Ep 39: Empowering Teams Through AI Skills Enablement with LexisNexis Chief Information Officer Reena Tiwari

Evan: Hi there, and welcome to Enterprise Software Innovators, a show where top tech executives share how they innovate at scale. In each episode, enterprise CIOs share how they've applied exciting new technologies, and what they've learned along the way. I'm Evan Reiser, the CEO and founder of Abnormal Security.

‍Saam: I'm Saam Motamedi, a general partner at Greylock Partners.

‍Evan: Today on the show, we’re bringing you a conversation with Reena Tiwari, Chief Information Officer at LexisNexis

With over 10,000 employees in over 160 countries, LexisNexis is the global leader in tooling and resources for legal research, boasting the world’s largest database for legal and public-records information.

In this conversation, Reena shares her thoughts on AI integration at LexisNexis, AI applications transforming the legal space, and navigating future trends of AI skills development. 

I imagine like the business you're in has a lot more complexity and sophistication than probably most your, your clients and customers really understand. Do you mind maybe sharing some of the ways you guys using technology that let's say the average customer, maybe the average listener might not fully appreciate?

Reena: So at LexisNexis, you know, we have been deploying AI, for example, for over a decade. We've been using natural language processing and machine learning and deep learning to be able to create the product and solution for our customers. We have more than 2, 000 technologists in the company of 11, 000 employees, and the way we create the content or the solutions for our customers is not just through the technology, so it's technologies, marketing, and also subject matter expertise that we have in the team.

And we are not just in the U. S. We are a global company, about 150 countries where we support our law firms and corporate markets. So that's the kind of benefit we bring to the table. 

Evan: So if you maybe kind of go back to like nine months ago, right. When you first joined, um, again, you could have worked at a bunch of different places, but you intentionally chose LexisNexis, right. Do you mind sharing a little bit about kind of what inspired you or what excited you and kind of like why, uh, yeah, like what, what felt kind of the most exciting about, you know, moving into, um, you know, CIO, CIO role there going into 2024.

Reena: So one of the key thing that drove me towards LexisNexis is because we are supporting lawyers. And because we are supporting law firms and large corporate markets. And I don't think there are many companies who do that. And, and it was very, very interested to work in the company that provides that type of service to non-technologists. That was one of the reasons. 

And I think from my role perspective, this, this is a large organization, a very complex organization, the way our operating model is a little complex. And from a CIO perspective, my tagline for my team is to simplify, harmonize, and modernize our technology internally. And just that, if, if I were to tell you, Evan, my team is simplifying the architecture, we are harmonizing the business process and we are modernizing our architecture and technology that itself is just, you know, passion enough of mine to just join it, join the company.

Evan: Well, wanted, why don't I maybe kind of shift the covers a little bit of talk, get to go back to AI. I know you mentioned it before. Um, I feel like it's impossible to have a podcast in 2024 without talking about AI. Right. I, that would be like absurd. So, um, you know, a lot has changed. You know, with the acceleration rate of AI, you know, you, you can't go on LinkedIn or read a news article without hearing about AI.

But to your point earlier, right, like, you know, AI and machine learning has been around for a while, right? It's not like a thing that popped up, right? LexNex has been using these technologies for a long time. They just, technologies have gotten different and better. And so maybe my first question is, where do you think we are in that hype cycle?

Right? It's very hard, I think, for a lot of our listeners to tell because on one hand you're seeing things that are obviously incredibly novel and kind of mind blowing and obviously very impactful. But on the other hand, right, there's a lot of marketing hype around it right now, so where do you think we are in the, in the kind of AI hype cycle?

Reena: Before I talk about the hype cycle, I would, I would say the reason why this is such a big noise in the world is because of the ability of every human using that technology without subscribing and without going through buying a technology. ChatGPT, for example, because of them enabling every single user or every single individual on this planet Earth to be able to use an AI based technology. That's why I feel the hype is really, really high compared to any other previous hypes we have seen. 

