Key highlights:

• • • The theory-practice gap is now an AI-era crisis鈥� Integrating legal training with hands-on pro bono experience is the future of legal education.

    • A collaborative model merges learning and doing into a single platform鈥� The model connects law students with vetted pro bono opportunities from legal services organizations, while also offering targeted, skills-based training at the moment students step into those matters.

    • Pro bono work is uniquely suited for responsible AI training鈥� On-demand programs led by expert faculty are available to help students sharpen pro bono skills, understand the use of AI in today鈥檚 legal practice, and stay on top of developments in numerous industry and practice areas.

Legal education has operated on a familiar, decades-long divide that saw students spend their first years learning the law in the classroom and then after graduation, gaining substantive experience practicing the law in the real world. This gap has always been costly for both students and legal employers, and now it鈥檚 emerging as untenable in an era in which AI is rapidly reshaping what junior lawyers do.

Pro bono and skills training close this gap

A new partnership between , a pro bono management platform, and the (PLI), a nonprofit provider of learning resources for legal professionals, is designed to close this gap while showing something larger about where legal education must go.

The partnership is designed to equip students with on-demand, actionable training that supports effective pro bono engagement by offering access to PLI’s training programs directly through Paladin’s platform. Since launching with 30 law schools in August 2025, students have signed up for thousands of pro bono cases through the platform, according to , Co-founder and CEO of Paladin.

For years, experiential learning in law schools was something students had to piece together on their own by hunting across spreadsheets, clinic listings, and externship postings for opportunities, says Sonday, adding that too often students were given little guidance on what they were walking into.

The partnership is designed to equip students with on-demand, actionable training that supports effective pro bono engagement

“What’s fundamentally different is the integration and centralization of learning and doing,” Sonday explains. “Historically, legal education has separated theory, training, and practice.” Now, she notes, a student can learn a concept, build confidence through targeted training, and apply it in a real-world setting within a short amount of time.

, Chief Strategy Officer at PLI, describes the experience from the student’s perspective: 鈥淲hen a first-year logs into the Paladin platform, they are not thrown into the deep end. Instead, they can access skills-based programs, such as a PLI program specifically on how to interview a pro bono client before they ever sit across from someone in need. This leads to a better experience for the student, the law school, and especially for the client.”

Pro bono work suited to responsible AI training

The urgency behind this partnership is inseparable from the impact AI is having on the entry-level legal market.

“We’re already seeing AI reduce the time spent on tasks like initial legal research, document review, drafting memos, and summarizing case law,鈥� Sonday says. 鈥淭his is work that has traditionally formed the foundation of junior associate training.鈥� The skills AI cannot replicate 鈥� such as judgment, issue spotting in ambiguous situations, client communication, and ethical decision-making 鈥� are what students need to develop deliberately earlier in their legal careers.

Indeed, those human skills are essential to the effective use of AI, Talmage says. The lawyer of the future will be a strategic advisor and creative problem solver, which are the very attorney roles that AI cannot fill, she explains, adding that those must be cultivated through experience. “You always need to be questioning and verifying and authenticating 鈥� and that’s generally a lawyer鈥檚 role.鈥�

For years, experiential learning in law schools was something students had to piece together on their own by hunting across spreadsheets, clinic listings, and externship postings for opportunities.

There is a particular logic as to why pro bono work is the right fit for learning to use AI responsibly. Pro bono is “a built-in, humans-in-the-loop model” in which students are always supervised by attorneys, Sonday says. And this supervision creates a structured environment in which to learn how to use AI tools, apply them to real matters, get feedback, and iterate. The result, Sonday argues, will be more attorneys who are AI-fluent early on and throughout their careers.

A message to law school leaders

For law school leaders, both Sonday and Talmage highlight that AI use has already changed the legal profession. The choice then for law schools is whether they evolve by design or by default.

Students know the legal profession has changed and so do employers, CLE providers, and clients, Talmage explains.

Sonday agrees. “The pace of change in the legal profession is accelerating, and students need to be prepared not just for the law today, but also for the practice of law in the future,鈥� she says. 鈥淚ntegrating pro bono platforms and AI-specific training aligns legal education with reality.”

The Paladin/PLI partnership offers a blueprint for what legal education must become in the future, transforming itself into a space that鈥檚 grounded in applied legal knowledge, human-supervised, and AI-informed. Indeed, the best way to train the next generation of lawyers is to give them real clients, real cases, and real responsibility while they still have room to grow.

You can find more about the challenges facing law schools and legal education here

Key insights:

• • • AI is changing legal鈥檚 role, not just its workload 鈥� Going forward, AI will do more than automate routine tasks, it also will help in-house legal teams become more strategic business partners.

    • The 5 archetypes make the transformation concrete 鈥� There are five practical ways in which AI could reshape legal work, including automation, stronger advising, better collaboration, and global scale.

    • Every organization鈥檚 AI transformation will be different 鈥� 成人VR视频鈥� own legal transformation journey shows the common and unique aspects of this process.

Beyond the automation, productivity boosts, or the now-familiar promise of doing more with less, the question over how AI will really transform the work that corporate legal departments do on a daily basis, has yet to be truly answered.

To deepen our understanding of where in-house legal is really heading next, Norie Campbell, 成人VR视频 Chief Legal Officer, and Lizzy Duffy, a Senior Director of the 成人VR视频 Institute, produced a new feature article, The 2030 legal department: 5 ways AI will transform how in-house teams work听that steps back from the day-to-day noise around AI and asks the bigger, more interesting question: 鈥淲hat is the legal function actually becoming?鈥�

Importantly, the article recognizes that in-house legal teams are navigating real constraints around time, budget, and clarity even as expectations continue to evolve. It also acknowledges how GCs are balancing rising demands with a growing focus on efficiency, while also working to define what effective and meaningful AI adoption should look like for their teams.

Indeed, this human pressure is one of the most compelling aspects to the questions corporate law departments are facing today, and it reverberates beyond a simple theory of AI in legal to really reflect a profession at a turning point.

The five archetypes

The feature also lays out five archetypes 鈥� distinct models for how AI could reshape legal work, from high-volume automation to better strategic advising, stronger business partnering, smarter collaboration with outside counsel, and truly global leverage across teams and languages.

By referencing these five archetypes, legal department leaders can start asking where their own teams fit, and what they need to do to get better prepared for the AI-driven legal future of 2030.

