[00:00:00] Irene Liu: Welcome to AI Sidebar. I’m Irene Liu, your host and executive director of the AI Initiative at Stanford Law School. Today, I’m delighted to welcome April Miller Boise, who served as executive vice president and chief legal officer of Intel, where she led Intel’s global legal, trade, and government affairs organization and advised the executive leadership team and board.

[00:00:22] She led her organization through a period of significant corporate transformation, and during her tenure she conducted a cross-functional survey of corporate legal departments to identify how AI could deliver the greatest value to the legal team and the broader business. So today, we’ll discuss what she learned from that survey, how legal leaders can approach AI adoption strategically, and what it takes to drive meaningful change in large organizations. So, without further ado, let’s dive into the conversation.

[00:00:57] April, welcome to AI Sidebar. We’re so thrilled to have you here. 

[00:01:01] April Miller Boise: Oh, I’m thrilled to be here, Irene. I’m so glad you asked me to have this conversation. Looking forward to it. 

[00:01:06] Irene Liu: Yes. And so, April, you joined Intel in 2022, and you’ve gone through a very pivotal transformation for the company, and you helped lead it through your role as the CLO. So, can you tell us about that period and the transformation that Intel was going through, and what it required from you on the legal side? 

[00:01:27] April Miller Boise: Sure, absolutely. I think it’s well documented in, in the news, but certainly I was on the inside and so, you know, you get to see how the sausage is being made. But I think it’s, you know, very well known that number one, the semiconductor industry, if you’re a manufacturer, it’s a long cycle business. And so, it often takes a long time to turn that kind of company around. We were going through a significant transformation that started before I got there, and that continues. 

[00:01:52] But for the four years that I was there, we got a significant amount of work done really in thinking about our strategy and our technology and our product roadmap, our culture, our people, and our organization. And I think Intel, like many, you know, large companies that are leaders, particularly that are, significant leaders in their space with significant market share, sometimes lose their way.

[00:02:17] And I think what Intel found is that, you know, their technology roadmap was just not keeping up with customer expectations. Maybe they had gotten a little bit arrogant, and certainly, were not as customer focused and customer centric as they needed to be.

[00:02:32] They also got a little bit away from the core, right? So, the core of what Intel does is semiconductor leading node of design and innovation and manufacturing and started getting into a lot of other businesses that were adjacent to that. And really, we needed to get back to the core to make sure that we were a leader in leading node logic semiconductors. 

[00:02:53] Irene Liu: Yeah. And as part of that focus, did you have to lead the legal team as well to also center their focus on the company focus? And how did you do that during that time of so much change?

[00:03:05] April Miller Boise: No, absolutely. So, during the period, you know, that I was at Intel, we really were transforming every part of the business, including all of the corporate functions. And so, really looking across the organization and thinking about what corporate functions, the work that the corporate functions were doing, and were they aligned with the core strategy, and did they have the right leadership team and the right core strategy in place.

[00:03:29] So, we really brought together some core parts of the corporate function. So, corporate security, government affairs, community affairs, legal, compliance, ethics, which we call integrity, and really kind of bringing that team together and looking across the board and saying, “What’s the important work that we’re doing, and is the work that we’re doing every day focused and aligned with the work of the company?”

[00:03:54] ‘Cause I think what companies find, you know, as they grow and, and maybe start to get a little bit unwieldy, you have people that are far-flung and that maybe are not as close to the core, and really are not focused in their daily work, on driving the strategy. So, the first thing you do is really reset the strategy and make sure the leadership team and the board are aligned around that strategy and then cascading that strategy out to the team.

[00:04:20] So, as leaders in the C-suite, it’s really our responsibility to make sure that our teams understand that strategy, it’s easy to explain, we call it strategy on a page, so you’re gonna see it on one page with some key bullet points. And then saying to our teams, like the work you’re doing every day, you need to see how that work directly drives this strategy.

[00:04:41] And I think what happens sometimes, you know, too often is the work that teams are doing on a daily basis is really not, you don’t see the direct line to the strategy. It’s kind of related, but it needs to be very, very clear how that work is driving the strategy and is clearly aligned with the strategy.

[00:05:00] So, that’s a big part of what we did, is focus on the alignment and also focus on the culture. You know, really having a culture of, of can-do, you know, focused on our customers and doing the things. We talked about our say-do ratio, making sure the things that we say, that we’re following through on them and doing that work with our customers and for our customers.

[00:05:20] Irene Liu: I love that you say a few things. There’s a say-do ratio, as well as strategy on one page. Is that, is that what you said? It was a strategy on one page?

