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 joined by Anna Gorodetsky, a partner at Major, Lindsey & Africa, where she oversees in-house counsel recruiting. As AI reshapes how legal work gets done, it’s also changing how law firms and legal departments think about hiring.

So in our conversation, Anna shares what she’s seeing in the current legal hiring market, including the growth of AI innovation roles at law firms, the pressure on in-house teams to do more with technology, and the practical AI experience that employers are increasingly expecting from candidates. We also discuss what practicing lawyers and law students can do to become more competitive, and how AI may change legal careers in the years ahead. With that, let’s jump into my conversation with Anna Gorodetsky.

Hi, Anna. Thank you so much for joining us on the AI Sidebar.

Anna Gorodetsky: Hi, Irene. Excited to chat about hiring in our age of AI.

Irene Liu: So, Anna, to set the stage, can you describe the legal hiring market today? Where are you seeing meaningful demand, and where has hiring slowed? And how has AI changed what employers are looking for?

Anna Gorodetsky: Yes, absolutely. The legal hiring market is not disappearing because of AI. It is bifurcating. There’s still meaningful demand for legal talent, but employers are much more selective about where they’re adding headcount. They’re increasingly wanting lawyers who can contribute immediately.

For example, NALP reported that law firm lateral hiring actually increased approximately 16% last year, with increases in both associate and partner hiring. And at the same time, firms have been shifting towards more experienced lawyers who can contribute immediately. And one analysis of last year’s associate hiring found that lateral lawyers accounted for a larger percentage of hires than recent law graduates. So, the senior in-house market, particularly in the Bay Area, is more uneven, I would say.

There’s meaningful demand in several areas. Number one, as you probably can predict, AI and other high-growth technology companies. Number two, privacy, cybersecurity, data, AI governance. We also see a demand for product and commercial lawyers, regulatory and compliance roles, both in financial services and fintech, as well as life sciences and biotech. We see a demand for public company governance, securities, IPO readiness, that expertise. We’re now also seeing more demand for energy data centers and AI infrastructure, as well as hardware, like robotics, autonomy, defense technologies.

And so, hiring has slowed for, I would say, broad generalists whose experience does not closely match the company’s immediate needs. So, companies are less willing to add nice-to-have layers of management or hire someone primarily for what they see they might need in the future. They really want to bring in people that they know will help solve the problems of today.

Irene Liu: So, there’s still hiring going on, which is great, but are you also seeing layoffs, hiring freezes, or restructuring in legal teams as a result of AI?

Anna Gorodetsky: I would be careful about attributing most legal layoffs directly to AI. There have been highly publicized restructurings in which AI was cited as a factor, particularly involving law firm business services, the knowledge management, administrative, and support positions. But even in those situations, recruiting and industry experts have cautioned that AI may be a part, but a small part of the story.

Firms may also be addressing overstaffing, redundancies, margin pressures, weak demand in particular practices, or outdated operating models. So, I would say within corporate legal departments with which I work the most, I am not seeing widespread elimination of senior lawyer positions because of AI. I would say the impact is more subtle.

AI is more likely to result in a position remaining vacant for longer, maybe a backfill being questioned, and that we do see. A junior role being combined with another position because there isn’t the same need for those junior roles. Work moving to legal ops more so than we’ve seen before into contracts management or flexible talent, sometimes fewer outside counsel hours because of AI, and sometimes a team being expected to absorb additional volume without adding headcount.

I also looked at some research on this, and legal leaders recently interviewed by Bloomberg Law described the near-term effect as a gradual slowing or demand of hiring, rather than this mass elimination of lawyers.

Irene Liu: So, let’s talk a little bit about the in-house roles first before we focus on the law firm. And so, with the in-house roles, are the general counsels being pressured to shift to use more AI and to hold off on any backfills or hiring? Is that sort of the general trend that you’re seeing?

Anna Gorodetsky: Yes, we’re definitely seeing that trend. We’re increasingly seeing and hearing that a replacement search is no longer automatically approved simply because the company previously had someone in the position.

At more AI-forward companies, particularly in tech, GCs are often asked, “What work was this person performing? Which portion can be automated? Can it be absorbed by the existing team? Can it be moved to a lower cost provider? Can outside counsel or flexible talent or contract professionals handle it? And frankly, what measurable risk arises if the position is not filled?”