So I think that's where the massive hype is coming from because everybody is talking about even school going kids are talking about, you know, I've talked to a lot of parents, they are now watching their kids not using answers from chat GPT to do their homework, you know, those kind of things.

So I think that's the reason the hype is there. 

Evan: And Reena, is that in kind of contrast to like the big data hype of 10 years ago, right? Cause it's not like what you're saying, like with the big data hype, it was all vision and theory, but it's not like everyone had like a little consumer app they could use, they could test out and experience the possibility of big data where you had to kind of dream.

But what you're saying is that with ChatGPT, like, there's an example of like the potential impact and it caused people to like imagine and envision that, right? And that's why you're saying that like the hype is, you know, maybe unlike other kind of cycles we've gone through. Is that right? 

Reena: That is exactly my thought processes.

That's why I'm seeing that differentiating factor between the previous other technology hypes versus this one, because it's more, um, more in the hands of every, every person. Whereas that big data was behind the scenes, only the enterprise or the people in the technology would know what big data is. With that hype, though, it becomes a challenge, your question around how do you differentiate between the hype and the reality, and that's, I think, every, all of us, all the technology leaders are struggling with.

How do we do that? And I don't know how others are dealing with this, but for me, the way I try to coach my team and the things that we are doing within our team is to really educate ourselves first. First educate ourselves. What is generative AI? How is it different than the other type of AIs that we have used in the past? Prescriptive, predictive, those kinds of things. And once we understand, then really question our processes. 

So, for example, I would say, if I look at my SDLC cycle, and I'd say, how are we writing code? How are we doing code documentation? How are we doing QA automation? In the data space, you know, how are we going about talking and looking at data deduplication?

And for every single thing, Let's, as a leader, challenge our team and say, okay, you're doing, working on data duplication. What are the different AI based capabilities you can use to do data duplication as opposed to hiring data stewards and manually doing that or subscribing to some subscription based, you know, yellow pages or something and using those.

There has to be a better way of doing it because this way of deduplicating your data has been around for 30 years. I'm sure there is a better way of doing it. And those are the kind of things you can start to challenge your team. And that's when you start to realize, okay, this is a problem I want to solve for.. Then what are the solutions out there? And then you start. 

So this is more of a bottoms up approach, as opposed to, oh, there are 10 technologies out there. How can I use them? And maybe those technologies are not fully baked in. Maybe they don't have all the capability. Maybe it's more of a marketing spin on it.

So creating that balance is how we can differentiate reality and hype. You know, first get your use cases. First, really at the ground, understand what problems are you trying to solve? Then go try to solve it and look at the different technologies out there and, and solve it. So that's kind of the approach I'm taking in my team.

And the way we are looking at measuring the success of this is identifying these use cases within my team and then trying to measure them and monitor them and reward anybody who comes up with a different idea with a unique idea. I want to reward them differently, really showcase the work that they are doing so that others get encouraged by that.

And it shouldn't be like this one person doing it sitting in that ivory tower on the top and because they are in the AI space, they get a different privilege. No, everybody should be using those kind of tools and technologies to improve their day to day lives. So that, that's the kind of thought process I have in mind in, in, in implementing these, this area.

Evan: I think maybe like, unlike, you know, the most recent crypto hype of a couple years ago, where people were searching for kind of use cases and trying to find some like material wins. It does seem like there's real results that, um, customers are seeing in their environments. And I do think the promise of AI is not caught up with like the results from AI, the impact of AI. It's not caught up with the promise, right? There's still a gap to close there. 

But even for you guys, right, there's been, you guys have launched, um, some really powerful features around, you know, document drafting and summarization, right? So that people can instantly produce, like, contract clauses and legal arguments, right? And that's all, you know, that's AI, right? So without a doubt, right, there's real impact there, right? So are there cases where, you know, you guys have seen, you know, impact, right?

Like if you were making an argument against, you know, someone who thought AI was all hype, right? It feels like you guys have some pretty good examples of, no, actually like, yeah, there's a lot of hype, but. right? Here's kind of real things you'd be able to do to better support our customers using these new technologies.