[00:05:27] April Miller Boise: Yeah. We called it S.O.A.P., so strategy on a page. It was like our, we’re having our S.O.A.P. Meeting, but it’s something that we did every year to make sure that there’s clear alignment. You know, presenting that, working on it with the C-suite and the leadership team, and then presenting that to the board once we have that alignment- 

[00:05:44] Irene Liu: Yeah 

[00:05:44] April Miller Boise: …you know, being very clear on one page and then cascading that to our teams. 

[00:05:48] Irene Liu: So, with that S.O.A.P., oftentimes I hear of documents, you know, there’s a famous, you know, Amazon memos as well too, but you hear that they often run longer than the, than the page limit. Did it stay one page? 

[00:06:02] April Miller Boise: You know, it did. I mean, I think having the strategy on the page is critically important. 

[00:06:06] Irene Liu: Yeah. 

[00:06:06] April Miller Boise: One of the things we saw, though, and one of the things we did, obviously during my tenure, was making very clear to the market that we were going to be a foundry. And so, you know, separating the, the P&L for foundry and the product business.

[00:06:20] Irene Liu: Yeah. 

[00:06:21] April Miller Boise: So, then we had a corporate strategy, which was the strategy on the page, but we also had a separate very clear strategy for the foundry team because we wanted to make sure that, you know, that’s standing up a new business. They weren’t used to operating, they were supporting the products team historically.

[00:06:35] They weren’t used to operating as a standalone P&L, and so that was really important that we had a clear strategy for our foundry business as well. 

[00:06:44] Irene Liu: Yeah, I love that. And one of the things that you also, during your tenure, you started in ’22, but ChatGPT was launched around that time as well, too, and so, or during your tenure, and so I’m sure AI became a key part of your business strategy as well as your team strategy.

[00:06:59] So how did you, as a CLO, move your team from awareness to actual experimentation in using AI, and was AI part of your S.O.A.P. as well, too? Was it part of your key business strategy? 

[00:07:11] April Miller Boise: So absolutely. So, I started in June or July of 2022, and then in November of 2022 is when OpenAI launched, you know, their first GPT model to the public. And so that was a game changer. I mean, I think certainly lots of technologists and people in tech, you know, in the background who were focused on technology were using artificial intelligence and were using generative AI. I mean, AI has been around for a long time, but having that generative AI model, that GPT model available to the public, I think they went to, like, a million users very quickly, and then 10 million users faster than anyone ever. And now they’re at over, I think, you know, almost a billion users. I think it’s, like, 900 million users. 

[00:07:56] And so, it absolutely fundamentally changed the way that everyone does their work, or certainly thinks about how we do our work, particularly, knowledge workers, you know, people who work in, in companies like the companies that, that we’re familiar with.

[00:08:11] And so, I think any good CLO or anybody in the C-suite always has a technology roadmap. That’s a really important part of the strategy for their organization. And AI and generative AI is now clearly a very important part of that technology roadmap and really has consumed a lot of that technology roadmap, and certainly a lot of the, the mind share and the dollars.

[00:08:35] And so, absolutely, you know, that was something that we quickly wanted to understand, like, what, what is this ChatGPT? What are the opportunities for using it in business? And I think initially people were just playing around with it, trying to understand the capabilities. And I think initially people were using it as, like, a very sophisticated search function, right? But now we’ve learned how much more generative AI can do and applications that we can use it in across, you know, certainly across the legal, corporate legal function, but across every corporate function. And beyond, there’s an opportunity to improve the work that we do and improve our efficiency simply by incorporating generative AI and agentic AI into our work.

[00:09:17] And so for us, it was very important to kind of re-look at our technology roadmap. And one of the things I found, Irene, and, and you and I have talked about this a little bit, is I think some organizations were delegating that technology roadmap to their legal ops team. And what I have found and what I have seen is the best practice is that it really needs to be led by the leadership team.

[00:09:42] So, like, the CLO needs to be really engaged and involved in what is our AI strategy, where are we going to deploy resources, what are the best, technology platforms, where should we be thinking about investing and adopting now, ’cause it’s gonna have the most impact on the work that we do. And what I, what I saw is, again, some organizations would delegate that to the legal ops team.

[00:10:08] And not that the legal ops team doesn’t have a role to play, you know, they’re gonna be, you know, implementing it and, and driving this tactically across the organization. But the tone from the top is really important, ’cause I think what we’ve seen is some lawyers and other knowledge workers would say, “Oh, this doesn’t have anything to do with me. What I do is, is very special and very bespoke, and so I don’t need generative AI. Generative AI is, you know, for other parts of the business or for other parts of the legal department.” 