That pressure is consistent with broader in-house research that I’ve done. More than half of the respondents to a Thomson Reuters 2025 Legal Department Operations Index said that their departments were under-resourced, and about 59% were increasing their use of technology, and 88% reported stable or increasing technology budgets. And then we also looked at the ACC and Everlaw, and they found that 64% of surveyed in-house lawyers expect gen AI to reduce reliance on outside counsel et cetera.

So, GCs can still obtain backfills, particularly for work involving a lot of strategy and business judgment and executive counseling, as well as the regulatory overlays that we’re seeing in highly regulated industries. But they need to make a more disciplined business case for them.

Irene Liu: And because there’s a lot more reliance on technology and pressure to use technology, are legal departments changing the profiles that they’re hiring because of AI? Are they looking for lawyers with more technical skills and ability to redesign workflows, manage AI, and analyze data, and lead cross-functional transformation?

Anna Gorodetsky: Absolutely, Irene. Although the change is, I would say, broader than simply asking for AI lawyers, right? They’re increasingly wanting what I would call kind of a lawyer plus profile, someone who has excellent legal judgment, but can also improve the way that the work gets done. And so that can include identifying repetitive or inefficient workflows, working effectively with legal ops and tech teams, evaluating technology without being dazzled by it, as well as creating playbooks and scalable processes, leading cross-functional teams.

I think GCs are looking beyond traditional legal skills and considering AI specialists, cybersecurity experts, and AI developers as part of this future talent mix that they’re going to employ.

Irene Liu: And you mentioned that there’s a trend towards this lawyer plus, and so if businesses are looking for lawyer plus, are they compensating more for this plus skill? What is the compensation trend? Because that’s a component that many are very curious about. What are you seeing from a compensation standpoint for these AI plus skills?

Anna Gorodetsky: We have not seen a broad identifiable, I would say, like AI premium, right, applied to ordinary in-house lawyer comp. Traditional in-house compensation is still driven primarily by other factors, namely company size and stage, the industry, the role scope, the seniority, the reporting line, public versus private, whether there’s management responsibilities as part of the role, geography, and other things like the candidate’s track record.

So I would say the broader in-house market has not shown a dramatic salary increase inflation attributable to AI. I think there’s one study that reported average salary increases of approximately, like, 2.8% across in-house legal positions. This was a Barker Gilmore study last year, and MLA has done its own studies. We haven’t seen a significant increase that we could say is attributable to AI.

Irene Liu: 2.8%, it’s marginal.

Anna Gorodetsky: It could be a statistical, you know, error

Irene Liu: Yeah, yeah. It’s almost like cost of living adjustment. And so frankly, what’s happening is that from a technical skill point, a lot of companies are looking for in-house lawyers with AI skills and lawyer plus skills, but the compensation has remained relatively stable despite the need for more technical skills. Is that how what you’re seeing?

Anna Gorodetsky: Absolutely. That’s what we’re seeing. And I would say for GC and deputy GC or other senior in-house candidates, AI experience is more likely to be a selection premium rather than a compensation premium, right? It may help the candidate win the position-

Irene Liu: Yeah

Anna Gorodetsky: … over someone with a similar resume, but it doesn’t necessarily add a fixed percentage to the offer. There is a legitimate concern that some companies are simply expanding the job description, where it’s expected to advise the business, handle more work, improve operations, understand data, implement AI, and reduce outside counsel spend, but compensation has not necessarily increased with these expectations.

Irene Liu: So, Anna, one of the other things that we’re hearing is that candidates for general counsel as well as more traditional legal roles, especially in-house roles, people are being asked in interviews, “What have you built with AI?” And that’s a very standard question that we’re hearing. And so how important is this question, and how should people prepare for this?

Anna Gorodetsky: I think it’s a very important question, particularly at AI companies and in searches where transformation is central to the mandate. I don’t think built necessarily means that a candidate had to code a proprietary legal application. For senior lawyers, a strong answer might involve redesigning an NDA or a commercial contracting process. Or it can be creating an AI-assisted first-pass review, or implementing an approved research or drafting tool, or building a playbook or knowledge repository, right?

And so, I do think that it doesn’t necessarily involve someone who is a coder, but someone who’s very familiar with these systems and integrating legal with maybe a company-wide AI initiative. So, the important point here is that employers are moving beyond, “Have you used ChatGPT?”

