Worried that the AI bots are going to make lawyers obsolete? In-house tech lawyers and AI-thought leader Laura Jeffords Greenberg is in The Legal Department this week to help alleviate those big feelings. She shares practical AI use cases for in-house legal departments, offers advice for how to approach this new (and sometimes scary technology) and shares tips for scoping AI solutions. If you’ve been sitting on the sidelines waiting for an invite to an AI in-house party, this episode is for you.

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Listen to the podcast here

 

AI for the Legal Department: Laura Jeffords Greenberg, Senior Legal Director Worksome and Legal AI Consultant

A Tech Lawyer And Lover Of AI

My name is Laura Jeffords Greenberg. I’m an in-house counsel and an AI legal consultant. A fun fact about me is that I am pursuing Croatian citizenship, so I might become a dual citizen pretty soon.

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I’m excited to welcome Laura Jeffords Greenberg. She’s in-house counsel and provides consulting to in-house legal teams about AI, and we are going to delve into a lot of topics related to AI and legal. As we were starting our conversation, I told Laura I’m a technophobe, and she is a self-described tech lawyer and lover of AI. I’m excited for us to exchange ideas. Hi Laura, how are you?

Thanks for having me. I appreciate it.

I want to know if this is the second or third conversation I have had with somebody in Europe, and so we are grappling with the pretty broad time gap or time zone change. I appreciate you being here.

We are in a good window here because we fell back, so we are a little bit closer.

The falling back and the different time zones are a real brain-bender. Enough about that. Let’s dive in. I want to give a little bit about your background and how you came to become ingrained in the AI for legal situations.

I have been in-house most of my career. I started out practicing law in California. I started as a sports lawyer and then through a couple of different changes, became a tech lawyer. I love working with engineering and development teams on cutting-edge technology, and I’d worked on VR, I’d worked on cryptocurrency, and also was starting to work on AI and machine learning but before it became, let’s say, consumer-grade, before ChatGPT. I loved that, but there was nothing that was going to help me do my job better as a legal professional.

 When ChatGPT came out, I was like, “This is the technology that is going to help the legal profession.” It’s a large language model trained on language, which is what we do all day, and using natural language processing, so we don’t need to know how to code. We can simply interact with the software on how we would speak with someone. I dove all in. I was so excited about it and wanted to figure out how we could use it for legal.

There’s a lot happening now. I’m sure you have this experience, also being an in-house lawyer, a lot of vendors are pitching. There’s a lot of noise around what’s available, how you can scale your team, you can be faster, and more efficient. It’s intimidating and difficult to sift through all that. You did a LinkedIn post about reactions around AI. Before we get into the blocking and tackling of technology and what it can do for legal, I thought it would be good to hit some of those emotions head-on.

I’m going to sample a couple that hit me feeling like you’re cheating. I had some conversations with a friend who used it to write a wedding speech, which I felt hit me in a certain way, overwhelmed with the pace of developments and worried about whether I was going to have a job. You said natural language. That’s what we do and now there’s a machine that can do that for us. The one thing that sticks with me is the impact on new learners or junior lawyers who haven’t had the analog learning experience. Help us think through those emotions and reactions to AI.

It’s very interesting. Every time I do this with a group, I always learn something new, and there’s a new twist or a new take. The rooms are always very diverse as well. We have the, “I’m a champion, and I love it.” There’s always one superuser and then someone who maybe has never even opened any generative AI tools. That’s the first observation when you are looking at legal teams. It’s usually pretty diverse, and we need to acknowledge all of those emotions because those emotions are preventing us from using these technologies.

We need to acknowledge the emotions surrounding AI because those emotions can prevent us from using these technologies effectively. Share on X

That’s what I have seen the most with lawyers. People, young lawyers like you mentioned, who feel like they are cheating or feel like they are not going to learn properly if they are going to use these tools. Those are real fears. How do we address those? If you are working with teams, whether it’s law firms or in-house teams, you need to address the fears that people have, even if you don’t have a good answer. Put something in place or work with them to say, “How can we solve this? We probably should explore using these tools because they do help your job, but where do we need to, then, help let’s say the younger attorneys learn? We can’t give them the AI tools and walk away. What are we going to do to help supplement their learning?”

 

Lawyers are probably uniquely positioned to have that skepticism, as you said, some of the apprehension to respect the tools. We have gotten to be a very comfortable society where everything is on the phone. We don’t need to think about street names. We follow the blue line, and it’s that tension, as you are describing, between the superuser and the novice or the skeptic, which is probably healthy.