[00:10:36] And so I think it’s important that the CLO really understand the opportunity, understand the platforms, and really step back and rethink about the work that we do, how we do our work. We talk about remapping our work, so it’s not just putting AI on top of the exact same work that we’re doing. It’s, you know, we, we have a challenge or an opportunity and we’re trying to get to an end goal. There’s a whole bunch of steps that happen in between there. We don’t wanna just keep doing those same steps and put AI on top of it.

[00:11:08] So we really spent time with all of my subject matter experts, I ask them to think about remapping the work that they do, thinking about their best opportunities, most significant opportunities to leverage artificial intelligence, and then to think about and help their teams think about how would that work change, and how did that work need to change in order to be much more efficient once we, incorporated AI.

[00:11:36] But if the CLO isn’t involved in that and driving those conversations with the, you know, your leadership team and the legal department and beyond, you know, whatever the focus is of a particular corporate legal team. So, like, we had corporate security, you know, they’ve also used artificial intelligence a lot in their work, they were some of our earliest adopters. But if you don’t have that tone from the, that tone at the top from the leader, it’s, you’re gonna have, you know, some people who are early adopters and love technology, but you’re gonna have a lot of people who just, you know, ignore it and say, “This is not for me. I’m gonna keep doing my work the way I’ve always done it because no one is mandating that I change.” 

[00:12:13] Irene Liu: I love that you started with the fact that it’s important for the leader at the top to be very engaged, and because there is a tendency to, designate a proficient lawyer or a legal operations person to basically lead it and delegate it.

[00:12:28] April Miller Boise: Yes. 

[00:12:28] Irene Liu: But really- Yes … if you are just as engaged and you’re setting the tone that this is important, and you partner with legal ops. Legal ops is a very important function for in-house teams. Absolutely. So, you need to partner with them and set the tone at the top that this is important, and this is not just going to be delegated to one person, but it is an, an across the organization effort. And I think it’s great that you incorporated different teams. 

[00:12:52] But you took it even one step further, April. From, from our discussions, you said not only did we start engaging the leaders, but you actually wanted to know what are other companies doing? And you hired a consultant to benchmark other Fortune 100 AI uses. So, can you tell us a little bit more about that consultant study and what you found? 

[00:13:11] April Miller Boise: Sure. We did do that. I thought it was really important, you know, that we learn from other organizations who are facing similar challenges, and maybe be, may be approaching those challenges differently. 

[00:13:22] And so we did retain a consultant to help us do some benchmarking, as you said. And not just with Fortune 100 companies, we wanted to talk to all different types of companies where I heard a CLO was really leaning into their technology stack and their artificial intelligence roadmap. I wanted to go learn from them. You know, they were ahead of us. What, what have you learned? 

[00:13:45] And so, there were some private companies, there were large public companies. There was a couple of smaller public companies as well, and it was really helpful for us to hear about the challenges that they encountered as they thought through their technology roadmap. 

[00:14:01] And I think it was interesting, there was like a build or a buy mentality. So, we talked to some of the large financial institutions, and that was really interesting because they had deep resources, and they also have a lot of regulatory challenges. And so, some of the large financial institutions were saying, “We’re gonna build it ourselves.” Right? “We’re gonna have all of our data scientists who are a part of our team, they’re gonna really understand the work that we do, and they’re gonna go and build our own technology platform.” Not everybody can afford to do that. You know, not everybody is, is JP Morgan or Goldman Sachs. 

[00:14:35] Some of the organizations, what they were doing instead, even if they had deep resources and deep pockets, they were leaning more into evaluating all the platforms that were available at the time. This is the other thing that, of course, is happening, is it’s changing very, very rapidly. So, this was, you know, more than 12 months ago. It’s changed tremendously since then. And so, we did all this benchmarking, which was very, very helpful with a number of companies and their CLOs and their legal, their legal ops teams. 

[00:15:05] But the other thing we did is we also interviewed a lot of the legal vendors as we learned who was adopting what vendors. We wanted to go and talk to the technology firms to hear what their plans were. You know, what does your platform look like? How are you thinking about the ecosystem? How is it continuing to evolve? 

[00:15:24] And so having those two sets of conversations, with CLOs who are definitely leaning in, who are, who are out in front, and then some of the best tech companies and the tech stacks really informed our thinking about how we should be approaching leveraging and adopting artificial intelligence.

[00:15:40] And you can imagine, like, if I left that work to the legal ops team, number one, I would’ve been very, far removed from the solutioning. I wouldn’t have had the right data set to help problem solve with them. And we may have ended up in a really different spot, because they don’t necessarily have the same, broad insight and, you know, just exposure to all the company’s challenges and opportunities that I do. They’re seeing it through a very particular narrow, you know, legal ops lens. And so, I think that was really, really important and helpful for us on our journey. 

