Transcript for "Turning risk into competitive advantage":
or good evening to everybody. Thank you so very much for joining us. I'm very excited to have this conversation today about how you can turn risk into a competitive advantage. Really thrilled to be joined by, of course, my colleague, Marvin. If you've been to these before, you'll know that we sort of roll like Bert and Ernie. But also more importantly, Lily, Lily Shore, the senior commercial counsel from Swosgrove. Lily, how are you doing today? I'm great. Thank you. So happy to be here. Thank you guys for having me. Oh, it's it's absolutely a delight. Go ahead and tell the tell the tell the gathered masses a little bit about, your background and your interest in in risk. Yeah. Absolutely. So hi, everyone. I'm Lily Shura. I work as senior commercial counsel for Sourcegraph. We are a company focused on enterprise developers. We have both a code search product that allows developers to search their various code bases and also a new agenda coding product that, people like me even can use to ask, AMP is the product to build anything. Right? Just use natural language to act as your developer friend to help you build things. So it's particularly cool on the enterprise developer side, but also very cool for me as someone who's always had big ideas and no way to make them happen. I am an attorney. Like I said, I'm in house counsel, but I, am also a super legal ops nerd. I've spent my entire career, analyzing data and information and then turning processes into, improved processes, whether through automation or through, just general best practices. And I've spent, basically, my career has taken these beautiful, unimaginable twists and turns, to be honest. I've spent time, in house at a CLM. I've spent time running my own consulting company, consulting for both emerging legal tech products and, in house teams looking for legal tech, looking to improve their legal operations. And now my, my role here allows me to do a little bit of everything. I play around with our tool to build legal tech. I negotiate our contracts. I use that tech to improve our contracts. I you know, get to analyze data and turn it into actual insights. To me, risk is a critical part of every legal team's job. It's a critical part of the way they operate and, having a really strong understanding of your approach to risk as a company, your approach to risk as a lawyer, and how you analyze that and turn it into something that company can use to be better informed. And, action on that data is the best way to be successful in a legal role. So, super excited to talk about this topic today. Fantastic. Well, really glad you're here. And, Navin, you have to keep it short. Tell us a little bit about your background so everyone understands where you're coming from on this. I I really wish you had gone Simon Says keep it short, but, you know, I'll I'll I'll take I'll take this instead. So hello, everyone. For those of you I have not met yet, I'm Naveen Maha Bijin. I'm head of community at Agiloft. You might see me at a bunch of our events or, you know, legal ops and legal conferences as well. But before this, I have a very similar background to Lily as well. So I can keep it short because just everything she just said, that's kind of me too. I, started my career out as in house counsel at an oil and gas company. So risk, not a stranger to that. But over the years, I've held roles as head of legal operations, worked in contract management, worked in legal tech companies, and, have been a consultant and run my own consulting firm as well. I love to implement CLM platforms and deal with contract management, contract data, and looking at those pesky clauses and, you know, extracting them and seeing what they say. So short enough for you, Simon? Brilliant. Absolutely fantastic. I'm noting that down as a record now then. Alright, everybody. So we're gonna dive in. This is gonna be, a play in five acts. We're gonna talk about five different things as we go here, sort of moving our way through, understanding risk, looking at ways we can control it. The the sections we're gonna talk first about just kind of really defining it. We're gonna talk about how we can get better access to it, how we can move from sort of as a moot compliance to a growth mindset, get more proactive than reactive. That's sort of the the the step. Everyone says four no. The fifth next of course, is your questions. So ladies and gentlemen, please ask us some questions. Pop it into that question, bar. Let's see if we can get to some of your ideas as well as some of ours. So jumping right in, our first sort of area is control is greater than chaos. Right? And so my question first to you, Lily, is how do organizations interpret or possibly misinterpret risk when it comes to contracting. Right? We know that the contract process just just sort of doing the contract can show up 18% of the sales cycle time. So are we doing it wrong? Are we doing it right? How do how do you see, where we are sort of broadly speaking in the world today in in understanding risk? I think this is actually this conversation is so timely and it's something I've been talking about quite a bit lately. I think over the last few years, at least, legal teams have been really focused on, the concept of a playbook and whether that's something they use themselves to negotiate, whether it's something they've given to the business to self serve with, or it's some sort of combination cross functional cross functionally of understanding the risk appetite. So I'm gonna speak to it kind of from a playbook perspective. The approach for a long time has been this is the concept, this is the language we prefer, these are kind of fallback language, examples we're willing to to get to, and this is the, you know, kind of hard stop. This is as far as we can go. And I think that we have now come to a place both as a legal industry and, in our world with, you know, with the involvement of AI and everything that we do at this point, that we need to shift our mindsets a bit. Like, our understanding of risk is so long been focused on however many concepts we can cover and how how far do we deviate from our traditional position. Whereas now, I think it's more of, for