LexisNexis CEO Says the AI Law Era Is Already Here  ## Metadata - Author: [[Decoder with Nilay Patel]] - Full Title: LexisNexis CEO Says the AI Law Era Is Already Here - Category: #podcasts - URL: https://share.snipd.com/episode/7eac8a8a-63e0-46a4-91aa-9ff4a297a3fb ## Document Notes ## Highlights - **LexisNexis Rebrands Around AI** - LexisNexis now positions itself as an AI-powered provider of legal information, analytics, and drafting solutions. - Sean Fitzpatrick says AI lets LexisNexis go beyond research to automate drafting and decision tools for lawyers. Transcript: Nilay Patel What is LexisNexis? How would you explain it to the layperson? Sean Fitzpatrick LexisNexis is an AI-powered provider of information and analytics and drafting solutions for lawyers that work in law firms and corporations and government entities. That's a new conception of LexisNexis. When I was in law school in the early 2000s, it was just the thing I searched to find case law. Yes. We've transformed over time. We were kind of just that research provider. Over time, we've acquired more businesses, we've integrated those businesses. And kind of in 2020, when we launched our Lexus Plus product, we integrated all those things together. And so we became an integrated ecosystem of solutions. And then in 2023, when we launched Lexus Plus AI, that's when we became really an AI-powered provider of information analytics, decision tools, and drafting solutions. And the capabilities of AI have really allowed us to do things, do more things than what we've traditionally done in the past. Nilay Patel That jump from being the sort ([Time 0:06:28](https://share.snipd.com/snip/92872c0d-2c1f-48d3-82f9-14443814f7e2)) - **AI Meets The Language Of Law** - Large foundational models and falling token costs enable new legal AI applications at scale. - Sean argues law's language- and precedent-driven nature makes it especially suitable for language models when properly grounded. Transcript: Sean Fitzpatrick First of all, you have these massive investments that are happening with the foundational models, right? These hyperscalers, you know, each one of them is putting in, you know, close to $100 billion, you know, Microsoft, Amazon, Google. And so these models, they just, you know, continue to get better and better and better over time. That's at the foundational model level. We don't really operate at the foundational model level. We build applications that utilize these foundational models. And at that level, what we see is prices are dropping, right? So we used to pay $20 like two years ago for a million tokens. And today, you know, we might pay 10 cents per million tokens, right? So that allows us to do things at speed and at scale that we've never been able to do before. And if you look at the law, you know, there are a lot of things about the law that make these models attractive. So most of the law is language-based, right? And these models are really great with language problems. The law is precedent-based, right? Nilay Patel And so— Well, we'll come to that. Yeah. I'm not sure that that's under—that's up for grabs, basically. Sean Fitzpatrick We come back to that. I'll grant you that, yeah. And then you look at the activities that lawyers do. They draft documents, they do research, they summarize things. The models are all really, really good at these types of things. And so you kind of have this like perfect storm of this technology and the things that legal do, lawyers do kind of coming together. And yet when people try to use these models, these consumer grade models, there are all kinds of problems with them, right? You can't just put it, like you said, it's not deterministic. You can't just put information into a computer and get an answer out. If that were the case, we wouldn't need a court system, right? But, you know, what we see happening is, you know, like with these models, like they're just not built for the legal system. So you can't go into court and say, I found this on the internet, right? You have to have authoritative content. The cutoff date for GPT-40 was 2023, I believe, right? You need to have information that's constantly updated. You know, your audience probably doesn't know, you probably know this because you're a lawyer, but there's the citator, right? You know, which traditionally has said, this is good law or it's not good law, right? It's been overturned. Now it'll tell you if it's the law at all, right? Or if the, you know, some system just made it up because, you know, these systems, they're probabilistic, right? They want to put together an answer that's probably right. Well, that's not the standard that we have in legal. ([Time 0:10:09](https://share.snipd.com/snip/99e0f59f-6eec-4840-8311-68f0e5fb62d9)) - **Ground Outputs In Authoritative Sources** - Build courtroom-grade systems that ground outputs in authoritative legal collections and citators. - Provide links, headnotes, and validity checks so attorneys can verify citations before