These archetypes cover everything from deciding on the best ways to leverage AI-led automation to helping legal teams become more proactive strategic advisers. The archetypes also detail how to foster collaboration that can allow other corporate functions to act more confidently without constant legal intervention. And how to use AI to reduce barriers caused by language and time zones, enabling multinational legal teams to work more effectively across geographies.

By referencing these five archetypes, legal department leaders can start asking where their own teams fit, and what they need to do to get better prepared for the AI-driven legal future of 2030.

成人VR视频鈥� own journey

This feature article also builds a practical, grounded picture of the future from inside 成人VR视频鈥� own General Counsel鈥檚 Office (GCO), showing readers a transformation that鈥檚 already taking shape.

This insider perspective offers a front-row look at how one GCO is trying to move from experimentation to real transformation and tells a bigger story than technology alone. Today鈥檚 transformation of the corporate legal department is really about leadership, ambition, and the choices department leaders need to make now if they want to stay relevant by 2030.

More than anything, the feature article stresses that adopting AI tools is not the same as true transformation. To move beyond incremental gains, legal departments must redesign workflows, improve data infrastructure, invest in training, and hire for adaptability and technical literacy. Ultimately, the central message is that efficiency is only a by-product 鈥� the real challenge is deciding what kind of legal function an organization will need in 2030 and how to start building toward that vision now.

You can access the full feature article, The 2030 legal department: 5 ways AI will transform how in-house teams work here

Key highlights:

• • • Curriculum听redesign must start now 鈥� One law school鈥檚 approach illustrates the necessity of mapping the entire curriculum to identify which skills to preserve, evolve, or build from scratch.

    • Training faculty in AI use is critical 鈥� Faculty AI training should be a multi-layered approach including hands-on training with specialized legal AI tools, guidance on redesigning curricula, and more.

    • AI simulations may be the key 鈥� Law school leaders need to act now by experimenting with small pilot projects and building simulation-based learning tools to replace the developmental depth that once came naturally in the first years of practice.

The debate about AI consuming most of the work that teaches essential lawyering skills to junior attorneys is forcing a reckoning with the long-held assumption that law schools were never designed to produce practice-ready lawyers and that it was always the profession’s job.

Indeed, AI is forcing that uncomfortable truth into the open faster than anyone anticipated because essential lawyering work 鈥� the document review, contract markup, research memo creation 鈥� dictated how a junior lawyer learned to spot the issue buried on page 47, to sense when a clause was off, and to develop the instinct that no classroom can fully replicate. Now, as more law firms deploy AI to handle precisely those entry-level tasks, the organic training moments that used to define the first two to three years of legal practice are evaporating.

, Executive Dean, Faculty of Law at Bond University, and Co-Chair of the Council of Australian Law Deans, says he sees where this is leading. The ultimate results will be firms hiring fewer junior lawyers today because AI has taken over that entry-level work, James explains, adding that means there will simply be no pipeline of mid-level, experienced lawyers to draw from in three to five years. Indeed, this is a slow-moving crisis, already in motion, and yet to fully arrive.

This crisis lands at the center of what the AI and Future of Legal Practice (AIFLP) initiative exists to address because at the core of this crisis is what does being job-ready really means when the job itself is being redefined. Answering this question requires law schools, law firms, licensing bodies, and technologists to do something they have historically struggled to do 鈥� that is to think and act collaboratively.

Rethinking the curriculum before AI does it for you

leads IE Law School鈥檚 AI initiative and is steering the school鈥檚 efforts to embed AI across the curriculum. To do so effectively, her approach requires going back to a broader set of foundational questions in legal education such as: For what is legal education meant to prepare students? How do students learn to develop legal judgment? What makes legal advice genuinely valuable? And what skills are essential to deliver that value in an AI-enabled profession?

鈥淟ayering AI tools on top of an unchanged curriculum serves no one,鈥� Perez-Llorca explains, adding that without answers to the fundamental questions, 鈥測ou are just adding technology to a structure that was never designed to handle it.鈥�

Check out how one law school professor is building AI simulation tools

IE law school is currently mapping its entire curriculum to determine which skills need to be preserved, which need to evolve, and which need to be built from scratch, while also using the AI-boosted curriculum to train faculty. Perez-Llorca describes the school鈥檚 faculty AI training as a multi-layered approach encompassing university-wide LLM training, substantive AI law curriculum review, hands-on training with specialized legal AI tools, guidance on redesigning curricula, and assessments to reflect students’ growing AI proficiency. Before students can be taught with AI, professors need to understand the tools themselves and how to use them in teaching, in simulation, and in assessment, she adds.

An AI tutor that meets students where they are

Bond University鈥檚 James says he has spent the last several months building an AI tutor designed to walk students through course material the way a patient, attentive instructor would. His vision for the AI teaching assistant supports the professor meeting students where they are. 鈥淚t [the AI tutor] introduces the week’s topic, outlines learning outcomes, guides students through the readings, checks comprehension with short quizzes, and then adapts in real time based on how the student responds,鈥� James explains, adding that the AI tutor will pull any student who is struggling deeper into the material until the learning outcome is achieved. 鈥淭he conversation never stops until the learning does.鈥�

However, James is careful to draw a clear distinction about what the tutor replaces and what it does not, stressing that AI is a substitute for the lecture recording, the static reading list, or the passive video watched at midnight before an exam 鈥� but it chiefly exists to support the law professor. This approach frees up class time, turning it from content delivery to more meaningful the time between the human instructor and students, he adds.

Act by design or default

The approaches by both Perez-Llorca and James point to a way to address the question of disappearing tasks that teach essential lawyering skills as well as shift the center of gravity in legal education toward ways to foster developmental skills and legal judgment. Indeed, inertia is not a strategy, and law school deans and associate deans can be at the forefront of this fight by taking decisive action, including:

• • • Experiment freely 鈥� Investigate with AI on your own by starting small with a pilot project.
    • Strategically assign where AI goes 鈥� Decide where AI belongs in the curriculum, such as in courses focused on legal research and drafting as they become commoditized by AI. Also, determine in which instances AI does not belong, such as counseling clients through ambiguity, navigating ethical complexity, and advocating persuasively. Make sure these all remain led by human lawyers.
    • Focus on skills 鈥� Map your law school鈥檚 curriculum by identifying which skills need to be preserved, which skills need to evolve, and which need to be built from scratch.
    • Build AI-assisted teaching tools 鈥� Make experiential and simulation-based learning central to the curriculum.