Do you mind sharing, you know, any of those you can share? 

Reena: Yes. Um, and so, you know, I'll give you an example. There was a case in New York where a lawyer went on to chat GBT and drafted his or theirs use case and later on found out that there was all hallucination. That case didn't even exist. And that's where the value we bring. 

You know, our major concern from out of the box free version is that they don't, they, they hallucinate a lot. They don't have the real data behind. Because it's gleaned from websites and all, they can't really name the source of the information. And so that's where we bring the value. We use the latest and greatest technology, which we have been evolving for the last decade or so, and use that data that we have.

We have so much real data and We focus on not hallucinating. We focus on bringing privacy, um, all all that privacy security around the data. We implement all of that to create that product. So the solution that we provide to our customers is is real. Is true, and it helps them in improving their productivity and efficiency, and they can get their answers that they're looking for faster.

So that's the kind of thing that we focus on.

Evan: Are there any particular upcoming use cases, um, around AI, you know, for, for legal professionals that, you know, you're, you're excited about or you think it's going to be, you know, really impactful or kind of change how, you know, maybe lawyers and other types of clients kind of work?

Reena: So we launched Lexus plus AI solution earlier in 2023. And that is where we are focusing on, and we continue to evolve that technology and make it a global expansion across an entire globe. We started with U. S. and now we are expanding to other regions, other parts. And that's kind of what our focus is.

And again, it focuses on four key capabilities. Conversational search. So it's more of a conversation as opposed to just entering a question and getting answers. It's document drafting. So, you know, it can instantly produce legal arguments, contract clauses and all that stuff. Summarization functionality, as well as the document upload capability that enables the users to analyze, summarize and extract the key insight from the documents that they upload.

So those are the type of capabilities we are focusing on and we continue to evolve on those. 

Evan: Maybe kind of talk a little more broadly about the AI trends in the market. Like, I think every, every technology leader or every person, I think has an opinion on like where AI will be helpful and where it won't be helpful.

Are there areas that you see kind of people being a little bit bearish about that you personally feel more bullish about, right? Are there, are there use cases around, you know, this could be necessarily like in your product, but maybe more in like terms of like how enterprises can use AI to power their operations or help run the business that you feel kind of particularly, you know, excited about it in the past, we've talked about, you know, customer support and customer success, but, um, other areas, right, where you just feel like, Hey, there's like a bigger opportunity here than most people realize. 

Reena: Yeah, I think the sales and marketing area could be one potential where we could see a lot of help with the automation. A lot of focus needs to happen on automation, on bringing this insights to the sales and marketing organization, helping them trying to understand their day to day lives, and providing that insight into the customers that they are working with. And then customer support. We've all been talking about operations and that chat bot type of features for the customer operations team. How do you make it more conversational? And I think every company starting from that and then going to the other areas. 

And one area which people don't really talk about is this insight part. There is a thought process that we have to start thinking about the reports and the insights. You're a CEO, Evan. How about you get a real life impact of every single deal that is done in your organization? 

Evan: That would be amazing. That would save me from looking at a lot of, uh, Salesforce and ERP reports. 

Reena: So I think those are the type of opportunities we need to start thinking about and looking things differently. I'm not saying that we don't use AI today for those, but can we change it. Again, break it and, and fix it in a different way? Uh, how you get your reports, how you get your up to date, real time reports on your fingertips. They are on your phone all the time. You just have to pick it up. 

It's kind of like that tickers stock ticker thing. You know, you have that ticker going on your app, some app, and it's predictive in nature, it's real time in nature. I think those are the type of outcomes we have to start looking at looking at. And from an enterprise technology leader, those are the areas I think we, we, we ought to start thinking about.

