, I I had to take a step back and reflect because I I would have thought it would be the natural language searching or redlining or data extraction would be the type. And it's clause library. And so I had to ask myself to go down the thought journey of why that one is the, most used AI capability. And I think there's, you know, I've like, now that I've sat with it, I'm not as like, what? Caught you my pearls. I think it makes sense sense because one of the things that every legal department struggles with is consistency between contracts and getting visibility into where they are varying from their consistent practices. And so clause library is something that I think, AI has made so much easier. So it does not surprise me that, companies now that I've thought about it, it doesn't surprise me that this is an early use case. Because before, this was so manual and it didn't with AI, it doesn't have to be, and it's a good way of of helping enable and empower people who are owning contracts to use the right language, the right up to date, things, and to kinda build out that knowledge. So I like this now that I sat with it. At first, I didn't. Oh, well, I think it's because we do now. I think I responded for a bunch of fancy people. Let's be honest. So, you know, Closet Library, good for them. Yeah. Well, so so building off, building on that, and and I love how you put that, Laura, that, contracts are getting more consistent, you know, from one contract to the next and putting on my litigator hat for a second, man, that is welcome welcome news. So, you know, we all know that AI in contracting is becoming ubiquitous and contracts are getting better for it and then, you know, things like clause libraries are one of the reasons for that. And when you add in applications like, like screens, for example, which is going to be incorporated into Agiloft soon, that shows users how their contracts and individual clauses stand up to community standards, things like that substantially reduces the risk of litigation based on fake ambiguous or poorly defined terms. And like I said in my intro, you know, I was a I was a commercial litigator, so I litigated so many horrible contracts. And I would work with I was in a law firm, and I would work with our, our corporate, team. And I would always suggest that a litigator lay eyes on a critical MSA or a supply agreement to look for anything that could cause a problem later if things went south. And the tools today allow that type of review at scale on every agreement and not just that the company deals, And that is just a a game changer of an improvement. Yeah. Wonderful. Love the clause library. That's what we're saying. Yeah. Love it. Yeah. It does make things easier. That's for sure. Do you have something else on there? This is a yeah. I'm like needle in a haystack here. Why do I want to use it? Teaching it the business language. I love that. I love that idea of taking a collaborative approach using AI and understanding the value of basically training it and making sure it's adept in your specific business language. Right? So I don't know. I just to me, that makes me smile as a person who's excited for this technological leap to see that that showed up on this list at that percentage. Yeah. Pretty cool. Absolutely. Good AI stuff. Alright. Okay. So, well, if there's some people out there not using AI, understandable. Absolutely. But why why aren't they why aren't they using it? It you know, either you have it or you don't wanna use it, and a lot of it, is because of the cost, which is interesting. And the fact that some people don't don't actually have it in in their CLM, which is a little surprising too. But maybe it doesn't give me the definition of a CLM. Yeah. The definition of CLM. And I think people there's a lot of home built solutions still out there too. Oh, yeah. Yeah. Yeah. And I wonder if maybe that's accounting for part of this answer as well. Very possible. Yeah. It's possible. I was really curious about other, because it's not insignificant. Right? It's like right in the middle. So I was curious what that what like, what some of the other responses were. I'm really happy to see that, that, you know, AI is too hard. That's down at 4%. Really happy to see that don't trust it is at 8%. I think that's a vast improvement in a relatively short period of time. Not too long ago, companies large and small were really kind of foregoing AI, particularly Gen AI for security concerns, and I think we're past that now as the survey would suggest. So that that is welcome news. Well, I think it's also that, you know, oh, go ahead. Please go. Oh, I was just gonna say the don't trust at the 8%. I also felt very optimistic about that. But I also just wanted to remind ourselves, I believe most of the respondents are not necessarily just users. Mhmm. Yeah. And so this may also be a little skewed towards those who are most likely to be comfortable with expanding on the technology and, like, taking it to the edge. So I'd love to see a survey compare this number to users. I'm just curious about that because if users are the ones that are having a lack of trust in the AI technology, there might be a disconnect at the influencer decision level and the user level. And I I would expect that friction to cause some issues with, adoption. Yeah. That's that's interesting. And, also, you know, we have to always remember that, you know, human in the loop. Right? You you have to it's not just taking AI at its at its face value and running with it. It is great. You you, lessened my burden of this administrative work, and now I can now I have something that's almost there, and I can, you know, review it for accuracy or whatever it might be. So yeah. So it's you know, the the trust is is getting there, and I think people understand that, yes, I can trust it to a degree, and and it takes me very far down the road, further down the road than I would have been without it. Right? Yeah. So great. Alright. Integrations. This is always interesting. The we've talked about, you know, data and sharing it throughout the organization. And now here we've got, you know, how many applications are you integrated with and, you know, and who are they integrated with? So this is very happy news because it does just the data first, the central single source of truth seems to really be taking hold, which is exciting. The first one bums me out, though. If I