鈥淭he choice is between dealing with this crisis by design or by default,鈥� James says, noting that the pipeline problem he described is already in motion while the practitioners, educators, technologists, and licensing bodies that need to solve this together are not yet consistently in the same room.

Watch our recent Clarity podcast to see

Key takeaways:

• • • Falling behind on worked rates 鈥� Midsize firms grew worked rates by just 5.3% in Q1 2026, roughly half the Am Law 100’s 9.8% growth 鈥� a structural gap that has widened with every passing quarter.

    • Underinvesting in the tools that will define tomorrow 鈥� Midsize firms also invested 6.2% more in tech and knowledge management in the quarter 鈥� the lowest of any segment 鈥� leaving them at risk falling behind as larger peers accelerate their investment.

    • Sitting out the talent race 鈥� With recruiting expense growth at -0.2%, Midsize firms are virtually absent from the lateral market while their closest competitors saw 5.6% growth in their investment.

In Q1 2026, demand growth across all segments landed at 2.7% year-over-year, with 听Midsize firms coming in at 2.6%, essentially in line with the market average and comfortably ahead of the Am Law 100’s 1.2%, according to the 成人VR视频 Institute鈥檚 recent Q1 2026 Law Firm Financial Index (LFFI).

Based on this metric, Midsize firms are not underperforming, as they are capturing work at a pace that outstrips the elite tier; however, a deeper look shows a more nuanced story. The Am Law Second Hundred led all segments with demand growth of 3.9%, posting a notable advantage over the Midsize segment. That growth was enough to make up the ground ceded by the Am Law 100 that the Am Law 200 as a whole still managed to outstrip the Midsize segment in terms of demand growth.

That makes the demand story a very mixed one for Midsize firms. While they are holding their own against the very largest firms, the Am Law Second Hundred 鈥� Midsize鈥檚 most direct competitive set 鈥� is pulling significantly ahead on volume. If that gap persists, it could further shut the gates to demand gains. Of course, that would be made all the more impactful because of how rising demand influences firms鈥� ability to raise rates.

Rates are the most consequential gap in the data

If demand tells a moderately positive story for Midsize, worked rate growth is the point at which the data turns slightly more negative for the segment. In Q1 2026, Am Law 100 firms posted worked rate growth of 9.8%, the highest of any segment by a significant margin. The Am Law Second Hundred recorded 6.9% growth, while the overall market average was 7.0%. Midsize firms, meanwhile, came in at 5.3%.

That is a gap of more than 4.5 percentage points between Midsize and Am Law 100 firms, a magnitude outstripping the entirety of the Midsize segment鈥檚 demand gains.

What makes this especially significant is that the gap is not new 鈥� one year ago, in Q1 2025, the same hierarchy held, with Am Law 100 firms seeing worked rates grow at 9.4%, Second Hundred firms at 7.1%, and Midsize firms at 5.9%. In other words, the rate divergence between Midsize firms and the rest of the market has been consistent and is widening even further. The end result of this is stark: Midsize firms are growing revenue per hour of work at a pace roughly half that of their Am Law 100 counterparts, and that differential compounds over time into a meaningful profitability disadvantage.

Expenses diverge in the wrong direction

On the expense side of the ledger, the pattern reverses in a way that creates a genuine squeeze for Midsize firms. Looking at direct expenses 鈥� the costs most closely tied to delivering client work 鈥� Midsize firms recorded growth of 5.4% in Q1 2026, the highest of all three segments. This compares to 4.8% for the Am Law 100 and just 4.4% for the Am Law Second Hundred. That means that Midsize firms are generating the slowest rate growth while simultaneously growing their client-delivery costs the fastest. That combination reflects a textbook margin compression dynamic.

Overhead expenses per FTE tell a different story. Here, Midsize firms showed lower growth at 4.0%, well below the Am Law 100’s 6.7% and the Second Hundred’s 5.8%. On the surface this looks like cost discipline, but it is worth reading carefully: lower overhead investment, especially when coupled with the market鈥檚 high tech and talent expenditure pressures may actually reflect forced underinvestment rather than efficiency. Midsize firms may simply have less capacity to expand their infrastructure spending, not less need for it.

Making an opposite bet on talent

Indeed, one of the sharpest contrasts in the “Q1 2026 LFFI ” data involves recruitment expenses. The Am Law Second Hundred is investing heavily in lateral talent, seeing recruitment expense growth of 5.6%. The Am Law 100 has sharply pulled back, growing recruitment costs at just 0.3% 鈥� a signal that the largest law firms may be consolidating their existing talent base rather than expanding it aggressively. Midsize firms sit at the opposite extreme, with recruitment expense growth of -0.2%, essentially flat to slightly negative.

This difference is notable because the Am Law 100 and Midsize segments are pursuing fundamentally different headcount strategies. As Am Law firms focus on leaner headcount powered by rates, Midsize firms have finding much more of their revenue growth comes from growing aggregate hours worked by hiring more lawyers. Midsize firms鈥� decision not to leverage as much investment in this area could signal a shift in strategy, simple cost pressures, or perhaps a greater focus on which areas they spend their recruiting money. Whichever the driver, it鈥檚 a sizeable shift across a segment that鈥檚 already feeling pressure across multiple facets of their business.

The compound effect of this divergence

The “Q1 2026 LFFI” data highlights several reinforcing challenges facing Midsize firms: slowing demand and lagging rate growth, the highest direct expense growth but the lowest technology investment, and minimal lateral recruitment investment. While no single factor is critical, together these divergences show a widening gap between earnings and costs.

Of course, this is not to say that Midsize firms are going bankrupt 鈥� far from it. Midsize firms鈥� profitability, on average, is growing at a solid pace as demand and rates continue to power them forward, even as expenses weigh on their numbers.

What may be more concerning is what this means for the future potential of Midsize firms, especially as the market bifurcation grows and the Am Law firms increasingly pull away. As this continues, it鈥檒l become harder and harder for Midsize firms to break into those ranks, compete for talent, and compete for the kind of bet the company work that is some of the most profitable in the legal industry. Reversing this course isn鈥檛 about Midsize firms鈥� 2026 results; rather, it鈥檚 about what they can achieve in 2030, 2040, and beyond.

You can download a full copy of the 成人VR视频 Institute鈥檚 Q1 2026 Law Firm Financial Index here

Key insights:

• • • Law firms have moved from restricting GenAI use (Don鈥檛 use tools that leak client data) to mandating it (Incorporate AI into your practice and market our firm鈥檚 GenAI capabilities)鈥斕齆either phase has given rank and file lawyers what they really need: Guidance on in which instances GenAI actually helps deliver better, cheaper, and faster legal services, where it introduces serious professional risk, and how to tell the difference.