both us to think more clear in that conversation with us, which is what are the core things we care about? Not across our contracts, what are the 30 clauses that matter, but what are the core things that are important? So for example, with our agentic product, I care a lot about making sure that we have a right to retain data, solely for the purpose of being able to run the threads functionality, for example. Like, if someone says I'm not allowed to retain their data, then we're gonna be able to reach that this second phase or I care so much less about governing law because I need to know that these, like, five critical things allow the product to function, allow us to move forward. So then taking a look at risk less about everything we could possibly cover, less about what the language itself really says, and more about the substance, the core issues that we face as an organization, the things we need to give our customers what they need and and to drive value, aligning on that as a business and allowing for that more creative and critical application of how can I get there, how can I still have the things I need, but meet the customer expectations and answer their questions too? So really more of that kind of change in focus to how we address risk. Yeah. That makes that makes a that makes a lot of sense. I mean, I think understanding the balance, between risk and opportunity and also kind of the size of the risk. Right? Somebody said to me a little while ago, that she balances the, the severity of the risk against the, you know, against the effort it's gonna take. If our risk is $300, then we're not gonna spend seven hours of outside counsel time trying to negotiate it. Navin, what what are your thoughts on this? No. I I agree with Lillian. In fact, it makes me think about something that that we were talking about, before this session started, this is the prep session, or the technical prep session. But, you know, when you think about risk, I'm not gonna try to define it and say there are different kinds of risk. But, you know, you see something as risk and you also have to think about is it enforceable or practically applicable as if I want to avoid this risk. How much is it going to cost me to put the systems in place to track and enforce this risk avoidance language that I've put into place as well? And so, I think that so early on in my career, I was kind of forced. I I don't want to say I was born business minded, but I was kind of forced to be business minded and and think about opportunity cost, you know, because in oil and gas, there is a hefty amount of risk at play no matter what you do. And you can't just contract risk away. Things go wrong, things happen, you know, pumps blow up and pipelines start leaking. You don't want it to happen, but it does. And so I think balancing just we need to get this document signed so that we can all make money versus fussing about every single, you know I heard I heard when we say governing law. I mean, governing law can be important, obviously. I know. I don't want anyone clutching their pearls thinking that I'm saying governing law doesn't matter. But but kind of really focusing on what really matters and what I've observed, at least with how organizations interpret this, is they start from this kind of overwhelming checklist of this is my preferred scenario that is extremely one-sided and extremely lengthy of I don't do this, I don't do that. I I make I have to make everything mutual because, I'm balancing risk, although not really, you know, but and then you work backwards from that that playbook example. So, you you know, to me, when you kind of manage risk and try to control it by slowing down your entire contract process, that's that's a huge, thumbs down because what you're really doing is you're you're choking the lifeblood out of your company, which really is all these contracts that need to start getting into play, whether they're systems you need to use or whether it's revenue you need to earn as well. Yeah. And I mean, would you say that to some degree, this has been kind of the the core of the kind of the how do you wanna call it? So misalignment sometimes of the kind of the legal team and the business team. Right? That legal has a series of of of kind of as it were risk flags it's looking for trying to avoid that are to no small degree. It's invisible, right, to the business side. In the same way, the business side may have goals and see opportunity that are difficult for the legal team to see in the contract. Does that does that seem like a reasonable guess? Well, I think it absolutely is. You know, different teams, and and it's kind of I always bucket it as legal compliance. Sometimes Infosec, sees risk one way, and then everybody else or the business side sees risk through a different lens, as well. You know? So so you're absolutely right. And I think it's it's really a blend of both. Right? Because, what hap what tends to happen is and and this is kind of part of the practice of law. We're trained to be both adversarial and highly conservative on risk. You know, you want to negotiate the the best contract for your client. When you move in house, your client becomes the company that you work for. But in doing so, there's a mismatch between these two ways that you view risk, and you might find yourself being the stumbling block in holding things back or worse here to kind of stick with the theme of the section we're talking about creating a lot of chaos, you know, where you Google, what about this? What about this? Instead of having a structured approach to risk, which I know, we'll talk about as well. Yeah. And just to add to that quickly, I think there that that mindset shift as a lawyer, Nava, is so important to point out. I think as you become more business minded, you start thinking more strategically, and your approach to risk becomes less about, did I check off this thing on my checklist as you're noting or this thing in my playbook? Or am I looking at this more from this lens of practical realities? You know, what I'm are the things I'm asking for meaningfully resolving the risks I care about? Are these risks actually impacting my business? Or are the things that the other side is requesting something