Irene Liu: Yeah.

Anna Gorodetsky: They want to understand whether the candidate can really convert experimentation into a reliable workflow, right? And so, that distinction really matters because adoption figures can be quite misleading.

There was a study this year by Axiom, I think they looked at five hundred and twenty-eight in-house lawyers, and it found that only 7% had actually moved beyond pilots to scaled, optimized, measured AI used. And I think 83% couldn’t demonstrate whether their prior AI spending had actually even produced a return. Because it was a vendor-commissioned study, I would definitely treat the exact percentages cautiously, but the implementation gap that it identifies is real, and it’s consistent with what we’re seeing in the market.

So, a good candidate answer should cover the following points: What was the underlying problem? What was the process before the change? What tools or approach was tested? What safeguards and human review were used? How did the candidate actually drive the adoption? And what measurable result actually followed?

So, the best answers are often not the flashiest. So, a modest project that reduced turnaround time by 20, 30% and improved consistency and had clear controls is more credible than a vague claim that a candidate transformed the legal department through AI.

Irene Liu: And are you seeing employers change their interview process even further, not only to question about what they have done and how they have used AI, but to actually incorporate practical exercises or case studies or even demos? Are they asking interviewees to go beyond just talking about their experience, but really showing how they have used AI during the interview process?

Anna Gorodetsky: Absolutely. They are very much beginning to change. Although I would say this is more developed in law firm graduate recruitment than I think it is at this time in the senior in-house hiring. I’m hearing from my partners on the law firm side that at firms like Freshfields and A&O Shearman have tested exercises involving AI prompts, fraud outputs, responsible tool use.

I would say in my searches, in the senior in-house searches, I more commonly see things like case studies, some operating model questions as well, scenarios involving an AI product launch, questions about governance and adoption, I think sometimes requests to describe a workflow improvement, and just probing around the candidate’s personal use of AI as well.

I do think that candidates should be extremely precise about their role. I think there’s a really meaningful difference between using a tool, participating in a pilot, leading a pilot, selecting the tool, implementing it enterprise-wide, and owning measurable results. I think overstating someone’s experience will be exposed through some follow-up questions.

I think it’s important to stay candid, and I think sometimes a candid answer such as, “I did not lead that enterprise-wide implementation, but I owned, you know, the use case and learned the following,” I think is much stronger.

Irene Liu: Yeah. But you mentioned that there is a premium, a selection premium to those that can use AI and utilize AI. But what about the practicing lawyers or lawyers that are currently in the market that just have not had experience with a formal AI implementation? How do they remain competitive, and how can they discuss their AI skills to remain competitive in this market?

Anna Gorodetsky: Yeah. I think they need to first become an informed user of AI. Learn the approved tools available within the organization, understand how they work, their limitations, the security model, the appropriate uses, right? I would say the next step is select one actual workflow. Choose something that’s sufficiently repetitive, measurable, and then intake research, contract summaries, first drafts, issue spotting, meta-reporting, or a knowledge management process.

As a next step, I would say establish a baseline. How long does that process take today? Where are the bottlenecks in this process? What errors or inconsistencies occur? And then run a controlled pilot. Start with low-risk workflows, include human review, and define successes before beginning, then measure the result, time saved, cycle time, consistency, business satisfaction, outside counsel savings, all of that.

I would say learn the governance issues, understand the confidentiality privilege, data use, hallucinations, all of that, and finally, develop a coherent interview story. And so, explain not just what the tool did, but how this lawyer exercised judgment and led the people through the change. And so, I think that training really matters.

I think there was a study earlier this year, a randomized study involving law students, access to an LLM without instruction did not improve performance, while a brief training intervention really increased adoption and improved results. So, I think the lesson for practicing lawyers is that access to technology is not the same as competence.

Irene Liu: So regardless of whether you have the opportunity or not to lead a, a wider AI transformation, you need to make sure you stay involved and that you’re experimenting too so that you build your competence.

Anna Gorodetsky: Absolutely. And importantly, not to forget that this doesn’t replace the core competencies that are-

Irene Liu: Yes

Anna Gorodetsky: Looked for in a lawyer, like the legal judgment, the commercial acumen, the communication skills, ability to make difficult decisions with incomplete information. All of those still remain very important.