[00:16:14] Irene Liu: So, on that journey, did you have, like, a small group of AI task force, in essence, that was reviewing the results from the consultants and then trying to figure out the best way to implement it moving forward within the department?

[00:16:28] April Miller Boise: Sure. So, we had a couple of things. So, number one, the consultant that we retained, I had them come in and talk to all of the leaders on my team. So, they interviewed, in addition to the CLOs and the tech companies, they talked to every leader on my team about how they were using technology and how they were thinking about artificial intelligence or not.

[00:16:50] So, they learned a lot about, you know, where are we tech-savvy, who’s really leaning in, who’s likely to be an early adopter. And there was a feedback loop, so she shared with my leadership team what she learned from her conversations with the tech companies and what she learned from her conversations with CLO, and then even what she learned when she interviewed, you know, everybody on, my leadership team.

[00:17:11] And then she, of course, also worked very closely with our legal ops team. And so that was really the core team that was responsible for developing some straw man solutions as we were thinking about, you know, what our challenges were. We couldn’t do everything, and so we said, “We don’t wanna attack 10 problems at once. We don’t wanna try to adopt 10 platforms at once. We really wanna think about what’s our highest value work that we think can be impacted by artificial intelligence and the technology platforms that we see.” 

[00:17:41] So that’s what I asked all the center of excellence leaders to say, “Bring me your best case that you think can be impacted by artificial intelligence, and then together we talked through those to say, “Okay, these one or two or three, these are the things that we should really be going after.” You know, some orgs were already using it. Of course, you know, e-discovery for a long time has been using artificial intelligence, and that’s continued to evolve, so that was not our focus. We were like, “Let’s focus on some new opportunities.” 

[00:18:08] And then, of course, you need to have somebody that’s driving it, and so the tone from the top for me is really important. But you also wanna have somebody that’s holding everyone accountable and, and driving, continued discussion and decision-making. And for that, I assigned my, chief of staff, because she was very interested in the topic. And, of course, you know, she had access to my calendar and, and everything that I was working on. 

[00:18:34] Irene Liu: Yeah. 

[00:18:34] April Miller Boise: And she had the enterprise-wide view because she, you know, works with all the other chiefs of staff across the leadership team, and she could really bring that perspective- 

[00:18:42] Irene Liu: Yeah

[00:18:42] April Miller Boise: to my team. And so that was great. 

[00:18:45] The other thing we did, Irene, is we decided to do these AI sprints. And the reason we did that is, and I’ll talk a little bit more about what the sprints were. We had, you know, maybe like two years ago, you know, any time we would have a big town hall or a big legal summit, we would have an outside speaker that would come and talk to the team about artificial intelligence and, you know, what that looks like.

[00:19:09] And so, one of our speakers was a guy named Cliff Worley, and he does a lot of speaking on artificial intelligence. Kind of he was an early adopter, but he also writes a newsletter that was called, I think it was AI Cliff Notes. But one of the things he said to the team is, everyone should be playing with artificial intelligence, you know, just two hours a week. Just set a, set aside two hours a week on your calendar and go out and try some of these technology platforms. 

[00:19:36] So imagine, this is, like, two years ago, 18 months ago. It sounds really good. People are like, “Yeah, that’s a great idea. I’m gonna put it on my calendar.” But what we found is people who are leaning into innovation and technology, they’re gonna follow through. They’re gonna do it every week. They’re testing the different apps. They’re gonna come back with ideas. 

[00:19:53] But the rest of the org, who are, you know, kind of naysayers or in denial or, like, “This doesn’t really apply to me,” they actually never really did that They maybe put it on their calendar, but they got busy and said like, “Oh, you know, everybody’s busy. We’re going through a huge transformation. I have too much on my plate. I don’t have time for that.” 

[00:20:11] So what we what we decided to do about 12 months ago is we started doing, maybe a little bit less than 12 months ago, we started doing these AI sprints. And the whole idea there was just what it sounds like. It’s a sprint, right? So, every Friday, 15 minutes, we’d get on the line, everybody in the department is welcome, and we would talk about, it’s open agenda. 15 minutes sounds like it’s not long enough, but it’s perfect because even if people are busy, they’re like, “I can probably do 15 minutes.” 

[00:20:39] And people, it’s an open conversation. And Melissa, you know, my chief of staff would drive it, talking about like what did people learn this week? What did you try? You know, did you fail? What new applications came out? What’s going on in the news? What are we hearing about Harvey? What’s Anthropic’s new plugin look like? You know, who’s using Claude? Do we have permission to use Claude yet? You know, what does our Claude version look like? But it really was a way to keep it top of mind every week for everyone, and they could really see what their peers were doing. 