that, practically speaking, will allow us to move forward or is a hard stop for the realities of how we do business or how we serve our customers. So it is it's an interesting constant internal battle, I think, to figure out, but that's why aligning on what that minim reasonably scoped minimal risk profile looks like is actually so critical because it allows you to start to be really mindful and intentional in how you apply those, those risk mitigation techniques that you're trying to apply. And and I seem to remember you you had a an interesting story about doing that with AI related clauses. Am I remembering that right, Lily? I I mean, AI is like everything I think about today because our products are so AI infused. I mean, I don't mean to be maybe maybe I meant that in the general are, like, all of us. No. It's it's interesting because I have found that the same it's it and I can talk about this all day long, but the same people who've negotiated the same kinds of contracts forever are the same ones who are negotiating for these really innovative AI products. And and I'm not always seeing that same kind of application of analysis of is this actually risky or is the thing I'm asking for reasonable in this case. And I'm I'm particularly aware of that because I am on a very small legal team. There are three of us at a relatively small start up. There's, I think, a 160 of us. Like, we're not a very big team. And so when we have these enterprise customers come in with these expectations of this is my checklist of 30 things that I have to have from every vendor, that can that can kind of stonewall us a bit. And so the example I gave in our prep session that I'll share with this team here is, I've seen a lot more AI restrictions included in either NDAs or MSAs lately. A lot of that pushing from customers to say something along the lines of either on the NDA side, you will not use AI to analyze confidential information. And that can be that can be kinda challenging to meet. Right? Like, if your email inbox has AI capabilities, are you then in violation of that, of that clause because the confidential information is full of your bad inbox or you're analyzing that information in some way to summarize it? Or on the MSA side, things like you can only use AI services that have been preapproved in this contract. And that can be tricky too as a vendor like us because our tool, while it is AI, the agent coding tool AMP, it has so many underlying LLMs and inference providers that we're working with that, you know, I don't wanna end up in a position where we don't have the ability to be innovative and work with the right kind of tooling. And the customer doesn't wanna be in a position where they don't know what providers are accessing information. Right? So it's a really delicate balance to figure out. And what I found to actually be the most helpful in those cases is to just allow that to open up a conversation, really dive in to the reasons behind the ask on the other side. Because the reality is they don't they're not going to be upset if your email system summarizes their confidential information. Right? They they don't care about that. They're not going to be upset if you work with an LLM provider who has a zero data retention policy. But it's more along the lines of we wanna make sure that we know who has our data, that it's controlled appropriately, that you're not kind of taking it outside of this realm of protection that we need to be able to entrust you as the vendor in. So I think we're in this period of, really diving in deeper on what all of this means and what the actual risks are with AI in particular, that make those meaningful conversations the competitive advantage we need to analyze those risks and to take that data and then, you know, iterate over time on what our positions are. So, it's something I'm I'll look at every day and I think is is really top of mind for me is how how we take these kind of, frameworks and turn them into knowledge that helps improve negotiation across the board. That's a great bridge into our next little thing. I'm keeping my eye on the clock for you. That's my job. Don't know don't know a lot about the legal stuff, but I I I got the clock. I'm I'm a good timekeeper. So let's talk a little bit about that. So we there's a really good idea of this this concept of understanding, what we've got, understanding implications. And I think and where we turn to now is how can we know rather than find out? And what I mean by that is how can one have a vision it's like like visibility over what's happening as it's happening and kind of see challenges as they come over the horizon rather than finding out when the letter from the expensive lawyer arrives or the angry account manager turns up. Obviously, at Agiloft, we've we've put in a lot of work recently in building out an obligation management tool, which actually we've got a brand spanking new version we'll be turning up next week. We're very excited about it. Can't get too far ahead, but it's really cool. But I guess my question is, how how do we go about turning something that's just subjective as what's the risk, into into measurable patterns? Marvin, why don't you jump in? We'll give give Lily a moment of a buzzword. Alright. How much time do you have, Simon? I you know? You have three minutes. Well well, we think about measurable patterns. Right? Every every organization with with a few exceptions that I've worked with has always had this is what we think our risk profile is, and then there's what it actually is. You know? And I think that's where technology can really shine. Right? A, getting that information out of the documents themselves. And it can be, you know, without giving you too many different examples. Right? Do we have price control language in these vendor contracts, or do we have opt out? Something simple. Or if we're a health care company, are these contracts, you know, properly containing, you know, HIPAA language and language protecting for protected health information and stuff like that. So I think where technology shines is, a, exposing what your what's in your documents. Now that's just the first stage. Right? The second stage is now, you know, let's call it risk scoring. Right? And