Irene Liu: Yeah, and thanks for emphasizing that. All of those are such important human skills that are frankly probably more important in an in-house setting because you’re constantly communicating with other team members, and your ability to be able to build that trust that AI can’t build is fundamentally more important in your success within an organization.

Anna Gorodetsky: Absolutely.

Irene Liu: So now that we talked about in-house, let’s shift gears to law firms. And we have been seeing a lot of different new roles being added. We’re seeing on LinkedIn these types of roles being posted around chief AI officers, innovation directors, AI knowledge managers, legal engineers, and even data scientists.

So, what are some of the trends that you’re seeing around these emerging roles within law firms, and which roles are actually receiving the most investment?

Anna Gorodetsky: Yeah. And just as a reminder, my lens is a little bit more so on the in-house side, but I have had a chance to look at some data and talk to my colleagues on the law firm side. And what we’re seeing on the law firm side is a range of roles, I would say, including chief AI officer, chief innovation officer, director of applied AI, director of legal innovation, AI governance leader, legal engineer, I love it, knowledge engineer, data innovation officer. And so, there are definite dedicated senior leadership appointments that are becoming more visible.

For example, at Pillsbury, they appointed their first chief artificial intelligence officer in July of this year, with responsibility for AI strategy, for governance, for enablement, data science, and knowledge management. Another law firm- HSF Kramer created a global chief AI officer position last year to lead the implementation across practices.

So, I would say the positions receiving the greatest investment tend to be those tied to actual delivery, so embedding AI into specific practices and turning firm knowledge into usable systems for lawyers, driving lawyer adoption, building client-facing products, establishing governance, measuring value, those types of things.

Irene Liu: So, with all of these new innovative roles that are being created at law firms, where are they finding the talent?

Anna Gorodetsky: Yeah. I don’t think, Irene, there is a single established pipeline, which is part of why the talent is difficult to find. Law firms are drawing from a number of groups of potential pools of candidates.

I think one is internal practicing lawyers, and these are often respected partners or associates who become early adopters, and they understand the work and can influence their colleagues. And their advantage, frankly, is credibility, right? Their possible limitation is that they may not have had the implementation or enterprise change experience yet. So that’s one group.

I would say the second group comes from knowledge management or maybe sometimes it’s called practice innovation and legal ops as well, and these are professionals who often understand to begin with workflows and data and technology adoption and internal policies of a law firm.

I would say a third group comes from legal tech companies, legal engineers, product lawyers, solutions consultants, implementation leaders of all kinds. They understand both the technology, but they also understand what lawyers need from it.

And I think lastly from consulting firms, corporate legal departments, some of these multidisciplinary professional services organizations, and these would be candidates who bring stronger, often, like transformation and proven program management experience. From what I understand, the market values particularly people who have moved among more than one of those environments.

So for example, if we look at some of the hires at Pillsbury and HSF Kramer. HSF Kramer’s chief AI officer, for example, had experience from a law firm, McKinsey Legal, at MasterCard, and Pillsbury’s appointment had led innovation functions at several major law firms and advised technology companies and investors. So, it’s not like they have one linear trajectory. They’ve had different roles that they bring to bear.

I would say the rarest candidate is not necessarily the most technical person. It’s just someone who can walk into a partner meeting, understand the legal work, command credibility, translate it into technology-enabled processes, and then persuade people to change how they work.

Irene Liu: And what are law firms expecting from these AI and innovation leaders? What are they expecting them to deliver, and are the firms even giving them the authority, the budget, and the resources that they need to succeed? How invested are they in these roles?

Anna Gorodetsky: The mandate can be extraordinarily broad. Firms are often expecting one leader to do a lot of things, like establish the AI strategy, select and manage vendors, create governance standards, address client and ethical concerns, train hundreds, sometimes thousands of lawyers, right? Increase adoption among those lawyers, produce measurable savings, advise on pricing, and recruit this technical team as well, and keep pace with new technology that seems to be changing on a daily basis.

So it’s a very difficult mandate for one person, and I think the underlying challenge is that buying the tool is the easy part, right? It’s really the adoption and workflow integration and the data quality, the incentives, and the change management that’s becoming much more difficult.

And so, yes, the roles can become unrealistic, and I think a firm may want an innovation leader to demonstrate immediate ROI while also requiring multiple committees to approve every single change, which is quite hard.