    • GenAI鈥檚 capacity to transform legal work for the better is real, but so is its capacity to degrade it听鈥擥enAI can significantly boost speed and quality on tasks involving breadth, synthesis, or straightforward analysis, but it can weaken performance on complex judgment and revision tasks 鈥� especially for stronger professionals 鈥� by encouraging overconfidence, missed issues, and superficial reasoning.

    • A use-mode framework can close the听gap鈥� A proposed governance framework can give law firm leadership a practical tool for identifying in which situations GenAI enhances legal work, where it introduces serious risk, and where professional judgment is non-negotiable.

This article synthesizes findings from the author鈥檚 paper,

Your law firm undoubtedly has a policy around generative AI (GenAI), which probably tells lawyers to avoid tools that leak client data, admonishes them to look out for hallucinations, and encourages them to incorporate AI into their practice to satisfy client demands.

However, it likely does not tell them which cognitive functions they should delegate to GenAI, which they should not, and where the line between the two is absolute. In the space between restriction and mandate, lawyers are making consequential decisions about GenAI delegation every day. Meanwhile, most law firms have not addressed that space with meaningful governance.

GenAI can make legal work worse

GenAI鈥檚 capacity to transform legal work for the better is real, but so is its capacity to degrade it. Most law firm leaders know that AI can hallucinate; yet far fewer know that it can make expert legal judgment and work product actively worse.

The best evidence of this dynamic comes from a with consultants from the Boston Consulting Group, who were given similar tasks and allowed to use various levels of AI assistance, including no AI. For professional tasks requiring breadth and option generation, GenAI delivered, showing that output quality improved by 40% and consultants worked faster. For tasks requiring judgment and synthesis, however, something unexpected happened. Consultants using GenAI were 19% less likely to produce correct solutions than those working without it.

Governing GenAI鈥檚 uneven performance requires asking a question that most law firms are not asking: What cognitive function is being delegated to GenAI at each step in the workflow?

The same pattern appears in research evaluating GenAI use in legal analysis. An empirical in the Journal of Legal Education confirmed that AI dramatically improves performance on straightforward analysis while producing no measurable benefit for complex reasoning. And in the case of complex reasoning, GenAI use also introduced recurring failures, such as jumping to conclusions, missing less obvious issues, and generating confident prose that masks superficial analysis.

from the University of Minnesota focused on legal tasks showed that GenAI assistance on a synthesis task improved performance by nearly 60% and produced a surprising downstream benefit. Those participants who used AI for synthesis outperformed the control group on the subsequent independent reasoning task even after GenAI was removed. However, when GenAI was introduced at the revision stage, the picture changed. GenAI helped weaker performers, but it actively degraded the work of stronger ones. Indeed, the best lawyers in the study produced worse revised work product when they used GenAI than when they worked without it.

A use-mode governance framework

Given all these findings, governing GenAI鈥檚 uneven performance requires asking a question that most law firms are not asking. Instead of determining whether GenAI is appropriate for a particular deliverable 鈥� such as a brief, a contract, or a board presentation 鈥� the governance question instead should be: What cognitive function is being delegated to GenAI at each step in the workflow?

My proposed framework, outlined below, organizes common GenAI uses into seven recurring modes following the sequence in which lawyers actually use GenAI to produce legal work product. Then, governance controls are calibrated to the risk profile of each mode.

Modes 1 and 2: Retrieval and organization

At the mechanical end of the cognitive spectrum are two distinct functions. In retrieval mode (Mode 1), a lawyer reviewing a merger agreement asks GenAI to identify every representation and warranty in the document. In organization mode (Mode 2), a litigator reviewing 50 depositions asks GenAI to construct a timeline from the testimony. The first locates material that already exists. The second arranges it into a usable structure. No new content is created in either case, and both uses are low-risk and should be actively encouraged, subject to modest verification controls. Firms that unduly restrict these use modes are leaving value on the table.

Mode 3: Summarization

Summarization (Mode 3) introduces selection risk. In this mode, GenAI chooses what to emphasize, include, and omit. Consider a lawyer preparing a board presentation on the results of an internal investigation. GenAI can condense dozens of witness interviews into key points and themes in minutes; however, a summary may focus on procedural detail while missing credibility issues that a lawyer would immediately recognize as material. The appropriate control is to mandate meaningful review by a lawyer with first-hand knowledge of the source material. A lawyer encountering the summary cold has no reliable way to evaluate what GenAI missed.

Mode 4: Candidate generation

Mode 4 is exploratory. A lawyer drafting a brief might ask GenAI to generate a list of potential arguments, propose alternative framings, or identify supporting authority. This candidate material expands options and accelerates iteration. The work product is not filing-ready and must be treated as provisional. GenAI can suggest, but a lawyer must decide.

The authority verification obligation at this stage deserves special emphasis. GenAI will identify cases, summarize holdings, and weave them into an argument structure. Thus, the output will read fluently and cite real-looking cases. However, a lawyer cannot assume the model has accurately characterized the holdings or context, and any authority cited in an external filing must be independently read and verified. GenAI can help find the cases, but a lawyer must read and apply them.

Mode 5: Editing and rewriting

In Mode 5, a lawyer asks GenAI to tighten a dense contract provision or restructure a wordy paragraph, risking, of course, unintended meaning change. An edit may read cleanly while subtly narrowing a representation, softening a covenant, or eliminating a carve-out. The revision risk is not hypothetical. The University of Minnesota study referenced above found that stronger performers produced worse work product when GenAI revised their independently produced memos. In this mode, a lawyer must confirm that the edit produced no shift in meaning and introduced no new factual assertions.

Mode 6: Critique and stress-testing

Mode 6 may be the most underutilized GenAI capability. Before filing a brief or presenting to regulators, a lawyer can ask GenAI to identify weaknesses in their argument. In this way, GenAI finds vulnerabilities before adversaries do; and unlike every other mode, the risk here runs in one direction. Lawyers who skip this step are missing one of GenAI鈥檚 core value propositions. Law firms鈥� governance frameworks should not merely permit it but actually require it in appropriate cases.