[00:21:08] And what we found is that other corporate functions throughout the company wanted to join our call. So, you would have like HR saying like, “Oh, we wanna join,” or you know, some people from finance or some people from procurement joining. So, it really was a best practice, and we would have, you know, upwards of, you know, 130, 200 people on that call- 

[00:21:26] Irene Liu: Wow 

[00:21:26] April Miller Boise: … every Friday. Yeah. just to kind of hear the latest and get motivated about adopting AI.

[00:21:32] Irene Liu: Was it also a show not tell session where people were also showing how they’re using it? Because oftentimes, especially with AI moving so fast, people just wanna see what are the buttons you’re pushing, how are you, what are you prompting. Were those part of- 

[00:21:45] April Miller Boise: Yes 

[00:21:45] Irene Liu: … the sprints as well too? 

[00:21:47] April Miller Boise: There was a lot of that, and then what we end; so, every, every Friday was different. 

[00:21:51] Irene Liu: Right 

[00:21:51] April Miller Boise: Again, it was kind of an open agenda And, you know, maybe Melissa would bring a specific example that somebody wanted to talk about, and she wanted to do kind of a show and tell. But be, out of that sprint, we also decided, and out of the work our consultant did, we also decided to do some training- 

[00:22:06] Irene Liu: Yeah 

[00:22:06] April Miller Boise: …sessions for our entire org if they were interested. So, some people did eight hours of training. Some people did, like, six eight-hour sessions or six four-hour sessions, and then some people did, like, 60 hours of, of AI training. 

[00:22:19] And it was a lot of the, the exactly what you would think people would be interested in. Like, how does this tool work? How do I set up an agent? How do I use Copilot? What are people using it for? And really, like, what’s a good prompt? This is when people really didn’t understand the importance of the prompt, right? Again, they were using it like search, and they would just ask a question. They really learned about the importance of having really good prompts. 

[00:22:43] Irene Liu: Yeah. 

[00:22:43] April Miller Boise: And so, we offered that training, and we had significant uptake in that, in that training participation. And again, you could do from eight hours to 60 hours, and people adopted, you know, whatever they thought was most important and most helpful for them in their practice.

[00:22:58] Irene Liu: And were there custom trainings that were for eight hours to sixty hours? ‘Cause that’s a huge range, so is it different types of courses- 

[00:23:06] April Miller Boise: Yes 

[00:23:06] Irene Liu: … that they’re taking outside? 

[00:23:08] April Miller Boise: Yes. There were. We worked with an outside vendor, and we specifically created. We worked with a vendor, the vendor already has content that they are providing to mostly corporate functions, a lot of legal, but not just legal about how to use artificial intelligence. 

[00:23:26] And so, some of it is specific to a particular platform, some of it is specific to prompting, some of it was specific to Copilot. We did a number of sessions with Microsoft, this is when Copilot first came out and, you know, we had test users of that, and people were like, “What is this whole new Copilot thing?” 

[00:23:42] And so, the training was done by outside experts, and it was very focused. And so, people knew, like, if you’re doing the six-hour training, it’s gonna cover this at a very high level. Or if you’re doing the, you know, four-day, six-hour training, here’s your agenda. And people could- 

[00:23:59] Irene Liu: Yeah 

[00:23:59] April Miller Boise: … opt into that. But people who did the longer training, we said, “You know, we, here’s what you’re getting yourselves into. We really want you to opt in to do the entire, you know, week or hours of training.”

[00:24:09] Irene Liu: Yeah. 

[00:24:09] April Miller Boise: Because we’re paying for those spaces, and we wanna make sure that we’re getting the value out of that. And I think people really got a lot of value out of it, and those are some of our, best users of artificial intelligence. 

[00:24:21] Irene Liu: Yeah. And going into that consultant study that you did, I mean, it seemed like it was a very thorough study in a sense that you studied not only legal departments, but vendors, and also within your team.

[00:24:32] What are some of the key learnings that you found from that study that you think other CLOs and other legal departments will find interesting? And what were some of the takeaways for you in addition to, like, doing certain sprints, for example, to educate the team? What were some takeaways that you implemented from those learnings?

[00:24:50] April Miller Boise: Yeah. So, I think some of the things we learned are, you know, number one, there are so many legal tech companies out there. If you go to these conferences, the hallways just lined with vendors with their tables set up. So, there are a lot of vendors that are, you know, that are working on these potential solutions, and not all of them are going to be successful, and they won’t all survive. 

[00:25:10] So a big part of it was really understanding the vendor- and their underlying technology stack, and whether or not we thought they were gonna be around. Because we didn’t wanna invest a lot of time and resources in learning a partic- a particular vendor solution if we thought it’s a very small company, they’re not likely to be here for the long term. So that was really important. 