I think for these roles to succeed, these leaders need to have visible sponsorship from the firm’s leadership, which often is the case, but not always. They need to have an actual budget, which they usually do have. They need to have access to practice group leaders, which is hit and miss. They need to have the right technical data and project management resources. They need to have the authority to set governance standards, which sometimes becomes a challenge, clear performance metrics, and a realistic time horizon.

Irene Liu: And they probably need more people, which is why we’re seeing these types of knowledge management, legal engineer, as well as AI directors within law firms’ job postings. So, I can see these leaders now starting to build out their teams, and it’ll remain to be seen how much support they get beyond that.

Anna Gorodetsky: Absolutely.

Irene Liu: Well, so Stanford Law School is obviously very interested in the hiring trends as well because we are trying to prepare our law students for the future, especially in this AI-driven hiring market. So, what experiences, courses, internships, or projects do you recommend to law students to help them stand out?

Anna Gorodetsky: Good question, and I, I would say my first piece of advice here, Irene, is don’t think of AI fluency and expertise, if you can even have such a thing as AI expertise, as a substitute for becoming an excellent lawyer.

So, students still need to learn how to read cases, how to analyze precedent, analyze ambiguity, write clearly, and all those wonderful things. However, I do think that a useful preparation for this new AI world that we’re living in would include a course on AI and the law, and most law schools are offering something like that.

Coursework in privacy, in cybersecurity, or data governance, I would say legal operations or process design exposure in any way that they can get it Working at a legal technology company or with a legal technology company in some consulting capacity. Maybe an internship in an in-house legal department that’s utilizing AI, interdisciplinary work with engineering or business students, which hopefully law students at Stanford could have exposure to.

Maybe there’s a clinic that uses technology to improve legal service delivery, or maybe a supervised project on applying AI. Maybe there’s an opportunity for a student to actually create a small portfolio, and that might include a responsibly designed research workflow, maybe a contract intake prototype or a comparison of AI-generated and independently researched work, or something like that.

I think some law schools are already making AI education, as you probably know, and are at the forefront of, at Stanford, mandatory. Firms are beginning to use AI-related exercises in graduate recruiting. So, I think the goal is not to become the best prompt writer in the class. It’s really to become a lawyer who knows how to use these powerful tools, but without surrendering that independent thought, that judgment.

Irene Liu: And that’s also another human skill, judgment, that is so important and critical in this day and age. One of the other things that we talked about is that only the top 5% of candidates may be securing opportunities. So, what separates those candidates, and what should everyone else do to upskill and become more marketable like them?

Anna Gorodetsky: Yeah. I would clarify that the top five is more of a shorthand for just how concentrated hiring outcomes can feel in such a selective market. It’s not, I don’t know that this is a scientific measurable percentage.

Irene Liu: Yeah.

Anna Gorodetsky: But the strongest candidates do tend to demonstrate several things at once. They have, number one, the relevant experience, not merely impressive experience, right? I think nowadays the employers can quickly connect what the candidate has done with what needs to be accomplished in the immediate future at the company and… or at the law firm.

Two, they show results rather than responsibilities. I’ve been telling candidates my entire legal recruiting career, start conveying your experience the way businesspeople do, which is by measurable, quantifiable impact. You have 20 years of experience, why are you still writing drafted, redlined, and negotiated agreements? So instead of saying, “I oversaw commercial contracting,” they can explain how they reduced, say, cycle time, enabled revenue, built a team, or created a scalable process, right? And so, I think all of that is really important.

I would say the other thing that divides strong candidates from less strong ones is that they have to show executive presence and judgment. Especially at a senior in-house level, clients are evaluating whether the person can truly advise the CEO, maybe even challenge a business leader appropriately and communicate in a crisp, concise way, translating legal issues into business terms, and that’s a very important one.

They need to understand how businesses are run and business models and speak about customers and products and revenue and capital and risk and strategy in an informed way, and not just from the lens of a lawyer. I feel like they need to be adaptable and without being superficial. So, they may have had AI and operational exposure, but they also need to have substantive legal strength and kind of the foundational legal experience as well.

They need to be able to convey a coherent career story as well. So, the interviewer needs to understand why they’ve made the moves they’ve made, what they learned from the various positions they’ve had, and why their career trajectory makes sense. So, these are just some of the things.

Irene Liu: And what about those that are in the market and are struggling to secure a role? I know that there are some in-house counsels that are trying to figure out their next job. There are also general counsels that are in between market. There are law students that are trying to find their first job, especially with junior hiring being so difficult.