Evan: That's a good point because most. I was gonna say most leadership roles, but it was probably true for like most roles period, right? Or like half the roles at a company. At some level, the job boils down to like some assessment and judgment and then act and then recommended action. Right. And certainly like, you know, as AI, you know, maybe it requires chat GPT version 20, right? But at some point, right, I think undoubtedly these, these tools will enable all of us, right? Independent of our roles, right? Independent of the, you know, where you're on the org chart to get better kind of understanding where we're at, you know, assessing that, you know, making a judgment about kind of what's best, how to prioritize. So that's, that's a, that's an exciting world you're, you're painting. 

Reena: It is very exciting. That's why we are all here. 

Evan: That's why we're here. That's right. Okay. Well, I want to, um, maybe we want to kind of shift gears a little bit, uh, talk more about, uh, you know, developing, uh, you know, developing a technology organization.

So I imagine that as you were kind of coming into your role, you were trying to assess, you know, what capabilities and competencies do we have on the team, how are we organized, and then contrast that with, okay, where are we going to be going over the next couple of years and what are some of the new workstreams or technologies that are going to be available and how do we kind of develop, you know, our organization to make sure that we're able to execute against those. 

So, um, You know, I talked to, you know, probably a CIO once a day, right, uh, as part of my day job. Um, I think everyone's kind of thinking through this, like, hey, how do I build a AI native team, right? Because that's undoubtedly going to be part of our future, right? Across IT and technology more broadly. So, you know, how do you think about that? Is there going to be? you know, new, you know, new skills, right? New training that you need to kind of inject to the team. Are there new roles that just like didn't exist in the past?

Like, you know, well, well, LexisNexis have a GPT knowledge manager, right? Like that, or, you know, there's these new roles that will be required in that future organization that maybe just. You know, we kind of have to invent, love to hear how you're thinking about how you, you know, best tee up and equip, equip your team to help them or help, you know, the organization best develop and succeed and have an impact right over the next couple of years as technology, you know, changes so fast.

Reena: This is a very interesting question because this has been the question for ACIO forever. How do you continue to manage the business, continue to reduce your technical debt, and get out of legacy systems, because every, every place there is legacy, and in parallel, continue to innovate? and think about new technologies, train your team. It's really a balancing act. And what percentage of your focus, your budget, your resources you want to put in new technologies, and what that percentage looks like, and how do you do that? 

At a very, very high level, if I want to break down the areas of our work, or the types of work that we do, It's basically run, run the business is what I call it. It's, um, if we had no innovation, if we had no changes. What type of work we will keep to keep the lights on. So that's one part. 

Second part is we keep on enhancing our current technology a little bit, a little bit, a little bit because the business needs it. So that's the second part. Third part is we have this massive transformation work or, uh, or our organization needs a massive transformation in certain areas. So that's more of a transformational area. 

The last piece is that innovation piece and more often than not, if you don't continue to focus on that, that becomes a zero. So as a leader who wants to continue to evolve and change and bring new technologies into the, into the mix, you protect that fourth area in whatever shape or form, whether it's your 1 percent of your time, money, resources, whether it's 10%, you define depending on the size of the company, depending on the journey of the company, depending on the journey of your team, but identify that area, protect that area and continue to have a dedicated focus on that.

But once you prove out, so that's the innovation part. You do the innovation, you prove it out. Once you prove it out, then you expand it and explore it in all the other areas. To my earlier point, this innovation team doesn't need to sit in some tower and look down upon everybody else. They need to be on the ground working with people.

So they do the pilot, they do experiment, they, they figure out this is something that we can use and expand everybody. And that's when you get into the. training part, um, education part, and coming back to the AI, I think everybody should be taking an AI course. Regardless of what your job is, even if you're not in a technology team, you should be taking an AI course.

I think schools and colleges ought to make computer science and computer programming as part of a core subject like math, English, science. Everybody needs to know programming and thereby everybody needs to learn about AI and, and that's going to evolve humankind, if you, if I may stretch. 

Evan: I'm with you. I agree.

I mean, it's, it's hard to imagine how it won't, right? And generally like using computers and technology, right? Those are just key skills that can apply to pretty everyone's job or everyone's day to day life, right? This is how we, you know, communicate and engage with the world. 