it can be as simplistic or as complex as you want it to be. So I know some organizations will calculate a score based on different attributes for the company, and that varies from industry to industry as well. So it might be your exposure to handling private data. You know, is it covered in the contract that you're allowed to? Is it provisioned for in the contract that you will be or that you will be having access to internal systems of your customer, as well. And so that gives you the power to actually, a, assess what your actual risk is, and b, you know, maybe adjust your policies as well and rethink how you can be, a lot more efficient. So you look at those measure measurable patterns kind of that you mentioned. Right, Simon? I I had, I worked with a company once where they were tech they're a technology company, and they had language around penalty payments. So if you did not pay your bill, you would get charged interest essentially, like like as if you were a credit card company. And so I don't know the history behind why it was enforced why it was put into these contracts. But having to kind of reassess and derisk some of these contracts, but also improve the negotiation process so that it didn't take as long because they were kind of hyper risk averse. One of the things that we decided was you don't really need this in your contracts anymore. And the way we figured this out was, a, we determined that it was getting removed, from contracts in negotiation, 80 plus percent of the time. And I kinda would make the argument that the other 20% of the time people just didn't notice it was there and they just signed the contract. So so that that piece was considered, high risk. Again, it may seem a little trivial or silly, but it was a it it was a source of revenue potentially, but also it was kind of a stick. You could, you know, force people to pay. Like, we need to make sure people pay their bills because that was considered a risk factor as well. It turned out it was never once enforced. So nobody no customer ever had interest penalties placed on them. So it's an unenforced clause on top of that. And and we got at that by, of course, not pulling from the contract itself, but a dataset from a different system from finance to go, yeah. So let's let's actually look at at all your customers and see. So so this is my long winded way. I I don't wanna go over the three minutes allotted. I think this is where technology shines. You get that data, you can analyze the data, and you can discern patterns in very short order. It might not be perfect. Like, you might not get super discreet the way you would if you were spending a year just, you know, going through every contract with a five tooth comb, but it's incredibly powerful because of how quickly you can do it. Yeah. I mean, I as as I pass this to Lily, I do wanna just make a comment with you. I think that's a fascinating story. I love first, you make me feel feel very old that you don't remember how payment terms used to have a period of time and then how much you could take off if you paid earlier and how much extra you pay after. After. That was like it was, you're making me feel old, man. But the the point here is we we're looking at this definitely through a legal lens, but from a business lens, obviously, having that 2% as it were threat in your initial profit in the contract is actually probably a greater risk than not having it in the first place. Because if it's getting knocked off every time, that means people are reading your contract and going, oh, yeah. No. That's not acceptable. I wonder what else is bad. It's, it's it's the old brown M and M story. So so really an interesting interesting story. I guess my question to to you, Lily, is sort of to move it over a little bit as we talked about using technology to service things and to make it interesting. Like, obviously, as you as you mentioned, doing a lot with AI, thinking a lot about AI. You know, I guess the question here is how much has AI changed our ability to find things? And and where does it, either, enhance or clash with human judgment? I love this question, and I'm so excited that you're following my line of thinking as to what I was go going to say anyway. I think a few years ago, we were in this position that was awesome, which was, you know, across our contract portfolio, how many of our contracts have x y z clauses or do not have x y z clauses. We can take that quantitative data and use it to, you know, make certain determinations or to move forward. We then kinda move to this instead of just pulling the clause itself. Like, how do we parse that into data that can maybe be reported on more easily. Right? So instead of here's your assignment clause across 300 contracts, you know, of those 300 contracts, this many are assignable without consent. This many require consent, for example, taking it and turning it into something more data driven. And that's really post signature. And I think now we're in this stage where we can have a lot more fun with and be more creative with how we use AI and apply it to these kinds of cases. So, for example, with our our product just launched four months ago. Right? It's new. Our negotiations are new. My my team and I write wrote these terms that apply to the products in the first place. So as I'm analyzing the negotiations over the last four months, I can use our AI tool, for example, and help parse okay. What where did we make concessions, in what areas, and help decide why, and what does that mean for the future moving forward? What changes do we make to our terms? Were these things that we thought were risky, that we thought we cared about, or do we really care about them as much now? So I think that host signature analysis in particular has become very interesting to me because it was it was always about identifying risk, but the way you do it now and what you can use it to move forward with, how you can be You know, we've always talked about being data driven and having actionable insights, like, how you can take that information and turn it into something truly actionable and change the way you do business and improve the speed at which you contract. You know, for example, by removing that clause that you're gonna