Anna Gorodetsky: Yeah.

Irene Liu: How should they upskill and what should they do next to try to become more marketable and find a role?

Anna Gorodetsky: Yeah. Well, I think it’s important to diagnose what exactly the problem is, because the problem could be multiple issues or it could be something very discreet. So, are they even applying for roles where their experience is relevant? Or maybe it’s too broad or too narrow. Is their resume describing, like I’ve mentioned before, duties rather than impact? And are they targeting only one title, industry, or geography and they’re being just too narrow, right?

And so, I would focus on the following. Number one, I would build a missing credentials kind of framework around actual work. So instead of getting a certificate in something, lead a project, take ownership of some regulatory issue, implement a workflow, manage a junior person, do something to obtain direct experience, right? Courses can help, but experience is much more persuasive.

I would expand the path without kind of abandoning the goal, so to speak. So, a candidate, for example, seeking a GC position might consider a deputy GC role or divisional GC role, or maybe a chief compliance officer role. And someone who’s in tech might consider fintech or insurtech or maybe even robotics but be open to pivoting a little bit industry-wise, right, adjacent sectors-wise.

I think creating momentum is important, and so interim work, consulting projects, secondments, advisory assignments, even nonprofit board work, all of those help. I would definitely discourage candidates from just collecting numerous credentials, certificates without a clear theory. So, no one’s gonna care how many AI certificates or privacy certificates you’ve had. It’s like, “What can you do now that can help us?” And unless you’ve already done it in some other sphere, it’s not gonna be as transferable a skill set.

Irene Liu: So, Anna, looking ahead, how do you expect AI to change the legal hiring market over the next few years?

Anna Gorodetsky: Well, number one, I think AI fluency will become the baseline. Right now, it’s a very nice to have for most legal roles. In three to five years, saying that a lawyer knows how to use AI may be similar to saying that a lawyer knows how to conduct legal research. It’s gonna be expected rather than a differentiator. And I think legal teams may grow more slowly while their mandates expand.

Going back to what we were talking about earlier, am I envisioning a bunch of layoffs? I’m not, and maybe because I’m an optimist, but I am envisioning a slower kind of growth in some areas. And so, I think legal demand continues to grow because of regulations, because of data, because of the geopolitical risks, product complexity, litigation, all those things that mandate more lawyers. But companies may build smaller teams than they otherwise would, particularly for repetitive, redundant, and maybe document review intensive work.

And junior work will be a challenge. I think that’s where we’re gonna see most impact, like research, diligence, like first draft, summaries, like basic contract review and document work will increasingly be AI assisted, and that we know now. We’re seeing that already. And that does create what we call this apprenticeship problem, because the legal profession will continue to need new ways to teach judgment when junior lawyers are no longer spending the same amount of time, a number of hours, producing that work from scratch like they used to. And so that will be a challenge. How do we actually train junior lawyers if a lot of that work is gonna be done by AI?

I think we will also be seeing more legal engineers, AI governance professionals, and some of those that we discussed before. Some will have law degrees. I think some of them will not. I think the most effective legal organizations will likely use multidisciplinary teams rather than assuming that every legal problem requires a traditional lawyer

Irene Liu: So, in essence, the legal market will continue to grow, but the roles will evolve, and AI skills will become a baseline.

Anna Gorodetsky: Absolutely. And I do think the value of human judgment will increase. As drafting and information retrieval becomes faster, the differentiating skills are going to be recognizing when the answer is wrong, understanding the context making judgment calls, persuading the stakeholders, and earning trust. These are still the dominant human judgment skills that AI cannot replace.

Irene Liu: Well, thank you so much for returning us back to the importance of humans in this age. And so, we really appreciate you sharing the hiring trends in this age of AI. Thanks so much, Anna.

Anna Gorodetsky: Thank you.

Irene Liu: A big thank you to Anna Gordetsky for joining us and sharing her perspective on how AI is changing the legal hiring market. And thank you for listening to The AI Sidebar. If you found this conversation helpful, please follow the podcast and share the episode with a law student, lawyer, or legal friend who is thinking about how to prepare for an increasingly AI-driven market.

We’ll be back in two weeks with another thoughtful conversation at the intersection of AI and law. Until next time, stay curious and keep learning.​