I think so, because, like you mentioned, we moved to Denmark, and I don’t know any street names. I’m not paying attention. Like you said I’m just following the directions and not paying attention to street names. I have lost that. It took me a very long time to finally memorize my husband’s phone number because I didn’t need to. I’m going to take that over to AI.  I’m going to, maybe, lose some writing skills.
Am I going to lose the ability to quickly respond to something or quickly think through something because I’m outsourcing it? There are some things that we can outsource to AI, but we do have to be careful about what we are going to lose because we have lost some things from using technology like maps or memorizing people’s phone numbers.

We can outsource to AI, but we must be careful about what we lose in the process. We've already lost certain abilities by relying on technology, like navigating with maps or memorizing phone numbers. Share on X

You can even be out to dinner, and somebody says, “What was the name of that movie?” Instead of throwing around ideas or whatever, it’s like you grab Google and it tells you what you need to know. In addition to those, you had a nice long list. I highlighted the ones that hit me. I worry about a lack of critical thinking, as you said, and also the loss of creativity that I’m going to ask the bot and it’s going to tell me what I should be, it’s going to give me the ideas.

That is true. A great use case for AI is brainstorming or providing counterarguments to something. I’m torn there. You can come up with some of your ideas, but so far, when I have used AI, it’s been supplementing or coming up with ideas that maybe I didn’t come up with. In one sense, it’s expanding my creativity, but then if I become over-reliant on it, it could erode my skill because I do believe that creativity is a skill.

It is a skill. I’m glad we agree on that. That’s self-regulation we have got to work on too, not becoming too dependent on it but using it as a tool.

I can see myself as I mentioned earlier, I have both ChatGPT and Claude on my phone.

Your friends are there. They are available.

I can use it all the time. Let’s not become overly reliant on the tools.

Let’s move past the big feelings. Let me give this little glimpse. I said I’m a technophobe, and I’m a late adopter. I would say I have been more open to learning about technology with AI than I have with other tech. Before, I have been, “I will use it,” or, “I will wait until I have to use it.” I was at a very large employer. We had 28,000 employees, and I was 1 of the last 2 to shift from Blackberry to iPhone. I still miss my keyboard. I still do.

There’s a support group. I’m sure of that.

Examples Of Use Cases

Moving past the anxiety. Let us talk. I know you do a lot of speaking on this, but giving us a couple of examples of different use cases that could benefit in-house departments. The promise of what this can do for us might help us deal with our anxieties.

There are different tools. We have general tools like ChatGPT, Anthropic’s Claude, or Google Gemini, and then we also have a variety of legal-specific tools. First, it’s important to know what technology you are using and then what problems you are solving. If you want to start with the very general, basic chat tools, it’s great, as we mentioned before, for drafting emails, policies, or responses. You can ask it to draft certain parts of a contract. At this point, I wouldn’t ask those tools to draft a full contract unless you had a very long prompt explaining everything you needed. Using it for editing and manipulating text, that’s a great place to start if you haven’t started before.

If we go over to the other end of the spectrum, we can look at what people are referring to as AI agents. That’s where you are looking at the AI performing tasks for you and manipulating the software on your computer. An example of that, like a precursor that is easy for people to understand, is building a GPT. We have ChatGPT, and within ChatGPT, you can build your custom version of ChatGPT and feed it knowledge. You can upload documents and give them custom instructions.

Talk more about specifically how we would do this. This feels like a 2.0 for me.

We move over to what we can do. The example that I like to use because it’s interesting and very easy to understand is a GPT called “Naming Your Baby in Denmark.” Both my husband and I are American, and I had one of my children here. For those who don’t know, in Denmark, there’s a list of government-approved baby names. If you want to name your child the name that is not on the list, then you have to go through this whole process. I also don’t speak Danish well, so I had to figure out how to name our son something that wasn’t on the list. I went back afterward and made a GPT for that. That’s the example that I will use.

What do you first have to do? You need to go check the list. Is the name you want on the list? Great. If it is, no problem but if it’s not, then what do you do? You need to check the naming laws. What are the rules around the names? Will your name be approved? It has to be within the regulations.

Did you upload the regulations, or did your GPT already have the Danish naming regs?