Mode 7: Evaluation and decision

The boundary against AI delegation becomes absolute when GenAI is asked to evaluate or decide. A lawyer advising a board on whether an event requires disclosure cannot delegate that determination to GenAI. A litigator assessing settlement value cannot outsource probability judgments because these are core expressions of professional responsibility. In this mode, GenAI may inform background analysis, but it may not substitute for lawyer judgment in making the call. This is a categorical prohibition 鈥� professional judgment cannot be delegated.

Going forward with GenAI

Law firm leaders who have moved their GenAI policy from restriction to mandate without governing the space between have not finished the job. Their lawyers are making consequential decisions about GenAI use every day without the guidance they need and deserve.

The use-mode framework presented above gives firm leadership a practical tool for filling that gap. It identifies the instances in which GenAI enhances legal work, where it introduces serious risk, and where professional judgment is non-negotiable. Firms that govern at that level will capture GenAI鈥檚 value; and those firms that do not will have policies that look serious but govern nothing important.

The views expressed in this article are solely those of the author in his individual capacity and do not represent the views, positions, or opinions of Foley & Lardner LLP, its partners or clients, or the University of Wisconsin Law School.

Key findings:

• • • Law students understand risks and opportunities of AI use 鈥� Almost three-quarters (72%) of students surveyed say they see AI literacy as essential, while an even larger portion (74%) say they also recognize the risks of over-reliance.

    • Student AI adoption is already widespread 鈥� Almost 6 in 10 law students use AI several times per week for academic work, but much of this learning is happening through self-education rather than structured teaching.

    • AI guidance in law schools remains inconsistent 鈥� Close to a majority (48%) of students report that AI policies vary by professor, and almost one-third (32%) say that their schools do not give them the AI skills needed for their future career.

There is a significant and growing divide between how law students understand artificial intelligence and how legal institutions, such as law schools, are responding to it, according to a new 成人VR视频 Institute white paper.

Jump to 鈫�

2026 Law Student Pulse Survey

The 2026 Law Student Pulse Survey, based on responses from more than 1,800 law students that were collected in April 2026, challenges two assumptions that have long dominated institutional thinking. The first is that students are reckless adopters who use AI to bypass the hard cognitive work of legal education. The second is that students are passive and uninformed consumers of a technology they do not fully grasp. The data shows that neither characterization is accurate.

In reality, 72% of responding students identify AI literacy as an essential professional skill, while 74% simultaneously acknowledge that over-reliance on AI could undermine the development of their own core legal competencies. Holding both of these positions in tandem reflects a level of professional maturity that many institutions have yet to demonstrate in their own policies and curricula.

The survey also exposes a serious institutional gap. Nearly one-third of students report that their school does not provide the AI skills needed for their future legal careers. And nearly half indicate that AI policies vary by professor, leaving students without coherent and consistent institutional guidance on what responsible AI use actually looks like.

Far-reaching consequences

The consequences of this AI-understanding gap extend well beyond the classroom. Students are entering the workforce self-taught and inconsistently prepared, at a moment when legal employers are moving quickly to embed AI fluency into their hiring and development expectations. The profession is at risk of producing graduates who are sophisticated enough to recognize the stakes but underprepared to meet them.

The full white paper outlines specific, actionable recommendations for law schools, bar associations and accreditors, and legal employers to follow to better address this gap in AI understanding.

You can download

a full copy of the 成人VR视频 Institute’s “2026 Law Student Pulse Survey” by filling out the form below:

Key insights:

• • • A significant visibility gap persists between legal departments and the C鈥慡uite 鈥� Most general counsel believe their legal department contributes strategically, yet senior executives often fail to see or understand that value.

    • Strong internal relationship鈥慴uilding is critical (and often underdeveloped) 鈥� This capability enables legal teams to spot risks earlier, stay embedded in decision鈥憁aking, and make their work more visible across the business.

    • Closing the gap requires communicating legal鈥檚 value and increasing true AI fluency 鈥� For legal teams to be seen as proactive, strategic partners rather than task executors, communication and strong AI fluency are essential.

General counsel (GCs) have spent years doing more with less, tightening their legal spend, and aligning the law department鈥檚 priorities with the wider business. And yet, despite all of this effort, a striking visibility gap persists. While 86% of GCs believe their department is a significant contributor to overall organizational objectives, only 17% of the C-Suite agrees, according to the , from the 成人VR视频 Institute, which was based on more than 2,300 interviews with corporate general counsel. Meanwhile, 42% of C-Suite executives say the legal function contributes little or not at all to company performance.

The challenge for GCs is whether their staff have the skills and capabilities to make their work visible, relevant, and understood by the business at large. To address this perception gap in 2026, every GC needs to prioritize building richer internal relationships with business leads, moving from task-based to outcome-focused messaging, and improving the team鈥檚 collective AI fluency.

Empower teams to build internal relationships

Nearly half of all GCs surveyed for the report cited staffing and resource constraints as the top barrier to delivering additional value, a concern that has remained stubbornly consistent for years. Beyond headcount, the report underscores that the deeper challenge facing legal departments is relational.

Internal relationship-building is one of the most critical and underrated people skills in a legal department’s collective skill set. Indeed, 68% of GCs rate internal dialogue as their most valuable source of information about emerging risks. In fact, the most successful GCs use a deliberate combination of formal and informal methods to build connections with the internal business units that they serve.

You can learn more about how to assess your legal department鈥檚 strategic positioning with the听成人VR视频 Institute鈥檚 Value Alignment toolkit, here

Some run structured weekly face-to-face sessions with business departments, complete with schedules, plans, and frameworks. Others rely on walking the halls, open-door policies, and ad-hoc conversations that keep the corporate law department visible and accessible on a human level.

The report offers a five-dimensional framework to help GCs audit where, with whom, and how often legal is in dialogue with other parts of the business.

Use communication tactics that focus on business outcomes

Even when legal departments are doing excellent work, they often describe it in the wrong language. Many in-house lawyers categorize their contributions in task-based terms 鈥� such as 鈥淲e support M&A鈥� or 鈥淲e analyze contracts鈥� 鈥� rather than in value-creating terms.

Some in-house legal leaders have progressed to stakeholder-level framing, such as, 鈥淲e protect the company from competitive threats鈥� or 鈥淲e support new business opportunities.鈥� Still, neither of these levels truly communicates value to a C-Suite audience, the report shows.

To effectively align the law department’s priorities with business goals, in-house attorneys need to develop the skill of communicating through a business lens. For example, one GC states that the primary goal of the law department is to “find the fastest and most compliant way for the sales department to sell products.” This response reframes the legal function鈥檚 activities as much more business fluent and value-added.