did have to clutch my pearls at any of these, it would be that first one where there's Oh, you're looking at it as half half empty, not half empty. Integrations? The no integrations are one or two integrations because because I I do think, and, again, this is my personal opinion. The biggest value for the enterprise is when your legal function is fully hooked into the rest of the enterprise, and one of the ways that you do that is for integrations. And so this to me is a missed opportunity. And I kinda wanna talk to the no integration and figure out, like, oh, are you just lower on the CLM maturity, like, scale? And so then it makes sense. Then I'm like, oh, cool. There's so much good stuff for you to do when you start moving up that pyramid. Right? But I also really wanna talk to the people that are in that 4% on more than 10 and hear from them, like, what is the benefit been to you? What are the hard points of doing it for you? And are those the 4% that are also hitting the road or hitting the road? Hit the ground running? Hit hit the road, you 4%. No. Hitting the ground running, mixing up my mind, of course. Get the ground running on things like data analytics. Because it'd be interesting to get in to compare that. Right? Like, are the data analytics people also the people that have all the integrations, or are they really focused on legal analytics only or contract analytics only? Anyhow, but, yeah, I do think, can't tell whether this is again maturity or this is just, like, using CLM strictly for one function, but I'd love to hear from that 4%. Well, I'll hunt them down for you. Don't worry. Please do it. Thank you. I'm kidding. I don't know who you are. It was for It was. It was anonymous. I don't know. Yes. It was anonymous. Well, if you're on and you responded, email me. There you go. There you go. I, a %, agree with Laura. I think that, integrations are the path to what I think is the highest and best use case of contract data, and that is to inform business strategy. So, you know, using AI to analyze contracts across sectors and regions, to help spot patterns, about emerging market opportunities, shifts in comfort customer demand, new products to explore, things like that. That is the pinnacle of how you should how we want companies to be using their contract data to really not just, you know, house their, you know, not using a CLM just to house their contracts, but using the data from their contracts to expand and grow their business. That's that's really fun stuff right there. And and it's competitive advantage too because you can tell that there's a lot of companies out there not doing it. So imagine the competitive advantage if you're the one in your industry that does do it. So Yep. That's fine. Alright. So now this is something we asked everybody whether they had a CLM or didn't have a CLM. So, you know, does importance correlate with usage? A lot of interesting stuff here. Data analysis and insights, things people wish they were using their c l CLM for rated not as extremely important, which I thought was interesting. So, of course, repository track contracts, very, very high. So thoughts? Yeah. So if if I'm reading the data correctly, I think about 70% of the respondents said that each use case was either important, very important, or extremely important. Right? Am I am I reading that right? I think I Yeah. Yeah. I think so. Yeah. Because the colors. Yeah. Yeah. Yeah. Yeah. And again, you know, we were talking before about the contracts maturity model. I think that tracks. Right? So organizations are building from the ground up starting with the solid foundation of repository drafting and tracking and then building up to more sophisticated AI driven use cases. So, so I I was not surprised at at this data at all. I I'm gonna say the silliest thing. The only thing that surprises me is the not important at at all for things like repository or credit access. And and There were there were people. And no no shame. I I just like, that does, surprise me. And so I'm trying to now, again, expand my mind to think of the kind of respondent who maybe not need a repository. And maybe it's and and, again, this is where I'm like, maybe it's a company that their terms and conditions are online. And so they don't need a repository necessarily. They more just need a tracking mechanism or an audit mechanism. So, again, like, anytime I see something like this, I I just have to, like, give myself a moment to process things. I'm like, what? You know, almost 10% only find repositories? Like yeah. Yeah. But I think it's Yeah. Pete, they're they're out there. They're out there. It it happens. It's okay. Yeah. And there might be legitimate use cases. And so I'm like, every business is different. And a a great legal department, they know their business, and they know what the business needs or and in some cases, does not need. Yeah. Yeah. It happens. Absolutely. Wise. They're out there. Very wise. I Okay. So let's talk about we've got some key takeaways. And it's funny because I'm sitting here thinking about these takeaways. I was like, you know, I after our conversation, I might have probably altered these, but these we did this beforehand. Right? So we we work with what we got here, girl. Alright. So data analysis and insight, you know, it's a least used feature. You're right. Because it requires this data centric mindset that just seems to be starting to take shape. I think we've talked about this a bit, but thoughts more thoughts, I should say. Yeah. I I think this yeah. It is. I think this is a a great takeaway and, you know, what we're just talking about about with, integrations being so important, you know, you really need the data flow data to flow across, business units and sectors and throughout the organization to get the highest and greatest value out of your contract data. So yeah. Yeah. Absolutely. And, of course, there we go to AI and our maturity model, you know, and more mature, uses will eventually come. And I think, eventually, you know, business strategy will be impacted by your AI and your CLM? How how do you think that would happen? Yeah. Well, I think this this goes back to my, are we waiting to implement technology until it's right or perfect. Right? And, I would say that if you're waiting because this very specific thing that you wanna do isn't quite there yet, that's okay. But maybe take a step back and and reflect on