What I did is I went and got the list. I uploaded the list to it. I also included hyperlinks because it’s a website, and then I summarized the naming laws or you could also upload them or provide a link to them. You’ve got the list and the laws. Gender is important in this exercise so you need to get information from the user about the gender because that impacts the name. Then I wrote a legal memo to the court arguing for my name use so then I turned that into a template and uploaded that.

Now, we have to check the name list. We got the name laws that are checked. You need to know what gender, and then use the template memo and then I made custom instructions for it as well. I had about a page or page and a half of instructions telling the GPT to first check the name list, then check the name against the laws, and then double-check the gender with the name. Then here’s the template. Please pre-populate this template and generate that for the user, and provide additional instructions about how the user, if they are not Danish, can get additional information from their home country to use as supporting evidence in the brief. I provide instructions on where to submit this based on location in Denmark. All of that is uploaded into the GPT. You go in, and it directs you through it. Ask questions and at the end of it, you get a template you can use and know where to send it.

You made the GPT into an associate.

I like this example because you have to go and check different things. It’s a very multi-step process that’s easy for everyone to understand and it’s not complex. They are doing the same thing every time.

It’s structured. If I had to zoom out using it to automate a process that has a lot of steps that are clear standards, and can be replicated or is a frequent request.

We all have that manual work that we don’t need to be doing, especially checking resources or going back and trying to find documents. I have also created “Plain English for Lawyers” GPT where I have uploaded my writing instructions and some other information. It’s, “Please correct any text you put in there and rewrite it in plain English.” There are all sorts of different fun things you can do.

What Are Some Typical Use Cases?

I know you do a lot of speaking and consulting with in-house legal departments. What are some typical use cases? Are there any typical use cases you are seeing that this technology can support?

It depends on the team and what tool they are using. There’s a big difference between using what I would call consumer ChatGPT versus having your IT team use the API and building your own in-house ChatGPT that has access to your files and the appropriate security and confidentiality measures or if you are using CoPilot. CoPilot has access to all of your Microsoft Suite products.

We are seeing a lot of text editing. I’m working a lot with policies and recording meetings. There are more complex use cases, options, and software out there. For example, different teams have also built their own with Zapier and ChatGPT. Some of these ideas, if you are working in Slack and someone asks a question in Slack, then you have an AI in the background that goes and gets the specific documents, looks at it, and generates a response for that employee immediately, or you can do that all via email. A lot of teams are starting first with policies, as we don’t have to be as precise if employees are asking questions.

That’s a long-tail project. Updating a policy isn’t something that somebody is expecting the next day. There can be a time for a pause for the human in the loop to double-check the AI work.

Teams have also gotten it to places where they pre-approved answers and they are training it and then they feel, “We have gotten it to a place that we’ve trained it enough, and we pre-approved enough answers,” that they let it go, and check on it every once and a while. I’ve seen almost all autonomous AI agents working in the policy space. Law firms are trying to figure out how to incorporate it for each of their departments, which have different processes and procedures.

I wonder about this being disruptive for law firms, and I have talked to a few law firm partners who’ve said, “We have difficulty finding the right work for our junior associates to train on because, for example, one national firm was telling me, “We use AI for diligence now.” You spent time going through bankers’ boxes. You train folks and they bill out at high billable rates these days. What are we paying for and how are we going to train them?

That’s some questions being a client of law firms, as in-house counsel. You are now starting to wonder, and we have had this conversation. Let’s say I need an employment agreement in a country that I’m not familiar with that is authorized to practice law. I go outside counsel. Do I give outside counsel a ChatGPT-generated contract to review, or do I let them use one of their templates? I’m now starting to think about, “How much am I paying for something that’s a template?” Their customers are starting to think about, “Are you using AI? Could you be more efficient? What am I paying for if I could almost get something good enough from these AIs?”

This is similar to what we talked about before about how I’m in healthcare, and we are exploring all different ways to use AI there. What I noticed is that as you explore these technologies, it pulls back the curtain on what our existing workflows are. I’m sure I’m confident those law firms are using their current templates that were developed for years and years. It doesn’t take them that long to pull up the template plug in your name and do a couple of tweaks. Now, that work is quick, and we are more aware that it can be done quickly. There was a mystery. We didn’t know how long it took you to find the template or whatever. One of the unexpected results of this technology is that we are learning more about how people do their work.

You are thinking more about how your law firm is working with practicing. What are they doing? What exactly am I paying for?