remove anyway when someone asks you to. It's really, really powerful, and I think we're only going to continue to, enhance the way that we work with the data in our contracts. Because the reality is, like, these are words, but they're they're date pieces of data. So the more we treat them like pieces of data, the, you know, the more we can use AI to analyze them and become better, faster, more efficient with what's in them. I I I couldn't agree with that. That's so well said. And I and I also think I I'm with you. We're sort of really in the early stages of the journey. I think AI has completely changed the way we think about unstructured data, which is what a contract is, right, just a bunch of narrative. We're really good at pulling it out. And so we got that far. I think the next stage is recognizing once you pull it out, then that data deserves to be looked at by another AI because now you're able to do the pattern recognition, the trend matching, to have the insights that the human being can't see it. And we're still working towards that. And and I think it's so important that we get that good data early on. We track it over time. We give it provenance. If somebody comes back nine months later and says, I don't remember saying that, we have to go to come back and verify it's there, but we still need to give it that that AI treatment. Alright. So alright. We we all agree this is good. I guess it's bad. It would be much more fun if we'd all disagree violently, but we have to keep moving. So okay. If you agree one of the things by the way. It can get very dangerous here if we're not careful. Yeah. I'll I'll start I'll start swinging that bad boy around, you know. But, I think Yes. So we are glad to be able to I'll I'll try I'll try to be the contrarian, in the next slide. Alright. So we agree. Like, we need to have a better look at risk. Getting getting the data out can really allow us to make really sensible decisions that are not sort of trapped within our bubble of, oh my gosh, we can't give away anything. I guess the question is, once we do that, how do we, as it were, action there? So I hate to use action as a verb. It really bothers me as a as a as an old ex English nature. But I guess the question is, how can we embed risk management of the workflows without slowing deals? So I'll give you a couple of examples to come to my head, and then and then we'll have you a much better informed version. You mentioned clause libraries, which I'd like I'd like to to actually, no. You didn't. I mentioned clause libraries. You mentioned playbooks, which I wanna double click back on. Playbook's big thing, obviously, we do with screens. Right? We have a little contract review system where you say, here's 10 yes no questions. Did it pass? Which we found to be terribly useful. On many levels, much more basically, many levels, nothing. Actually, much more accurate than saying, here's a bunch of clauses I like. Here's a bunch of clauses that just came through the door. Tell me tell me how they fit together. It's probably asking a bit much of AI. Asking asking if it passes standards, really effective. But, you know, that sort of thing. So, going first, can't remember this time. It's your turn to go first, Dolly. So how do you see embedding kind of what we learn into our workflows so that we can both, you know, retain confidence over our risk and compliance management, but also expand our opportunity from a business perspective. Yeah. Well, I'll I'll I'll I'll oh, sorry, Lily. What were you about to tell me? Turn. I got I got confused, Simon. Was it me or Lily, actually? It was Lily. Oh, well, I'll I'll shut up for now. I have so much to eat. I'm sorry. We started this by Simon saying, more importantly, Lily Shiro is here. So let's not forget. More important. Just kidding. No. I I just wanted to say quickly on this piece. The all of this feeds into the next portion of this, the plan five x, for example. It all blends together. So identifying that risk, the real what you actually care about, keeping it reasonable and reasonably scoped and minimal, and allowing it to, keep that strategy of moving your business forward as the guiding light is really impactful. And then applying, you know, to see this is really impactful. I find that we're in a cool base where, you know, my my playbook that was once this mighty, mighty beast has become, you know, a couple of pages of quick notes on what I actually care about and how to how to kind of be creative and address things so that falls within the risks that matter to me and matter to my business. But one of the things I found particularly interesting is by treating playbooks and risk profiles in a way that makes sense for AI, it makes me faster as a lawyer too. So for example, I'm just gonna use a this is a basic example, and I'm sorry to use it. But for NDAs, like, I we are a very small legal team. I do not have time to read an NDA deeply. I'm doing too many other things. I'm going to skim it quickly anyway. I'm gonna look for a few key things based on that playbook. I've now been able to leverage our agentic coding product, which is not made for this, to say, okay. These are the 10 things or the let's be realistic. These are the five things I care about. The only things that are unacceptable are these three. Everything else I'm fine with. And I I want you to read this, and I want you to give me two bullet points. Recommendation, should we move forward? Yes or no? No more than, you know, 20 words. That comes out in, you know, fifteen to twenty seconds. I skim the NDA, confirm that it's valid, I move on. So being able to get to that place where I everything everything about automation, everything about use of technology has always been processed first, then technology. So process and aligning on what that risk profile actually is, what you really care about, using technology to make that better in some way. And then, again, using that guiding light of my business is trying to move fast. I am not a good legal partner if I slow down an NDA review by five days, for example. I'm a great legal partner if they send me an NDA, and I can get it back to them in thirty minutes. Right? So being able to kind of leverage what is your role, what is your role in the