Reena: Um, so, so that's how I think about keeping up with the skills, um, continue to help my team grow by pushing them.

And by putting that metrics, how many of you are taking new technology courses and measuring it over a period of time? 

Evan: Okay, unfortunately we have, I want to ask you like seven more questions about AI in the world, but unfortunately we only have five minutes left, so I'm getting the red light from our producer.

So wanted to kind of, um, maybe end the episode with a bit of a lightning round, right? So looking for kind of like the one tweet responses, which I know will be, you know, I'm going to throw you some curveballs. 

Reena: Oh, I forgot about that. Yes. 

Evan: Yeah. I'm going to throw you some curveballs. These are hard to answer briefly, but, uh, you're looking for like the, the, the quicker, the, the, or the punchier responses.

Reena: Okay. 

Evan: Um, so I got maybe like five questions. 

Reena: Okay. 

Evan: So first one is, how do you think companies should measure the success of a CIO? 

Reena: By having the CIO connect the dots between the key metrics of the company and their work. 

Evan: What is one piece of advice you wish someone told you when you first became a CIO?

Reena: Focus on talent first, then the projects and delivery. 

Evan: How should CIOs best position themselves to collaborate with the rest of the C suite? 

Reena: Be able to speak in business term, not just only technology. 

Evan: And maybe switching gears to the more personal side, is there a book you've read that's had a big impact on your life or your work or your leadership?

And uh, if so, love to hear why. 

Reena: The latest book that I read is a very good book. It's called Our Iceberg is Melting, and that talks about change management and as a CIO leader, change management is something we don't focus on, but that helps. 

Evan: What is an upcoming technology that you're personally most excited about? It doesn't have to be AI, because I know that's probably my answer, but like, you know, more broadly, like, if you look at technologies emerging in the world, you know, what do you just feel kind of personal excitement and passion for? 

Reena: I think home automation is still very far behind.

I would love to put in that type of automation in my home that it knows everything that I want and it should just does it. I shouldn't have to do half the things at home. 

Evan: That's right. Imagine everyone could save, like everyone in the world, right, could save, again, this might take us decades, but if everyone could save 15 minutes a day. Right. Not having to do all this, that mechanical things. More time with family, more time for hobbies, more time for impactful, meaningful missions. Right. So, uh, 

Reena: Building relationship, having fun, going out, rather than doing household chores. 

Evan: Yeah, that's, that's, that's right. That is, that is, uh, I share that dream.

Okay. Last question. I'm looking for, kind of looking for like your contrarian take. Right. Something that maybe you believe that other people don't. What do you think will be true about technology's future impact on the world that most people would consider science fiction today? 

Reena: We believe that technology is there for everybody. I don't know the exact percentage, but there is a large amount of population in the world who does not know or does not use technology. So I think it is at this point more of a science fiction because I don't know how to get there, but everybody should have access to technology. And by technology, you get support in everything, whether it's law, whether it's financial, whether it's personal, you know, any kind of support, it should be on your fingertips.

And the only way it should be on your, it can get to your fingertips is if the technology is available to you. 

Evan: One of my favorite, um, authors has this quote, says the future is already here, it's just not evenly distributed. 

Reena: Correct. 

Evan: Well, Reena, thank you so much for taking time to join me today. As always, I really enjoyed the conversation with you and I'm hoping we can chat again soon. 

Reena: Yes, it's always a pleasure to talk to you and I learn a lot from you as well, Evan.

Evan: That was Reena Tiwari, Chief Information Officer at LexisNexis

‍Saam: Thanks for listening to the Enterprise Software Innovators podcast. I’m Saam Motamedi, a general partner at Greylock Partners.

‍Evan: And I’m Evan Reiser, the CEO and founder of Abnormal Security. Please be sure to subscribe, so you never miss an episode. You can find more great lessons from technology leaders and other enterprise software experts at enterprisesoftware.blog.

‍Saam: This show is produced by Luke Reiser and Josh Meer. See you next time!