We have a lot of contracts at my company, and we use an outside firm for part of a type of technical contract. They were very upfront and because we had to do amendments for a number of them they said, “Is it okay with you if we use AI to expedite this?” We thought, “That’s great. How much are you going to charge us?” They said, “We are not going to charge you to do that.” I thought that was amazing.

That’s the problem with the billable hour if we’re making processes more efficient and optimizing them. That’s not great for the economic model of a law firm.

How Do We Evaluate These Tools?

It’s not great. We will get into a little bit more in-depth about the ethical issues around charging but that is something that in-house lawyers are going to be much more attuned to exactly what I am paying for. We are talking about the big AI solutions, but there’s also a lot of AI tech that’s built into a number of tech solutions. I wondered if you had some advice for lawyers. We are getting pitched all the time for this tool and that tool. “It’s going to change the world.” “Magic wand.” How do we sift through the noise? Are there resources? How can we best evaluate these tools that are coming across our desks?

That’s a great question because I tend to divide tools, and like you said, the general tools of, let’s say, chats, and then having your software that has an AI add-on onto it. What exactly is that AI add-on doing? One of the first questions that I’m always interested in, and you can get some more information about, is, “What models are you building on top of? Are you building on top of OpenAI? Anthropic? What model are you building on top of?” That will give you some information about their understanding.

That’s a question for the vendor. What model are they building from?

Which model are they using and are they switching out models depending on the task? Starting there gives me a baseline understanding of who I am talking to. How much do they know, and then how sophisticated is their tool? There are some products out there that have simply what we call a wrapper to slap something on top of ChatGPT, and then now it’s a product. You are using ChatGPT as a feature in their product.

Are there IP issues with that?

You are using it through their API and licensing it from them.

Do they have the right to use whatever is in ChatGPT, or because it’s open source?

They are licensing it and charging them for the usage, which they’re passing on to you. That is an interesting indication of what is going on here and how sophisticated this product is. I would always ask, “What is the problem that you are trying to solve? What is this AI trying to solve? Is it some fancy bells and whistles, or why is this making my experience of using your software better? How is this making my life as a user easier? Why would I want to use this?” We use Notion at my job, and that’s a knowledge management system, and they have AI built into it. And it works pretty well, but you have to pay for it, but their AI buttons are all over, teasing me all the time. That’s the one where I did a beta and you could try it. The other thing is to try it.

Try before you buy.

That’s the one where I was like, “I can see the value of this. If our company’s entire knowledge management is in this software and AI is able to search all of our documents in the little chat window and answer them pretty accurately, that’s something that is hugely valuable because it’s someone not having to go and find the page and read it.” It’s taking a lot of time and having AI built into your knowledge management system is a huge benefit and going to save a bunch of time, especially for the legal and compliance team.

From that standpoint, could it be used to do a first cut on discovery responses, for example?

I’m not involved in litigation anymore, but there are AI tools out there that will take large documents and give initial reports or whatever it is that you are looking for.

The transactional stuff unless you are doing a big deal like that’s not a big burn on the legal budget but especially discovery or e-discovery, all that is a huge burn of your budget. That’s something I’d probably want to learn a little bit more about if there’s anything or any tools that we can use to force the law firms to use.

That’s a great use case for AI. If you are looking at tools, maybe get someone from your IT team to also understand what it is that they are doing, or someone who’s a superuser who’s interested and excited to ask those additional questions about how it works, how they are using the AI, and if you are going through a large volume of documents. There are very different methods that you can use that we don’t need to get into and some work better than others.

“Try before you buy” is a good takeaway. Are there any tools outside of the chat tools that you think are must-haves or tools that we should prioritize for in-house departments?

It depends. Your tech stack, processes, and your problems. Everyone wants to be like, “There’s one solution.” I don’t think that there is, because I have tried, let’s say, there’s LEA, who’s out of Stockholm, that is more geared toward European jurisdictions, not the United States, and it’s probably more of a tool than for in-house.

Out of Scotland, there’s Wordsmith which I love for in-house. It’s built for a tech lawyer who works for a tech company in-house because it has Slack, Notion, and G Suite integrations. It’s integrating into all the software I’m already using. Let’s say there’s an insurance company and you’re all Microsoft, you might be trying to figure out how to leverage and get the most out of CoPilot because you are already in the Microsoft ecosystem.

Regarding my observation about needing to learn the technology, do I understand that as in-house lawyers are exploring AI tools, they need to know what other tech is available and used by their company?