whether there is some value in going after the good instead of the perfect and focus on that as a way to build out your own, muscle on AI, and to help others develop their muscle on AI. Because even if you are ready to go when the technology is right, you're gonna have users that are going to be slower adopters. And so getting them ready will help you take advantage of AI functionality that helps transform your department to better meet the business strategy of your company. Very well said. Yes. Yes. Okay. And it does seem like CLM is being utilized as you know, the the the efficiencies are paying off. You know, it seems that people, especially with the the repository and the that it seems like that people have realistic expectations for what the CLM is gonna do for them. Yes. We talked about AI and to stretch it and to to really enhance your business strategy, but people are realizing CLM benefits today. Yeah. Yes. Today, they are. I have I have maybe unrealistic expectations because I I have seen and we all have seen how much our world has changed with the large language model, generative AI. The next phase is going to be a Genetec AI. I mean, the my day to day, the way I approach my personal life and my professional life, like, I use it every single day. So when I say I probably have unrealistic expectations, I think the technology is changing really quickly, and I cannot wait to see how organizations are going to adopt and change and leverage the technology to, like I said, the highest and best use cases to drive business strategy and not just as a repository for their contract data. So my my expectations are way up here. Okay. Danielle Hogland's our early adopter. And and now for the last takeaway, we get to talk about your VUCA. If you can't remember VUCA, we can call this the toilet paper principle, which is Yes. I like that. You'll not realize that you need the toilet paper till you need the toilet paper. Right? And I do think if if you've been waiting on on CLM, and you're starting to to to think to yourself, man, there's some things that I could do dealing with better now because of it. And take take this as an opportunity to maybe make the business case and, stock up a toilet paper Here we go. Of CLM. I can't believe I just compared to I think that's a great last year. I really wish it was. I thought that you were yeah. Alright. If you take one thing away. Yeah. Okay. Good stuff. Yeah. Alright. So we do have a few questions, from the audience. I know we have four minutes left. We'll see if we can get a couple of these in there. We've talked let's see. One of them was about the benefits of data sharing, but I think I think we've covered that one pretty well. Yeah. Okay. So how how can organizations so we talked about growth a lot. May I? You know, how organizations ensure that, you know, their chosen CLM solution's flexible, scalable. How do they ensure that to meet you know, as the needs evolve, the business needs more? How how do they do that? Not everybody at once. I mean, I already got it done first. I'm I'm thinking. I'm thinking. Can you can you rephrase that? For some reason, my brain Sure. Is not taking it if I'm being Okay. Perfectly honest. Yeah. So what do you look for in the CLM if you want to have flexibility and scalability? I think there's different things you wanna look at. So the first is, you have to really know your business and know what you're doing it for. Right? So coming in with that knowledge is gonna help you kind of find the right flexible solution for what you do, and what you might be doing in the future or the random things that might happen that you can think of. Of course, you it's like the known unknowns and but there's also unknown unknowns. But, you know, really, really do demos. Ask questions of other people who work with that vendor. Think about how I mean, talk to your IT team. Right? Like, if you don't have an IT person that you talk to a lot, this would be an opportunity to say, like, hey. If we're looking for a flexible solution that is going to be able to evolve with the needs of our business, what are some things that you should look for? And they might have some suggestions as well, right? So be collaborative, even how you're thinking about approaching the buying question. And then I think also just remember that, like, a a good well established CLM company is now an AI company too. And what does that mean? It means that the ones that have really built out the foundational end to end CLM product, they are incorporating AI into the functionality. And so, you know, just something to think about. Like, if you really want to try to get, a lot of everything, you may not have everything you want all at once, but I promise you the larger vendors are really, leaning into using AI functionality to improve the core functionality of their product. So, again, don't let the enemy the perfect be the enemy of the good. Right? I think it's the takeaway for me. Yeah. Danielle, do you have a thought? I was thinking kind of along the lines of what Laura said. I think, you know, we talked about this earlier, in the session, the importance of readiness work and really understanding where you are today, where you want to be, and finding a solution that fits within those goals. But, again, those goals have to be informed by the prework that you put into it. Yeah. And I think there's a couple of things too is the fact that make sure that who you're working with isn't making you fit your processes into their solution. Make sure that their solution fits into your process is that it you know, that's how you need your business to run. So that's how it should be done. And also make sure that if it's a, you know, absolutely the the the smaller steps taking just maybe one type of contract and putting it into a CLM, make sure that, yes, absolutely solve that problem for today, but you're once you solve that problem, you're gonna realize 14 other problems that you didn't think about. Make sure that any system can expand into solving tomorrow's problems. So, ladies, I think we're at the top of the hour. I wanna thank you both very much. What an interesting interesting conversation, and thank you both so much for your time and for CCBJ. Really appreciate all all your help and wonderfulness as well. And thank you to everyone who showed up to, hear our 2¢. I appreciate you taking the time to join us. Absolutely. Thanks a lot.