risk profile you're analyzing, and how are the things that you care about actually protecting your business versus supporting you in that role you're trying to play. So, I think it's it's really exciting to see all of that come together, but I will fully admit that every day is a new iteration on that. Every day is a new analysis This is how it's working, how to make it better. Yep. Got it. Results. If you have any. I don't know if you have any. I I mean I mean, you know, Lily kinda stole all my thoughts at this point. But no. No. I I I agree with all of that, Lily. And and, you know, my kind of ethos is you obviously want to automate as much as possible. Less is more, I think, when you think about risk. And I did want to add something about kind of actual approvals, like analytical, sensible approval processes for risk management. When do these come in? Right? When we see deviations, you know, hey. Someone wants to insert an update clause that it affects revenue, or, like, how you track revenue for your that sale sales contract, for example. And and you start going to multiple people because we all build these systems in tech. We build a workflow where we're collecting information on the front end to an intake form, and that helps us extrapolate the risk as well, when we're reviewing the contract. And then we apply the playbook to kind of make it a bit more efficient. What do I really care about? Because the days of, I think, cloak and dagger clauses like, I mean, if you're dealing with the reputable Fortune 500 SaaS company, they're not gonna stick in a clause or, you know, your firstborn child now is, you know, indentured to work with us for all time or something like that. It it may be we own the IP rights to whatever you build in our system, and then you have to decide if that's okay because you're not really doing anything super novel or exciting that you can patent or that it's not okay because you really are doing something serious. But what I was gonna say was, from an approval's perspective, if you're sending it to someone to approve, either as an escalation or secondary approval, if all they are doing is, well, this is okay. This is a big contract, so I'll say yes. That is not risk management, and I think those are steps that you really need to carve out of your risk management process. You think about managing this and, like, making it actionable, I think, actionalizing as you said, Simon. So that piece, the kind of not because then what you have is not risk management. You have bureaucracy. And that's what you're really trying to automate away when you do something like this. Yeah. I mean, I I will say one of the most interesting solutions I've had proposed over the last six months, was a chap who works at a very I I wanna be very discreet, but a a very large company that has, many, let's say, sort of outposts around the world that they do different work. And what he said to me was, what I want to do is I wanna take that screens concept of it's a series of yes, no questions. I want to embed it into our contract life cycle management system so that when somebody at one of these far flung places wants to, I don't know, hire a guy to clean the snow off of the front steps on a Thursday. Well, I want the contract because we have taken on some, we have taken on some some liability. Right? So I want the contract, but I don't wanna have to read it because it's gonna cost us $500. So what I want to do is to upload it, run the screen, Assuming the screen comes back with a reasonable answer, I want it to immediately approve it and pass it back to the guy, say, yep. Get that signed. You're off to the races. Now that, to my mind, is a really smart way. Of using the technology we have to ensure that we're not creating work for ourselves. And I I'm really interested to see, as we release our next version of the the screens integration into Agiloft, literally, like, next week, I think. How many people start to see ways in which you can use that little AI thing and then hook it together with real code to say, okay. Now that I know the answer, I can I can make sort of, as it were, deterministic decisions? I can make yes, no answers. It should be really interesting. Alright. So final final act in our play, how to get proactive versus reactive. So this is this is this is kind of a weird thing, but I'm thinking now, you know, we've had our risk. We've we've had our conversation with our counterparty. We've signed our contract. Right? So now everybody has made promises and commitments and obligations. If it's done well, we've all agreed, kind of what the, what the bonus is if we outperform, because because that's the thing we always think about. Also, the penalties is when you don't do it, which we all know are the things you're thinking about right now. How can we use, like, AI technology to track those obligations to, make sure that everybody is sort of keeping their side of the deal in a proactive way rather than waiting for the angry letter to cross over into into someone's inbox? Of course, it wouldn't be a letter or it'd be an email, but, you know, you know what I'm saying. Nava, thoughts? Well, you know, as I touched on this a little bit, I think, but, you know, AI is incredibly powerful for extracting obligations and and all that stuff from signed contracts. The other thing that people really have to think about is you need to pair this with data from other systems as well to kind of push that example of the financial systems. Right? Because, you you know, the the four corners of the contract don't don't always tell you, was this risky? Did did this result in a loss? Did this result in a gain? Did we pay penalties? All that information is stored in other systems. And so I think that to to answer your question rather directly, Simon, I think AI is incredible at digesting massive amounts of information. You know, that would have taken me and a whole team months to kind of pass through and, you know, make those connections, and make sense of everything and and draw some analysis out of that. Like, what did what worked, what didn't work, what should be changed, what can we be a bit more lenient on. So penalty payments for nonperformance are a big one, I think, for most companies