It’s where they are already working. Are you working at Google or Microsoft? What are you using the most you need to have an AI tool that integrates with that. Also if you want a customized ChatGPT experience but tailored for in-house teams, GC AI is great. It’s based in the US. It’s a great tool as well but that’s more general.

Do you have examples of what that tool does or can do?

Customized for in-house lawyers. You input all of your company information, which is great, so you don’t have to tell it.

No one could see my face, but I was like, “Ah.”

What’s your company name? What are your subsidiaries, and other company names? Where do you operate? What’s your industry? What’s your market cap? All of this background information is helpful to have the AI know in the background when answering questions for you, and then it’s also trained on legal data. It’s AI that has been created for in-house lawyers to help them do their jobs more efficiently.

I want to shift a little bit because, again, harking back to those big feelings that people have, the American Bar Association ABA grabbed onto these feelings and overlay them with our ethical obligations. These feelings are getting to our ethics our legal ethics. They issued a fifteen-page opinion on ethical AI use. There are a couple of areas that I thought we could explore with your expertise.

You practice in Denmark, but you have practiced in the United States, and I’m sure you are familiar with the model rules. Model Rule 1.1 is the duty of competence, and this part of the opinion explores a couple of things. One, we are supposed to be competent in technology. That’s in California, where I practice. There’s a requirement for CLE credit around competent use of technology. I can’t use my word processor anymore. My Blackberry is hung up.

Are There Any Resources For Where We Can Stay Up To Date?

No more WordPerfect. I did reference that in an episode. Also, there is an expectation that lawyers have substantive technical knowledge. I do feel like the opinion is telling folks that it’s a call to action to learn about AI. Are there any resources where people can stay up to date? You rattled off a couple of tools, but you do this every day. Are there any good resources for where we can stay up to date?

I would say the newsletter Brainiacs is good. That is geared towards the legal industry, and you get a newsletter about what’s going on to keep up to date. It includes both practical information on how to use these tools as well as substantive legal information, so it’s a nice mix. I’d say that’s probably the first place to start. Within those newsletters, there are other references as well.

One of the just general business uses of AI, I follow Allie K. Miller on LinkedIn, and she is about having an AI-first mindset and talks about all the different AI tools she’s using. When updates come out, she also speaks about those. Those are two good resources to get started.

I would also advise folks to follow you on LinkedIn because you are posting about this with real nuance and great questions. You even will show prompts, the way you’re prompting, and a lot of dynamic conversation occurs in the comments. I want to call out your thought leadership as well.

Thank you. If I have a question, then I try to figure out the answer. That’s my approach. If people have questions, they will ask me questions, and if I know the answer, I will share it with them and then turn it into a post. If I don’t know the answer, then I will also try to find the answer and turn it into a post. I welcome questions as well.

The next model rule in my opinion is Model Rule 1.4, and this is a rule that we know but is maybe not one of those that’s top of mind, and that is the duty to reasonably consult with the client about how you got to the result. This goes to the conversation about letting the clients know when you are using AI.

Part of me is I can’t spell. I use spell check, but I don’t tell people I’m using spell check, and everyone assumes that we’re using spell check. If you have misspellings, it’s like, “Why aren’t you using this technology to help you spell?” When do we get to that point with AI?

We might.  This conversation came up with ambient listening and AI transcription for medical visits. I’ve had this conversation a couple of times. I did a panel discussion at a conference. The question was, “There are human scribes now and they could be making mistakes.” There’s an issue with consent with having another human in the room. The difference is that it’s rare that you have a human scribe. It’s not all the time. Second, we know what a person is. “I know that Laura is in the room with me.” There can be a lack of awareness and if you don’t have transparency, that erodes trust. At this point in our evolution, it’s not ubiquitous yet in terms of everybody’s awareness. It’s not like the blue line on the map. It’s not Google. It feels scary. That’s my view. I agree. The spell check is a great example.

I do think trust is a big issue with this technology, but it’s also so new that we need to think about how we are using it. If someone’s using AI to help them write new emails, I don’t think you need to tell them that. However, if they are using AI in a way that is going to impact, let’s say, a fundamental write or impact something in the case that you are trying and you are not maybe validating it or relying on it too heavily. We are going to get into this gray zone where, if it’s going to injure your client in some way, then you probably should disclose that or talk to them about using it. You use it not to take a shortcut but to expedite something in a way that you might not be able to fully control in some way, then you are going to need to talk to your client about that.