[00:25:30] We also learned a lot about the underlying large language models, and, like, who was using what model, and did we think, the tool was better because of the model, or was the tool simply better and we wanted to change the model than it, it relied on. 

[00:25:46] The other thing that really im- that we really did as a result of talking to all these different resources is, we said it’s incredibly important, and I talked about this early on, that we map our work.

[00:25:59] And so, if you think about, like, an M&A project, right? If you are, you know, you’re gonna maybe acquire a company. You hear about the auction. The company is for sale. They’re gonna set up a data room. They’re gonna have a management presentation. All the steps that are involved in that, it was really important to think about what are all of those steps, who does what, and where are you trying to get at the end of the day, right? 

[00:26:20] And so, one of the things, for example, is, you know, any time there’s a, a merger and acquisition, you’re gonna have this back and forth of the drafting of, the purchase agreement. rounds and rounds and rounds, potentially, you know, multiple rounds of drafts and comments, and somebody’s creating an issues list or a table, and what did they say last time, and what’s our fallback position?

[00:26:40] And so what we said is, okay, we wanna do a deal. We need an agreement, and at the end of the day, we want an agreement that we can sign. There’s a whole bunch of work that happens in the middle. How do we map that work, and how do we try to eliminate as much of that work as we can to make us more efficient? And what are the ways that we can use artificial intelligence to eliminate some of those steps? 

[00:27:01] So the, having every organization, every part of my team really, you know, do a process map of the steps that they take in their work, I think was really, really helpful in thinking about, okay, you know, how should we use the tool then? We don’t wanna use the tool just for every single step. We wanna try to eliminate some of the steps because the tools are really effective at helping us do that. 

[00:27:23] Irene Liu: Yeah. No, definitely. And so, in addition to mapping, though, what were some takeaways that you had from learning from others? So internally, you learned what the other- 

[00:27:31] April Miller Boise: Yeah

[00:27:31] Irene Liu: …teams are doing and how you can leverage AI, and mapping is such a critical skill, especially when everyone’s sprinting. It’s sort of a time to pause and reflect and figure out what are the steps and what are the drudgery, what are the areas that where you can leverage AI. But I’m sure when you also surveyed other teams, there are probably some learnings about how they’re leaning into AI in different ways.

[00:27:53] April Miller Boise: Yeah. 

[00:27:53] Irene Liu: Were there any surprising findings, or did you feel like everyone sort of still figuring it out as they go? Which I think is somewhat the sense of today, but were any others leaning in in a different way that you said, “Ah-ha, I really wanna try that too”? 

[00:28:09] April Miller Boise: I think it really varied a lot. Across the types of organizations that we talked to, people were leaning in and using the tools in very different ways.

[00:28:19] So, some of them thought, like, you know, I’m leaning in mostly in commercial contracts because I have hundreds of thousands of contracts, and that’s the place where I’m gonna get the most value. For financial services, there was a lot of, like, leaning in because of, you know, regulatory- privacy issues in Europe, GDPR, and really, like, all of these customers and, you know, needing to trace all these transactions, and so they were leaning in in a different way.

[00:28:44] For me, one of the most important takeaways, and it was an ah-ha, but it was something that I already knew, and I, I had started this work at the organization that I was at even before Intel, this idea that what you really need in an effective legal organization or, you know, corporate department, particularly legal, though, you need more non-lawyers.

[00:29:06] Like, there’s a lot of important work that can be done by people who are not lawyers, so the data scientists, the knowledge management team, like, people who are really helping you think about what’s the work that the organization is doing? What’s the information that we have? How do we extract that information? How can we do our work better? 

[00:29:25] So I think the legal department of the future is going to have a lot more professionals who are not lawyers. There’s still a very important place for lawyers, but a lot of the work that we do is not necessarily legal. It’s, it’s high-value work. It’s developing business solutions, but you don’t need to be a lawyer to do that.

[00:29:44] And so, I think, and I saw this, again, particularly from the technology companies, like Intuit was a great resource. We talked to Google. They were a great resource. And JPM, they have; they’re really looking at having more data scientists as a part of their team, so some, you know, not everybody is gonna hire the people internally. They’re hiring a consulting firm or a firm who has the data scientists on board, but some of them who have the data scientists and can consult with them, but many of the organizations were saying, like, “No, we hired X number of data scientists, and they’re gonna help us really better understand our work.”

[00:30:21] And I I saw today, I’m trying to remember what the org was, but a couple of organizations are working very closely with Anthropic and OpenAI to forward deploy to them a whole bunch of data scientists who can come to their organization and really better understand the work of the corporate function so that they can develop AI tools to help us better do our work. 