court use. Transcript: Sean Fitzpatrick So our system is backed by 160 billion documents and records, you know, that curated collection that we have. That's our grounding data, right? So you can go into court and not say, I found this on the internet, but you could say, you can refer to a specific case, right? We also have a, we call a citator agent, right? So we'll check that case to make sure that it wasn't fabricated by the system, but that it's actually still good law. And you can also look at the case law summary so you know what the case is about. You can look at the head notes so you can see the particular points of law that were addressed in that case. Again, you can see if it's still a valid case. Privacy is another issue, right? There's a special relationship that exists between attorneys and their clients. In that attorney-client privilege, there's some privacy requirements that you need to have in order to maintain that. Of privacy and security that you need. Transparency is another issue. So you put this question in, you get an answer back. Well, based on what? Like, what was the logic that the system used? So again, our system, we open up the black box and you can see the logic that's being applied. ([Time 0:13:11](https://share.snipd.com/snip/8815a2fd-799a-43d4-b0c6-02e16c67a50c)) - **AI As Augmentation, Not Replacement** - Sean sees AI as an augmentation, not a replacement, producing drafts that free lawyers for deeper analysis. - He notes AI often generates many useful and some irrelevant suggestions, improving efficiency and outcomes. Transcript: Sean Fitzpatrick I think that these models, they don't replace lawyers, right? I think they help the lawyer and they augment what the lawyer does. So if you think about an activity that a lawyer might do, like, let's say that they were preparing for a deposition. So they need to come up with a list of questions that they're going to ask the individual that's being deposed. You know, you can take the facts around that particular case and you can load them into a vault. And then you can point the system to that vault and say, based on the facts of this particular matter, develop a list of deposition questions. And then, you know, that's something that a lawyer would have done on their own, right? In the past, they may have, you know, referred to a list of questions that they had previously or something. Well, actually, can I just grab on that example? Sure. Nilay Patel Maybe a lawyer would have done that, but more often a lawyer would have told a bunch of junior associates to sit in the basement and do that. Yes. And that thing was how those junior associates learned how to do their job. Sean Fitzpatrick Yeah. Nilay Patel And that's what I mean. Like we're sort of farming out the thinking, and some people might never actually do that thinking. Yeah. And that might change the profession down the line in really substantive ways. Sean Fitzpatrick Right. Yeah. And it is an apprentice system, right? And so if you start to take some of the layers out of the bottom, you know, how does everyone, you know, skip the bottom layer and still make it to the second layer with the same level of capabilities And skills. I think that's a real challenge. You know, I think the systems are allowing lawyers to not necessarily have the associate do that work, but now they can say, you know, generate me 300 questions or 700 questions. You know, it doesn't take that long to go through 700 questions and the models never get tired. So, and what our experience is, is they'll go through that list of questions and they'll say, first question, yep, that's a good question. I would have thought of that, you know, the system made it a little bit faster, right? But it didn't really help them any. Second question, same thing. Third question, same thing. Fourth question doesn't even make any sense. Scratch it off the list, right? Fifth question, oh, that's interesting. I wouldn't have thought to ask that, but that's really, you know, something that's probably important. So I'm going to add that to my list. ([Time 0:16:43](https://share.snipd.com/snip/25a1d6a7-e243-4c9b-b2fe-a6a9c0c2625b)) - **How Juniors Historically Learned Work** - Nilay recounts that junior associates traditionally learned by producing deposition questions and motions. - Sean describes how AI can generate many questions and occasionally surface surprising, valuable ones for lawyers to adopt. Transcript: Nilay Patel Maybe a lawyer would have done that, but more often a lawyer would have told a bunch of junior associates to sit in the basement and do that. Yes. And that thing was how those junior associates learned how to do their job. Sean Fitzpatrick Yeah. Nilay Patel And that's what I mean. Like we're sort of farming out the thinking, and some people might never actually do that thinking. Yeah. And that might change the profession down the line in really substantive ways. Sean Fitzpatrick Right. Yeah. And it is an apprentice system, right? And