that provide services, especially whether it's, you know, SaaS or actual in person. And so being able to track that and then mirror that with not mirror that, but connect it with when you did pay penalties as well can then help you identify what contracts a, you know, resulted in penalty payments. And then now you can get into a deeper level of analysis, which is, okay, but what do these contracts say? What were the situations around these contracts that actually resulted in this risk? And what you might find is that you had tighter SLAs because you kind of deviated from policy here and, you know, your customers wanted, you know, three day response instead of your standard five business days. And the contract alone tells part of that story, but then you didn't have the support staff to actually fulfill on that SLA. You just agreed to it because you needed to close that deal and, you know, get the revenue, for example. So so, really, what AI is really powerful at is looking at multiple datasets and actually letting you draw some, you know, useful analysis out of it very quickly. I think I think you raise a really interesting point, Naveen. I And actually, I didn't think we were going to go through this. So this is really interesting how this is developed. But I think that in the same way we were talking about kind of aligning the view, the perspective, the goals of the legal person who's trying to reduce risk and the business person who's trying to create opportunity, we also have to start aligning those systems. Right? We've tended, I think, in the software space to think of kind of the legal system, just legal tech, if you will. I mean, it's all of the island, and we operate everything inside. But I think you make the really important point that if we really want to help the rest of the organization to, grow and to learn from what you, Lily, I think quite rightly said data hiding in the contract, we have to be able to not only extract it and manage it, we have to distribute it. We have to put it into other systems so that those processes also have the opportunity to grow and to learn and to develop and to improve because everything ain't gonna come from the legal team. Right? We're gonna know whether we, you know, whether a risk should have been had, but we're not gonna know whether it was a great contract or not at the end of the day. Because, yeah, we're not really tracking that. We're tracking whether people did what they've done, said they was gonna do. Right? So, I guess, Lily, Dulce. Yeah. Absolutely. I did this topic speaks to my trauma in in such a powerful way, and I say that with love because I think about being in a role where the CEO go, every other day to the desk of the contracts team members and say, like, hey. How many of our contracts have this clause in it? And before we had a CLM, that was an impossible task. Right? Just brutal, brutal time spent analyzing each of these contracts. So we I've been all about, like, steps toward a better position, right, in this in this conversation. The next step was having that data in the CLM. Sorry. I'm being attacked by the sun. Having that data in the CLM and being able to, like, answer those questions. And if, you know, it wasn't part of the initial dataset that we included, then figuring out a way to, include it moving forward. We've now been able to move a few steps further in analyzing that data in different ways. But when it comes to your role at the business as a lawyer, for example, to be proactive, to be truly a lot of this information. Not only do the systems need to be connected, which, like, is a larger webinar for a different day. But, but I think there's something really powerful, you know, as you're analyzing things whether, you know, in negotiations say, well, somebody's gotta make make sure they sign up for that notification so we get that in, you know, subprocessors for changing, for example. Or as you're looking at things post signature saying, okay. This is where, you know, data matters such that somebody has to do some waiting to see if they did it. How are we notifying them that they have to do it? How are we removing legal as the police here to make sure that it happens and making sure that everybody really knows what their role is? Because the contract is such a powerful document. The contract is the thing that defines what our relationship is. And the problem is for so long, that's just that with legal. And most of the information in there is not legal in nature. Right? Whether it's through various, like, boilerplate things or through the, you know, the order form attached to it or the SOW, whatever it may be. And it's just it's really hard. It's been really hard for our industry to move away from that lawyer's owner of contract position. I think now we have this really powerful position we can come from just say, put into actionable usable data. And let's transfer that ownership to the people that need to have it such that legal legal is enabling the proactive nature of this, and can be can afford to be reactive when things come. Like, we know that our systems are in place such that this team knows that they need to go deliver the service as of this date. Right? Instead of us having to check on that and remind and inform and all of that. So I I'm really excited to see how that evolves over time. Because I don't think we're totally there yet, but I I do see the light, and I'm very excited by that. Yeah. I think I think you make a you make such an important point. Right? Is is that inside of a contract, there is a fairly finite amount of data surrounded by very important but also quite dense words. Right? Because we're trying to make sure that we say, you know, you'll mow my lawn. It's very much you will mow my lawn for a particular level on a particular day. Right? But in the end, what we what needs to get translated is once per month, one lawn month as it were. And I and I do think that allowing that communication to happen where we take the kernel, so tiny piece of data, we'll put an IP address on them, so everybody can get at them. That really is the future of unleashing the value that sometimes hides in contracts. I read the other day, there was a study that said in many cases or in some cases