 

Back on the medical side of things, in California, the governor signed a law that requires physicians and healthcare providers to indicate in their patient communications when it was generated by AI.

It can get things wrong. If the doctor is not reviewing or editing it afterward, that’s an example of if I use ChatGPT to draft a memo to the court and it gives me cases. As a responsible lawyer, I’m going to check that. I’m going to check myself.

Hopefully. There are some examples where folks haven’t done that, as we all know.

They are blindly sending it to the court. In the same example that you gave, you are going to want to know, “Did your doctor look at it before sending it to you, or did they blindly send you the AI output?” Those are two very different scenarios.

It depends on how you are using it. We already talked about the duty of delivering value and charging a fair price. This doesn’t come up in the in-house context, but for law firms, when we already covered that. Don’t bill me $800 an hour for all the time you’re dealing with the AI.

In-house teams are also facing pressure to not hire additional headcount and figure out how to use technology to solve some of their problems. As we mentioned before, this also goes back to AI not being able to solve everything. If you don’t have great processes and procedures in place already, or if you have some other underlying issues, throwing AI on top of that isn’t going to fix or solve that problem. There’s an interesting dynamic for in-house teams as well, where they are feeling the pressure from their management to do more with less.

How You Help Support In-House Teams

It’ll be like, “Can’t you get AI to do that?” As we are wrapping up here, you do a lot of outreach and consulting with in-house departments and other legal providers. I want to give you an opportunity to talk about the services that you provide and how you help support in-house teams.

I do have a full-time job as an in-house lawyer, and on the side, I primarily provide training for in-house teams on how to use their AI tools. It could be any tool that you are using, on how to get the most out of those tools. I have a couple of superusers, some people who have never touched it, and a group in the middle, and I try to bring everyone to the same level so then you can move forward and start to develop use cases. We start with playing around, developing use cases, and then, after that, it’s integration and maybe looking forward to more complex solutions. That’s what I enjoy working with teams on and doing. Interestingly, some people have also reached out to me individually for one-on-one AI coaching. That’s an interesting development. I was like, “Let’s try that as well.”

I can see that because you don’t want to sound dumb. There’s so much information in everything you read. In my ABA Journal, two-thirds of the magazine was about AI.

I almost have this obsessive thing where I love playing with it and want to figure out how we can use it to its greatest potential.

You are obsessing about WordPerfect, or maybe you’re obsessing about something else.

You’re obsessing about something else. Then, following people on LinkedIn or finding ways to stay up-to-date might be a little more challenging. I’ve even had friends reach out with questions and say, “I’m looking at this, what do you recommend?” I’m always happy to jump in and point someone in the right direction.

Laura, it would be helpful to have a resource and a sounding board to help navigate all this, which can be very overwhelming for folks who are spinning many plates at the same time. I’m thrilled that you have that service to help people and appreciate you being here. Where can people find out more about you? You’re on LinkedIn, but is there any other place people can find you?

That’s primarily on LinkedIn, and I also have an email there. You can hit me up on LinkedIn or use the contact information there to send me an email.

I close all episodes with the same question, which is more fun. I don’t know if you asked ChatGPT, but what is your pump-up song?

I had to think about this one, and I’m going to go with maybe a little esoteric, but Topdown by Channel Tres.

I don’t know that one.

I lived in LA for a while. I’m a California-licensed attorney, and it is a good song that you can imagine yourself driving in a Cadillac Convertible and getting into the groove with it.

Thanks so much for being here. I enjoyed it.

Thank you so much for having me.

 

About Laura Jeffords Greenberg

Laura Jeffords Greenberg is a Senior Legal Director at Worksome. Laura has also previously served as Director of Legal, Managing Counsel, Executive Board Member of Unity Technologies ApS, and Senior Legal Counsel at Unity Technologies. Laura has also worked as Senior Vice President – Business and Legal Affairs and Corporate Secretary at Rad and as Senior Legal Counsel – International Sales & Distribution at Red Bull Media House.

Laura began their career as an Associate Attorney at Peterson, Colantoni, Collins & Davis, LLP and also served as a Graduate Management Council Law Clerk (Limited Term Assignment) at the National Football League.

A thought leader in using AI in the legal profession, Laura advises international companies on legal strategy and leads global legal teams at the intersection of technology, media, and entertainment.

Her career has focused on supporting software, technology, media, and digital distribution teams. She enjoys problem-solving, simplifying complicated issues, and scaling legal operations to increase revenue for the business.