so if you start to take some of the layers out of the bottom, you know, how does everyone, you know, skip the bottom layer and still make it to the second layer with the same level of capabilities And skills. I think that's a real challenge. You know, I think the systems are allowing lawyers to not necessarily have the associate do that work, but now they can say, you know, generate me 300 questions or 700 questions. You know, it doesn't take that long to go through 700 questions and the models never get tired. So, and what our experience is, is they'll go through that list of questions and they'll say, first question, yep, that's a good question. I would have thought of that, you know, the system made it a little bit faster, right? But it didn't really help them any. Second question, same thing. Third question, same thing. Fourth question doesn't even make any sense. Scratch it off the list, right? Fifth question, oh, that's interesting. ([Time 0:17:30](https://share.snipd.com/snip/bdfbd01d-eb63-46be-b449-58769434ec6b)) - **AI Is Already In Daily Legal Work** - AI adoption among attorneys is already widespread and growing, with two-thirds reporting use in surveys. - Fitzpatrick expects expansion as tools integrate into daily workflows and deliver tangible time savings. Transcript: Sean Fitzpatrick I think they'll figure this one out as well. Nilay Patel What are some solutions that you've seen as people try to figure this out? Sean Fitzpatrick Well, I don't know that necessarily folks have come up with a lot of solutions around the apprenticeship model. I think that what we're seeing for sure is people are embracing AI. It's here, it's in the courtroom, it's in the law firm. Two-thirds of attorneys are using AI in their work, according to our surveys. They're already using that. And our survey is probably a little outdated. I'd say the number is probably higher. I don't know about you, but I use AI every day, practically, is in my personal life and in my work life now. And I think the legal profession is, you know, perfectly suited for it. ([Time 0:20:17](https://share.snipd.com/snip/cf099976-20a6-4201-bf94-5c9607ec19bb)) - **Make Verification Effortless** - Make it easy for lawyers to verify citations by linking sources and checking formats within the tool. - Protege ensures citations are valid, in proper format, and flags whether cases remain good law. Transcript: Sean Fitzpatrick Yeah. Well, like you can never stop an attorney from just taking it into court, not doing the proper work. Right. I think that's going to continue to happen. I think somebody is going to lose their license over this at some point. Right. And we're seeing the sanctions start to ratchet up. So, you know, it was, you know, a couple of attorneys got fined five thousand bucks a piece. And then, you know, some attorneys in federal court down in Alabama got referred to the State Bar Association for disciplinary action. You know, I think the stakes are increasing and increasing. With our system, what we do is if we have a citation, we will provide a link to that citation. So you can click on it and you can see it in our system. And there's no fabricated cases within our system. You know, we have a collection mechanism that ensures that every case and there's a valid case. It's Shepard Eyes that has said head notes and, you know, different tools that the lawyers can use. ([Time 0:23:29](https://share.snipd.com/snip/f840a375-c54d-4d2f-a6dc-60ea4c04407b)) - **Keep Humans In The Filing Loop** - Always present drafts to attorneys and avoid unsupervised filing or action by AI. - Offer alerts and drafts for tasks like continuances but require attorney approval before filing. Transcript: Sean Fitzpatrick Can connect into a DMS, a document management system that has an attorney's prior motions. We have our vault capability so they can load their motions up. So they can still use the motions that they've already developed. And that's a perfectly fine way to do things. Well, I'm saying from scratch. But yeah, we have the ability to do it from scratch, too. But a lot of trainers don't want to do it from scratch because they've reviewed every single word in that motion and they know that it's good. And if they do it from scratch, then they have to review every single word, right? But if they want to do it from scratch, we can do that for them today. And we can use their prior work product if they want to use that as the grounding content to create a new motion, or we can use our authoritative material. They can choose what the source is, what the grounding content is. I guess I'm asking, what's the level of automation there, right? Nilay Patel So you're an attorney, you've got a document management system, you've got a new client, you need to file some standardized motion that you always file for whatever thing you need to Do, continuance. At what point does Lexis say, I'm watching this case, I'm going to file this for you, I'm just going to hit the buttons for