Legal teams are not always good at touting their accomplishments, however, and this is a challenge when a lot of the work can be categorized as invisible. For example, when protecting the company is done right, threats are eliminated before they occur and no one notices. When efficiency is unlocked through process improvement, the C-Suite only sees the outcome if someone connects the dots explicitly. This is why surfacing invisible value is now a business imperative for corporate law departments.

Advancing from AI literacy to AI fluency

The most significant skills challenge facing legal departments in 2026 is how to best use AI strategically. Mentions of AI as a strategic priority among GCs have doubled in the past year, according to the report. In fact, almost half of all GCs now reference AI in their survey interviews. Yet the report draws a sharp distinction between being AI literate and being AI fluent, with most departments being the former but not the latter.

To close that gap, the report recommends a six-layer model covering learning, empowerment, ownership, accountability, usage, and expectations.

At its core, the model asks GCs to start with open encouragement and access to AI tools to build momentum, then shift toward more formal expectations around adoption to make AI use a daily habit.

You can download a full copy of the 成人VR视频 Institute鈥檚 here

Key takeaways:

• • • Efficiency is a means, not an end 鈥� Gains from AI only count when you can show what they enabled: better advice, stronger protection, smarter business support.

    • Narrow measurement invites cuts 鈥� Legal departments that measure AI value only through cost savings are telling C-Suites that legal costs less, thereby inviting budget and headcount reductions.

    • Measure across all four plates 鈥� A framework that captures effectiveness, risk, and enablement alongside efficiency is what shifts perception of the legal department from cost center to strategic asset.

Your legal department has invested in AI tools, adoption is growing, your team is saving time on routine work and, by most accounts, work operations are running faster. Then your CFO asks a simple question: What has AI delivered for the legal department?

If your answer centers on hours saved and cost reduced, you are not alone. However, you may be leaving your most important value story untold. And in a climate in which legal departments are under more scrutiny than ever to demonstrate the full return on their AI investment, that gap matters.

This is the fourth and final part of our series on the 鈥淔our Spinning Plates鈥� model, which frames the GC’s evolving responsibilities as:

1. 1. 1. delivering effective advice
      2. operating efficiently
      3. protecting the business, and
      4. enabling strategic ambitions.

This article focuses on the Efficient plate and specifically on the risk of letting it do too much of the talking.

The Efficient plate under pressure

For a GC, making the best use of what are often limited resources is a constant pressure. The Efficient plate sits alongside, not above, the other three plates and must be kept always spinning. Right now, however, for many in-house legal teams the Efficient plate is receiving disproportionate attention, and for understandable reasons.

AI adoption in corporate legal departments is accelerating quickly. According to the 成人VR视频 Institute’s AI in Professional Services Report 2026, nearly half (47%) of corporate legal respondents surveyed said their department has already integrated generative AI (GenAI) into their work 鈥� more than double the figure from the previous year. A further 18% reported that they鈥檙e already using agentic AI, with more than half expecting agentic AI to be central to their workflow within the next two years.

GCs are genuinely excited about what this makes possible. As one GC said in the survey that underpinned the AI in Professional Services Report: “It presents the promise of getting out of low-value work and into higher-value work that supports the business.鈥� Another described their vision of a legal department that is “boldly digital-first, relentlessly innovative, and tightly woven into business priorities.”

Clearly, the opportunity is real, but so is the risk of measuring it badly.

The measurement trap

Our 2026 research found that only one-quarter of legal departments are currently measuring the ROI of their AI tools. That alone is striking given the pace of adoption but the follow-up finding is where the real problem lies 鈥� of those departments that are measuring ROI, 80% are tracking it in terms of internal cost savings.

Reducing external spend, automating high-volume processes, and bringing more work in-house are all legitimate efficiency gains and worth reporting, of course. However, when cost reduction becomes the only story being told, two things can happen. Your C-Suite learns to associate your department’s value with how little it costs, a frame that is very difficult to escape once it鈥檚 established. And the wider value that efficiency enables in terms of sharper risk identification, faster business support, and higher-quality advice goes unmeasured and therefore unrecognized.

听If your metrics only capture time saved and cost reduced, and not what that freed-up capacity actually delivered, you are measuring the means and ignoring the end.

Think about what GCs themselves say they want from AI. As several GCs said in the survey, they鈥檙e hoping AI will provide them with “better output on more meaningful tasks,” “proactive, strategic insight,” and “getting out of low-value work.” These are not efficient outcomes, per se; rather, they are effectiveness, protection, and enablement outcomes, made possible by improved efficiency.

So, if your metrics only capture the input (time saved, cost reduced) and not what that freed-up capacity actually delivered, you are measuring the means and ignoring the end. This is the efficiency trap 鈥� measuring the plate so narrowly that it starts to work against you.

Reframing how you measure efficiency

Measuring efficiency well does not mean measuring it more. It means measuring it differently, and always in relation to the business you support. A few principles worth applying include:

Present spend in a business context 鈥� Legal spend as a percentage of company revenue tells a more credible story than a raw cost figure. It scales with the business and can be benchmarked meaningfully against peers.

Show what technology investment actually delivered 鈥� Time saved through automation is a useful starting point, but the stronger case is what the team did with that time. Tracking the shift from routine to strategic work over a period of time is a far more compelling ROI story.

Connect efficiency gains to business outcomes 鈥� An efficiency gain that enabled a faster product launch, prevented a compliance risk, or improved stakeholder satisfaction has a value that no cost metric will capture. Build those connections explicitly into how you report the value of the legal department to the C-Suite.

New resources to help

To support GCs in getting this right, the 成人VR视频 Institute has added two new resources to its Value Alignment Toolkit that directly address this measurement gap.

The Metrics Library brings together more than 100 metrics organized across all four spinning plates. It is a practical starting point for GCs to browse, select, and adapt to the specific goals of their departments, making it easier to build a measurement framework that reflects everything departments do, not just the part that appears in a budget line.

The AI Success Metrics guide addresses the AI measurement gap head-on with a best practice guide and a hands-on worksheet designed specifically for legal departments navigating AI adoption and asking: How do we actually know whether this is working? It looks beyond cost savings to capture the fuller picture of AI value including quality, capacity, strategic contribution, and risk.

Getting the balance right

In today鈥檚 environment, every GC needs to consider their answer when their C-Suite asks what the legal department delivers. Are your department鈥檚 metrics giving them the full answer or just the part that’s easiest to count?