anyway, when it gets bad, companies get only 60% of the value that they anticipated out of a contract because it gets signed and we don't really keep track of all of the details because it's just too difficult. So I think there's a great future coming, I guess, is the way to look at it. It's not glass half empty, but glass half full. And so as we wrap up, I guess, what I'd like to do is ask each of you to, you to what advice would you give to a company that's trying to move from being reactive to risk to being proactive and making strategic strides through risk management. I'm gonna start with you, Navin, because I'd like Lily to have the last word. Alright. Alright. I'm I'm gonna stay on theme. I think my my key takeaway is when you think about a risk management strategy, be proactive. Right? You don't want to wait until it's a fire drill that you have to do because I I that's that's our shared trauma here, in that, you know, Rashi kind of analyze stuff. So I think, really, it's it's just you need to spend the time to assess what your risk policy and what your specific risk profile really is. Now, of course, that's easier said than done. And so the second layer to that is, of course, if you do not have the time, you should bring in a subject matter expert, or a consultant because the truth is that I think in most cases, that is an investment that is worth doing if you've never done this before and you're in the chaos phase of your risk management journey. You know, because you're looking at things like identifying what actually does constitute risk. You're looking at building processes to both capture that risk and, you know, build plans around it. So take that that SLA example. I'll use that as my parting words. Right? Many companies agree to some kind of SLA, and there's a standard where, hey. We can typically respond within five business days or forty eight hours, whatever that number is. Right? And if you deviate from that, that needs to be flagged to someone. And now that someone has to actually manage the actual risk, not the not the risk in the contract, but the very real risk that if you don't properly staff that particular project that you miss your SLAs and you pay penalties and then the executive team or the board is very cross with you. So so I think in go to get away from situations like that, you do need to spend the time to really sit down and go through this with a semi fine tooth comb backed with technology and some subject matter expertise in this space as well. So that that would be my parting words. I know that he probably has something way better. So I'm I'm confident. No pressure. Put no pressure, Lily. No pressure at all. Just be brilliant, please. It's just it's fine. I got it. Well, first of all, there are 32 of you who who've been with us for fifty two minutes, and I just wanna thank you for doing that. I I know that a lot of this can seem really overwhelming. I think about the realities. I mean, Nava, you brought up this, you know, the word bureaucracy that's constant in a lot of in a lot of these kinds of roles. Right? This is this is what we do. This is how we do it. We, you know, check off these boxes. We move on. There has been the reality of your role, it's there's been a culture developed where you're kind of removed from the business. You're a piece of the puzzle, but then just moves past you and you don't have insight. Information is you're kind of a step back. Really, look at what you're dealing with. Look at your realities as a as a lawyer, as a legal department, as a team feeding a business. Right? And determine how you move forward. Where do you want to go and how do you get there? And that can really honestly freak people out because it's a huge undertaking, especially when someone comes to you and gives you the mandate of saying, like, I want you to apply AI to how you negotiate, for example. That can be extremely overwhelming if you can barely, you know, manage the systems you have today. So I think that there is such power in just taking little steps forward and finding real wins in that. Right? Because the reality is when we talk about turning risk into competitive advantage, we both mean that, internally and externally. Right? You become a much better lawyer for your business by enabling faster negotiation, better risk management within your business. You become a much better lawyer for your business by negotiating more clearly, cleanly, faster, more efficiently, externally with the counterparties. So kind of taking a high level, looking at what those bullet points of what you really care about are, and then developing some sort of action plan to move forward with it to enable you to turn risk into competitive advantage, I think is is going to be really powerful for you and puts you in a position like now instead of being able to bring in the subject matter expert whether whether internally or externally to really drive that home for you. I that's very well said. And I and I, you know, I I can't emphasize enough. Think beyond what we're doing and thinking about the business. That's going to be the great leap forward for corporate legal departments over the next five years. It's not going to be, oh, we're doing a deal, stop off and see the lawyer, get the contract worked out and then go on about our business. It's going to be a a truly smooth working together piece because for the first time in human history, you can extract the data from the contracts in ways that you couldn't ten years ago. On that note, I I just wanna, I I think we're about there. So I wanted to thank you so much. Not been always a joy to have your crazy background out there. I'm sorry you chopped Iron Man's head off, but other than that, we're good. And Lily, thank you so very much for making time today. It's really been a pleasure and a joy to get your perspective. To all of those of you who stuck with us, thank you for your time. Thank you for your attention. If you have any questions following up from here, you can find all of us easily enough on, on LinkedIn, all over the place. We would love to hear from you, and I hope we'll see you again soon at some kind of info lesson or webinar style event. Have a wonderful rest of your day. Thank you, Simon. Thank you.