[00:30:44] And I think we’re gonna continue to see that. I think that’s the big game changer with AI, is really remapping the work that we do and having platforms and tools that really understand that and can help us. So, I think, again, the, the legal department of the future It’s gonna have more non-lawyers that are helping us do our work more efficiently.

[00:31:04] Irene Liu: Yeah. In the legal department of the future, I think even the existing roles will shift a bit. So, when I think about legal operations, for example, I think it’ll become more legal engineering, because- 

[00:31:13] April Miller Boise: Yes 

[00:31:14] Irene Liu: … of a lot of the work, not only in current day-to-day that they’re managing, but they’re going to be trying to figure out how to transform the legal function with AI, implement it across, and really work cross-functionally to make sure those tools work. So, it’s somewhat in existence today, but it’ll require a deeper skill set, and so it’ll be interesting to see how those functions evolve as well, too. 

[00:31:38] April Miller Boise: Yeah. And, and to your point, Irene, I think it’s gonna require a lot more integration across the corporate functions, right? So, finance, HR, procurement- IT, like integrated supply chain. You’re just gonna see much more, I hope, collaboration across those organizations- 

[00:31:58] Irene Liu: Yeah 

[00:31:58] April Miller Boise: … and thinking about, again, what are we trying to solve for? 

[00:32:01] Irene Liu: Yeah. 

[00:32:01] April Miller Boise: Where does that work sit? And, you know, how do we streamline that work. Instead of having it bounce from this org to that org to that org, like, let’s create a process that just makes it, much more efficient. 

[00:32:12] Irene Liu: So, April, with the large size of the team and the amount of legal work that you produce, I’m sure you partner a lot with legal law firms. And I’m sure you’ve also had conversations with law firms. What are those conversations that you were having, and were you holding any types of summits with law firms?

[00:32:29] Because I’ve heard some of these larger legal departments have been holding summits with outside law firms to tell them how they wanna partner with them on AI and also talk about pricing as well. I mean, I think that’s been a critical discussion for a lot of law firms, especially with the advent of gen AI.

[00:32:45] April Miller Boise: Yeah, a, absolutely. I mean, number one, our relationships with our best law firms are really important and, you know, we really partner very closely with them, and we expect them to be an extension of the work that we do internally, or we wouldn’t hire them. I do think there is a fundamental shift in the legal industry going on, and I think the best law firms are trying to stay ahead of it and really doing their own diligence and their own investing in artificial intelligence and trying to determine what’s the best model for them.

[00:33:15] But I know what can’t happen, and I have seen this with some law firms, and so we have been very clear with the firms we work with, is some law firms, and this has changed probably in the last six months, but you had firms that were, for example, just adopting Harvey, and then wanting to pass on the subscription price to their corporate customers without really changing their billing practices, and that can’t happen. I mean, legal departments, smart CLOs are not just gonna say, “Charge me the same billable rates and the same number of hours, and then also charge me for the AI for the technology.” 

[00:33:46] I think fundamentally our relationships with law firms will change. I think, again, the smartest law firms are really thinking about how do they lean into AI and how do they adopt it in a way that positions them to add more value for each project with a shorter amount of people hours that go into it.

[00:34:04] ‘Cause what we really wanna pay for is not hours. You know, we wanna pay for results, and we are hiring our firms, again, as an extension of the work that we do. And our, you know, our total cost of our function needs to go down every year, and even more so now with- artificial intelligence.

[00:34:21] There are expectations that corporate functions are gonna continue to cost less and less and less. So, we can’t just have law firms charging us their normal billable rates and then charging us for the tech stack on top of that. 

[00:34:33] Irene Liu: And did you find them receptive to those conversations? Were they being more creative? Do you see any changes or shifts? 

[00:34:40] April Miller Boise: I think the best firms are absolutely receptive, but they’re also proactive. And so, there are a number of firms that I talk to that I think have demonstrated best practices. So, you know, Cleary Gottlieb, they’ve done a lot of investing, and I, I really like their motto. Gibson Dunn has long been really focused on this. Cooley has also invested a lot in AI and ensuring that, you know, their lawyers are going to be more effective in understanding artificial intelligence and how they deploy that. And then, you know, K&E I, I, I don’t use them, but I’ve, I’ve read in the news, and I haven’t talked to them directly, but I think their motto is really interesting.

[00:35:18] You know, they said, “We’re gonna invest $500 million to build our own legal technology platform.” So, I think that’s gonna be really interesting. Of course, you know, they’re competing against AI companies that are spending billions of dollars. So, I, I’m not sure exactly what that $500 million is gonna be invested in. I think it’s over several years. But I think they’re really gonna be looking at, how do we get a return on investment for this $500 million, and what are the things we’re not gonna invest in to have our own technology stack? So, I think it’s TBD on that. 