you, don't worry about it, in a way that a great legal assistant Might do that? Sean Fitzpatrick We're always going to give the attorney the opportunity. We don't want to just be doing things on their behalf in an unsupervised way. So we're going to give them the opportunity. We could get to the point where we say, hey, look, it looks like you need a continuance. Here's a draft of a continuance push here, and it will automatically file it. We're not to that point today, but if you need a continuance, we can draft it for you. ([Time 0:29:40](https://share.snipd.com/snip/f1aa109c-44f2-484f-a177-42a14bf7d9fb)) - **Personalized AI Assistants For Lawyers** - Protege aims to personalize AI assistants for each attorney, using practice, jurisdiction, and past work. - Sean says automating many legal tasks is feasible now and prioritized by customers' needs. Transcript: Sean Fitzpatrick And so we're, we're working with our customers to understand, you know, what are the most important tasks? And we're working with them to automate those tasks today. So we have, you know, the largest and most robust backlog of projects that we've ever had in the history of our company, because there's so many of these things that still are to be automated, But, you know, we're working with our customers to do that. If they tell us that, hey, what we really want is for you to automatically file this or for you to, you know, provide me with an alert that says, hey, this deadline is coming up and you need To file this. Here's a draft. Do you want to file it? If they ask us for that, I'm sure we can develop it. We're not at that point today, but we are in the drafting phase. That vision, that's not like a five-year vision or a three-year vision. That's available today. That's Protege, right? That's what Protege does today. But there are tasks that it can do, but we haven't finished that massive backlog yet. ([Time 0:32:08](https://share.snipd.com/snip/7b4c3c7b-fc93-4400-b8da-ce7379bcee11)) - **Hiring Attorneys To Audit AI Output** - LexisNexis hired many practicing attorneys to review AI outputs, an unexpected but crucial investment. - Sean calls attorney review a "secret sauce" that raises output quality and legal reliability. Transcript: Nilay Patel Well, tell me about those attorneys. You hire attorneys to basically do doc review of the AI. Are they very senior attorneys? Are they moonlighting from big firms? There's a bunch of junior associates in a basement. Sean Fitzpatrick It's based on the task, right? So what we try to do is get attorneys that have experience in a particular matter. So if we're looking at documents related to an M&A transaction, we want those to be looked at by someone who has some experience in mergers and acquisitions, and they can tell us, yeah, That document looks great, or you know what, it's missing, it's missing these particular things. And then we can go back and say, why did we miss those particular things? And what changes do we need to make to the way that we're training these models and directing these models to correct that situation going forward? Nilay Patel What's the biggest thing you've learned from that process? Sean Fitzpatrick I guess the biggest thing I've learned is how important it is to have attorneys doing that work. ([Time 0:45:34](https://share.snipd.com/snip/d46c7631-7b6d-44e8-ab7a-3042edd3fdf9)) - **Tools Are Neutral — Use Determines Impact** - Tools are neutral like bricks; uses determine outcomes and harms in legal contexts. - Sean acknowledges the product can aid originalist research but insists LexisNexis doesn't shape legal decisions. Transcript: Sean Fitzpatrick Definitely understand your point there. You know, I think about like the analogy of a brick, right? You can use a brick to build a hospital to take care of sick children, or you could take a brick and you could throw it through a window, right? One use is really great and one use is pretty negative. But in either case, it's a brick. I think about our tool as being not good or bad. I think it could be used for good. You know, I think it could be used for, you know, any type of activity that attorneys, I wouldn't want to say originalism is a bad thing, right? I think it could be used for many different things. I think it could be used for originalism. I think it could be helpful for those that, that wanted to take that path and find a new way of looking at something. We have all the data. They can search it. They can use the tool to find things that they, you know, it wasn't possible to find in the past. So I could see them, you know, using our tool in that way. ([Time 0:55:35](https://share.snipd.com/snip/583eb902-7a97-4e98-af4d-539f22b2a67d)) - **Follow Responsible AI Principles** - Apply responsible AI principles: transparency, human oversight, privacy, security, and bias prevention. - Relx (LexisNexis's parent) enforces these principles across product development and deployment. Transcript: Sean Fitzpatrick Have responsible AI principles