Efficiency is not the enemy of strategic value. A department that runs well, uses its resources wisely, and embraces technology thoughtfully can in turn create the conditions for everything else the business needs from its legal function. However, that case only lands if your metrics measure across all four plates, not just one.

You can explore the new Metrics Library and AI Success Metrics guide, along with the full 成人VR视频 Institute鈥檚 Value Alignment toolkit听here

Key takeaways:

• • • Violence against judges is escalating 鈥� Targeted shootings, coordinated harassment campaigns, and threats that now routinely follow judges to their homes and families.

    • The rhetoric driving the escalation is coming from the highest levels of government 鈥� The absence of any public denunciation from the Department of Justice is highlighting the source of the problem.

    • Will the violence itself become part of judicial rulings? 鈥� The endgame of judicial intimidation isn’t that judges stop ruling, it’s that the threat of violence becomes a silent presence in the deliberation itself.

NEW YORK 鈥� Those attendees who came to the recent听 to talk about AI, agentic workflows, and the business of legal technology, also were treated to a session that will likely stay with attendees and had nothing to do with AI.

In that session, four federal judges took the stage; but they were not there to talk about pricing models or AI adoption. They were there to talk about staying alive.

Setting the stage

Jason Wareham, CEO of IPSA Intelligent Systems and a former U.S. Marine Corps judge advocate, introduced the session 鈥� a panel of four sitting United States District Court judges 鈥� by speaking of how the rule of law once seemed resolute, yet how that faith in that has been shaken, year after year. He worked hard to frame his observations as nonpartisan, a matter of institutional fragility rather than political allegiance. It was a generous framing, but it was one that would not survive the weight of the ensuing discussion.

The Honorable Esther Salas of the District of New Jersey said that the reason she was there has a name. On July 19, 2020, a disgruntled, extremist attorney who had a case before her court arrived at her home during a birthday celebration. He shot and killed her twenty-year-old son, Daniel Anderl. He shot and critically wounded her husband. She has spent the years since on a mission to protect her judicial colleagues from the same fate.

The new normal

Next, the Honorable Kenly Kiya Kato of the Central District of California described what has changed. Judges鈥� rulings are still based on the Constitution, on precedent, and on the facts; but what’s different is the small voice in the back of a judge’s head. That voice, often coming after a judge issued a decision that they now have to fight against, asks: What will happen after this? It is now expected, Judge Kato explained, that a high-profile order will bring threats. When two colleagues in her district issued prominent decisions, her first thought was for their safety. That is not how it has been historically.

The Honorable Mia Roberts Perez of the Eastern District of Pennsylvania asked how we got here, pointing to language from the highest levels of government: judges called monsters, a U.S. Department of Justice declaring war on rogue judges, and recently politicians bringing justice鈥檚 families into the conversation.

Judge Salas pushed even further. She acknowledged the instinct to frame the problem as bipartisan, but said the current moment is not apples to apples. It is apples to watermelons. The spike in threats since 2015, she argued, traces directly to rhetoric from political leaders using language never before deployed against the bench.

The federal judiciary is looking to break annual records for threats [against judges], and there is an absence of any public denunciation from the Attorney General or the DOJ.

The evidence is not abstract, nor are the victims, and the panel walked through it. Judge John Roemer of Wisconsin, zip-tied to a chair and assassinated in his home. Associate Judge Andrew Wilkinson of Maryland shot dead in his driveway while his family was inside. Judge Steven Meyer of Indiana and his wife Kimberly, shot through their own front door after attackers first posed as a food delivery, then returned days later claiming to have found the couple’s dog. Judge Meyer has just undergone his fifth surgery since the attack.

All of these incidents happened at the judges’ homes.

Judge Salas then played a voicemail, one of thousands that federal judges receive. It was less than 30 seconds long, but it did not need to be longer. While names had been redacted, what remained was a torrent of threats and obscenities, graphic, sexual and violent, delivered with the confidence of someone who does not expect consequences. Some judges receive hundreds of these after a single ruling, often from people with no case before them at all.

The shadow over the courts

Throughout the session, there was a presence the panelists circled but rarely named directly. A shadow that shaped every observation about escalating threats, every reference to rhetoric from the top down, every mention of language never before used by political leaders, of action or inaction the likes of which would have been unthinkable just several years ago. The specifics were spoken. The name, largely, was not.

It didn’t have to be.

Judge Kato said that what was perhaps the most disheartening aspect of all this is that these threats are getting worse. The people who know better are not doing better. Indeed, she said her children think about these problems every day. What will happen to mom today? Will someone come to the house? These are questions children should not have to carry. They did not sign up for this, and neither did the judges.

In 2026, Judge Salas noted, the federal judiciary is looking to break annual records for threats. She also noted the absence of any public denunciation from the Attorney General or the DOJ. The silence, she said, says a lot.

Not surprisingly, the implications extend beyond the judges themselves. As Judge Salas noted, if judges have to weigh their safety alongside the law, ordinary people don’t stand a chance. If one party is stronger, better funded, or more willing to threaten, then the scales tip.

That is the endgame of judicial intimidation. It鈥檚 not that judges stop ruling, but that the violent and the powerful 鈥� indeed, the people least fit to hold the scales 鈥� can tilt them at will.

That concern echoed an earlier warning from Judge Karoline Mehalchick of the Middle District of Pennsylvania. Judge Mehalchick said that judicial intimidation feeds on misunderstanding. When the public no longer grasps why judges must be insulated from pressure or conversely, mistakes independence for partisanship, the threat environment becomes easier to justify, easier to ignore, and harder to reverse.

What is perhaps the most disheartening aspect of all this is that these threats are getting worse, and the people who know better are not doing better.

In his 2024 year-end report, U.S. Supreme Court Chief Justice John Roberts identified four threats to judicial independence: violence, intimidation, disinformation, and threats to defy lawfully entered judgements. The panel discussed this report as prophecy fulfilled. Public confidence in the judiciary has plummeted since 2021, and the reasons are complex. The judges insisted they are still doing their jobs the right way, but the violence is spreading anyway.

What survives

Judge Salas asked the audience to watch their thoughts. Are they negative and destructive, or positive and uplifting? Can we start loving more? She ended by sending love and light to everyone in the room.

The judges were visibly emotional on the stage.

The words were beautiful. They were also, in the context of everything that had just been described 鈥� the killings, the voicemails, the zip ties, the pizza deliveries masking a threat under a murdered son’s name 鈥� resting in a shadow that no amount of love and light could fully dispel on their own.