[00:35:48] But again, I think the best law firms are really thinking about it and being proactive and, you can’t just sit around and think like, “Oh, this doesn’t impact us,” or “My business model’s gonna be the same, I’ll just adopt the technology and pass on the cost.” 

[00:36:03] Irene Liu: Yeah, no, that’s really helpful. I, and it is interesting to see that the the proactive law firms are leaning in. They really do care, and they’re trying to figure out what’s best for their clients as well. But this is definitely a time, a moment for them to also rethink their models too- Absolutely

[00:36:18] in many ways. Yeah. So April, so in, when you’re looking at, given all the studies and all the work that you’ve done, if there’s a new CLO starting at a new job during this time and they’re going through a corporate transformation and an AI transformation at the same time, what are the three things you would tell them to do?

[00:36:35] April Miller Boise: Yeah, so I, I mean, I think we’re a, we’re always going through transformation, and I like to say, you know, I run into burning buildings for a living. You know, I, I put out fires, and I, you know, shepherd, help shepherd companies through significant transformation. I think that really is my calling card, and that’s where I’ve spent a lot of time, in corporate transformations. 

[00:36:54] And so it’s, this is not new. It’s a different type of transformation, certainly. I think the first thing you need to do, though, is you need to be aligned with the leadership team, your CEO, your board, on, like, what is our strategy? Like, what is it that we’re trying to do? And let’s get everyone on the same page there. So, knowing the strategy is number one. 

[00:37:14] I think the second part is getting your team, the right team, in place. So, who’s on your leadership team? Do you have the right leaders in place? Are they aligned with the kind of culture, that you need to have in your organization to execute on the strategy that you’ve set with the leadership team?

[00:37:31] If not, you know, you’ve gotta make some changes in that leadership team. you need to make sure you know people across the organization, kind of up and down. There may be junior people that you wanna elevate, et cetera. And then I think the last thing that’s probably the most important after you get those two things in place is you have to make sure your team is doing the right work.

[00:37:49] Irene Liu: Yeah. 

[00:37:50] April Miller Boise: And so, you can have hundreds of people across the globe doing really interesting, strategic, and important work, but if it’s not aligned very directly with the strategy on the page, it doesn’t really matter how good they are on executing on those, you know, day-to-day projects that they’re working on, because it’s not driving the strategy.

[00:38:10] And so, that was one of the things that I spent a lot of time talking about, is just making sure the entire team understands the strategy and understands their role in driving that strategy every day. 

[00:38:22] And if you’re doing things that, you know, maybe are important to a client who’s coming into your office every day with their hair on fire, and they really want you to work on this project, if it doesn’t clearly draw a line back to the strategy- 

[00:38:35] Irene Liu: Yeah

[00:38:36] April Miller Boise: …you have to say, “My hair can’t be on fire for this, because this is not a priority.” So, getting that alignment is really important, ’cause you’re not gonna get more resources to do, you know, non-important work. So, gotta be aligned around what’s really important. 

[00:38:50] Irene Liu: You have to choose your fires. 

[00:38:52] April Miller Boise: Exactly right.

[00:38:53] Irene Liu: …in a way, a, as well. so, April, one of the other things that you mentioned, I think you said obviously get the strategy right. But I also loved how you said, and, and I think that’s part of setting the tone at the top, focusing on the strategy, setting the right tone, and then tactically really mapping out as well where you can add value and where you can use AI to add value. And then the third- 

[00:39:16] April Miller Boise: Correct 

[00:39:17] Irene Liu: … thing, to do these sprints to really share knowledge with one another, I think are, are really significant and helpful tips, especially to new CLOs too. 

[00:39:25] So April, thank you so much for sharing all these insights. I love them. I, I know if I were a new CLO, I would take away so much from this conversation, so I’m so grateful that you were here. Thank you for sharing your Intel journey and your strategy on a page. I felt like this was a strategy on a page session of AI transformation within a legal team. So, thank you for sharing that S.O.A.P. with us. 

[00:39:49] April Miller Boise: So great to talk with you, Irene. I really appreciate the work that you’re doing personally, and the work that’s going on at Stanford. This is obviously a very fast evolving story. You know, there’s something new with generative AI and agentic AI every day, and how we can use it in our business. So, I appreciate the opportunity to have the conversation. 

[00:40:07] Irene Liu: Thank you. 

[00:40:07] April Miller Boise: Good to see you.

[00:40:12] Irene Liu: Special thanks to April Miller Boise for joining us and being so generous with her stories and lessons learned. And thank you for tuning in to the AI Sidebar. If today’s episode taught you something new, please share it with someone who’d benefit from it. And don’t forget to subscribe so you never miss an episode. Keep learning, stay curious, and we’ll see you next time