that we operate under. And so that includes a number of things. One is we always try to consider the real world implications of any product that we develop. We want to make sure that there's transparency in terms of how our product works. So we open up the black box so people can see the logic that we're using and they can actually go and change it too if they want to, right? So we want to make sure that transparency and there's control. Human oversight, right? So we always incorporate human oversight into the development of our products. Privacy and security is another one of our core tenets of responsible AI creation. And then the prevention of the introduction of bias is another thing that's incorporated in. So those are the relics principles for AI development. ([Time 0:58:38](https://share.snipd.com/snip/78b7ee92-9cf9-4633-960e-46bbea9b4358)) - **AI Reflects Prevailing Case Law** - Protege returns mainstream legal interpretations, recognizing recent cases that affirm birthright citizenship. - Sean demonstrated the tool answers reflecting prevailing case law and notes alternative interpretations exist. Transcript: Sean Fitzpatrick Can't tell you. Do you have your phone on you? There's a mobile app. I could pop up here and ask it, I suppose. So what was the... Hold on a second. Let me pop into Projet here. All right. Does the 14th Amendment guarantee birthright citizenship or are there exceptions? Let's see. Yeah, I'm very curious to see what it says, because up until recently, there's only been one answer to that question. Nilay Patel Then now the Trump administration is saying there's no, actually that's not what subject to the jurisdiction thereof means. And they will, in order to win at this report, have to construct an originalist argument to that question. And I am confident that the way they're going to do that is they're going to feed a bunch of data into an AI model and say, this is what was actually meant at the time of drafting the 14th Amendment. That's a thing that AI will be used for that is very destructive. Sean Fitzpatrick I'm not an attorney, by the way, so I'm just going to read the answer here. 14th Amendment of the United States Constitution guarantees birthright citizenship to all persons born or naturalized in the United States and subject to its jurisdiction. The phrase subject to its jurisdiction has been interpreted to include nearly all individuals born on U.S. Soil, with a few narrow exceptions. These exceptions include foreign diplomats, children of foreign diplomats, children of enemy forces in hostile occupation, children born in foreign public ships, and historically Children of members of Native American tribes who owed allegiance to their tribe rather than the United States. Nilay Patel Yeah, you should send that to John Roberts right now. Can Protégé do that? Because that's the answer. But the question is, well, you said that on this podcast, are a bunch of conservative influencers going to say Protégé is woke now? Sean Fitzpatrick Yeah. I mean, it does recognize— This is the culture war that you're in. It does recognize that recent cases have affirmed this interpretation, rejecting attempts to expand the exceptions of birthright citizenship. ([Time 0:59:50](https://share.snipd.com/snip/f7ee4fa8-9399-4259-8eae-74d014098b47)) - **Customer-Led Roadmap For Continuous AI Growth** - Short-term roadmap focuses on automation of many attorney tasks using latest models and customer-driven priorities. - LexisNexis plans continuous evolution as models improve and costs fall, with lawyer needs guiding features. Transcript: Nilay Patel Think these questions, they're going to come up over and over again. We should have you back to answer them as you learn more, but as you look out over the horizon the next two, three years, what's the next set of capabilities you see for LexisNexis? And what do you think the pressures that might change how you make some of those decisions will be? Sean Fitzpatrick Yeah, I think the main thing that's going to change the path going forward, and it's hard to say what exactly what it's going to look like, because if I look back two years ago, I would have Never guessed we'd be doing what we're doing today because the technology didn't exist or it was too expensive to implement. That's totally changed over the last two years. And I think over the next two years, it's going to change again. And so it's really hard to say where we're going to go. Our vision remains the same, which is that we want to help attorneys. We want to provide them with a personalized AI-powered product that understands their practice area. It understands their jurisdiction. It has access to our authoritative set of materials. It has access to their prior work product. It understands their preferences. It understands their style. It understands what they're trying to do. And it can automate tasks that they do today manually. ([Time 1:07:22](https://share.snipd.com/snip/eb6d7930-5441-4b24-ad6e-e620f3fc7799))