The room responded with a standing ovation.

Thousands of people came to Legalweek 2026 to talk about the future of legal technology. For one morning, four judges reminded them that none of it matters if the people charged with administering justice cannot do so safely.

So, while the billable hour may survive and the associate will adapt, the harder question, the one that should keep the legal industry awake at night, is whether the bench will hold.

You can find more of听our coverage of Legalweek events听here

• • • AI is already reshaping the legal profession 鈥� AI听is already embedded in lawyers’ day-to-day legal work with a significant share of both law firm attorneys and in-house legal teams actively using GenAI tools, with many expecting it to become central to their work within the next five years.

    • AIFLP Advisory Board was formed to prepare lawyers for an AI-reshaped profession 鈥� TRI convened 21 respected leaders from legal education, private practice, the judiciary, and AI ethics and governance to help ensure lawyers and law students are prepared for a profession reshaped by AI.

    • Human judgment remains central in an AI enabled legal future听鈥� Becoming AI ready is not simply about learning to use new tools; the Advisory Board emphasizes strengthening irreplaceable human capabilities is critical.

In today鈥檚 tech-driven environment, AI is no longer a future concept for the legal profession 鈥� it鈥檚 already here, and it鈥檚 changing how lawyers work, learn, and serve clients. Recognizing just how fast the evolution is moving, the 成人VR视频 Institute (TRI) has launched the AI and the Future of Legal Practice (AIFLP) Advisory Board, bringing together a group of respected leaders from across the legal ecosystem to help guide what comes next.

The board includes 21 accomplished voices from legal education, private practice, the judiciary, and AI ethics and governance. Their shared goal is simple but ambitious: Help ensure that both today鈥檚 lawyers and tomorrow鈥檚 law students are prepared for a profession being reshaped by AI.

Why now?

Because the shift is already underway. According to TRI鈥檚 recent 2026 AI in Professional Services Report, 41% of law firm attorneys say their organizations are already using some form of generative AI (GenAI); and nearly half of those at corporate legal departments report that AI tools are being rolled out there too. Even more telling, most professionals said they expect GenAI to become central to their day鈥憈o鈥慸ay work within the next five years.

That pace of change raises big questions about competence, ethics, education, risk, and access to justice. And those questions don鈥檛 have easy answers.

What the Advisory Board will focus on

The AIFLP Advisory Board is designed to tackle those challenges head鈥憃n. Its work will center on four key areas that are already under pressure as AI adoption accelerates:

• • • Legal education and talent development
    • Ethics, professional competence, and accountability
    • Governance, risk management, and client counseling
    • Access to justice and modern service delivery

The Advisory Board鈥檚 early focus areas will look at how AI is actually changing legal practice today, what future鈥憆eady lawyers really need to know, and how legal education and real鈥憌orld practice can better align. The emphasis is not just on using AI tools, but on strengthening the human skills that matter most, such as sound judgment, critical thinking, and careful verification of AI鈥慻enerated outputs.

Shaping the future, not reacting to it

Citing the critical need for this Advisory Board鈥檚 creation, Mike Abbott, Head of the 成人VR视频 Institute, notes that the legal profession is at a crossroads, and it can either react to AI鈥慸riven disruption or take an active role in shaping how these technologies are used to support lawyers, courts, and the public.

鈥淏y assembling a board of distinguished leaders, our goal is to help practicing lawyers and the lawyers of the future navigate a rapidly evolving landscape,鈥� Abbott said. 鈥淓nsuring that legal education strengthens irreplaceable skills such as critical thinking, human judgment and effective communication helps make AI use safe and effective. The Board鈥檚 efforts will ultimately help shape a future-ready profession, leading to better outcomes for all.鈥�

Meet the AIFLP Advisory Board Members

By convening experienced leaders from across the profession, TRI hopes to help lawyers navigate this landscape with confidence. Advisory Board Members include:

• • • Michael Abbott, Head of the 成人VR视频 Institute
    • Soledad Atienza, Dean of IE Law School (Spain)
    • The Honorable Jennifer D. Bailey, (Ret.), Partner, Bass Law
    • Benjamin Barros, Dean, Stetson University College of Law
    • Professor Sara J. Berman, University of Southern California, Gould School of Law
    • Megan Carpenter, Dean Emeritus, University of New Hampshire Franklin Pierce School of Law
    • Ronald S. Flagg, President, Legal Services Corporation
    • Donna Haddad, AI Ethics and Governance expert, and founding member, IBM AI Ethics Board
    • Nick James, Executive Dean of the Faculty of Law at Bond University (Australia)
    • Johanna Kalb, Dean and Professor of Law, University of San Francisco School of Law
    • The Honorable Nelly Khouzam, Florida Second District Court of Appeal
    • The Honorable William Koch, Dean, Nashville School of Law, and former Tennessee Supreme Court Justice
    • Sheldon Krantz, retired partner, DLA Piper, and a founder, DC Affordable Law Firm
    • Stefanie A. Lindquist, Dean, School of Law, Washington University in St. Louis
    • The Honorable Mark Martin, Founding Dean and Professor of Law, Kenneth F. Kahn School of Law at High Point University, and former Chief Justice, Supreme Court of North Carolina
    • Caitlin (Cat) Moon, Professor of the Practice and founding co-director, Vanderbilt AI Law Lab, Vanderbilt Law School
    • Hari Osofsky, Myra and James Bradwell Professor and former Dean, Northwestern Pritzker School of Law; Founding Director, Northwestern University Energy Innovation Lab; and Founding Director, Rule of Law Global Academic Partnership
    • Joanna Penn, Chief Transformation Officer, Husch Blackwell
    • The Honorable Morris Silberman, Florida Second District Court of Appeal
    • The Honorable Samuel A. Thumma, Arizona Court of Appeals, Division One
    • Mark Wasserman, Partner and CEO Emeritus, Eversheds Sutherland
    • Donna E. Young, Founding Dean, Lincoln Alexander School of Law, Toronto Metropolitan University

What鈥檚 next?

The Advisory Board held its first meeting in February and will meet quarterly going forward. As the work progresses, TRI plans to publish research findings, best practices, and practical recommendations for legal educators, law firms, and courts.

In a profession built on precedent and careful reasoning, the rise of AI presents both opportunity and responsibility. The AIFLP Advisory Board is an effort to make sure the legal community meets that moment thoughtfully and on its own terms.

You can learn more about the impact of advanced technology on the legal profession here