Artificial Intelligence

Vanderbilt Law School recently launched an exciting new initiative called the Vanderbilt AI Legal Lab (VAILL) to explore how artificial intelligence can transform legal services and access to justice. In this episode, we spoke with VAILL’s leadership – Cat Moon,(👑) Director of Innovation at Vanderbilt’s Program on Law and Innovation (PoLI), and Mark Williams, Associate Director for Collections and Innovation at the Massey Law Library – about their vision for this pioneering lab. 

VAILL’s mission is to harness AI to expand access to legal knowledge and services, with a particular focus on leveraging generative AI to improve legal service delivery. As Moon described, VAILL aims to experiment, collaborate widely, and build solutions to realize AI’s potential in the legal domain. The lab will leverage Vanderbilt’s cross-disciplinary strengths, drawing on experts in computer science, engineering, philosophy, and other fields to inform their ethically-grounded, human-centered approach.

VAILL is prioritizing partnerships across sectors – courts, law firms, legal aid organizations, alternative providers, and others – to test ideas and develop prototype AI applications that solve real legal needs. For instance, they plan to co-create solutions with Legal Aid of North Carolina’s Innovation Lab to expand access to justice. Moon explained that generative AI presents solutions for some legal challenges, so VAILL hopes to match developing technological capabilities with organizations’ needs.

Ethics are foundational to VAILL’s work. Students will learn both practical uses of AI in law practice as well as broader policy and social implications. As Williams emphasized, beyond core professional responsibility issues, VAILL aims to empower students to lead in shaping AI’s societal impacts through deeper engagement with questions around data, access, and algorithms. Teaching ethical, creative mindsets is VAILL’s ultimate opportunity.

VAILL will leverage the resources and expertise of Vanderbilt’s law librarians to critically assess new AI tools from their unique perspective. Williams noted that the lab sees law students as a “risk free” testing ground for innovations, while also equipping them with adaptable learning capabilities to keep pace with AI’s rapid evolution. Rather than viewing AI as a differentiator, VAILL’s goal is producing legally-skilled innovators ready to thrive amidst ongoing change.

Vanderbilt’s AI Legal Lab represents an exciting development in exploring AI’s legal impacts. By emphasizing human-centered, ethical approaches and collaborations, VAILL aims to pioneer solutions that expand access to legal knowledge and services for all. We look forward to seeing the innovative applications VAILL develops at the intersection of law and AI.

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Transcript

Continue Reading TGIR Ep. 228 – Cat Moon and Mark Williams Launch the New Vanderbilt AI Law Lab (VAILL)

This week on The Geek in Review podcast Marlene Gebauer and Greg Lambert featured guests Colin Levy, Ashley Carlisle, and Dorna Moini discussing Levy’s recently published book “Handbook of Legal Tech.” Levy edited the book and contributors included Moini, Carlisle’s CEO, Tony Thai, and many more legal technology experts. The book provides an overview of key technologies transforming the legal industry like automation, AI, blockchain, document automation, CLM, and more.

Levy shared how he ended up editing the book, describing it as “herding cats” to get busy experts to contribute chapters. He wanted the book to serve as a comprehensive introduction to legal tech, with each chapter written by leaders in the various subject matter areas. Carlisle and Moini explained their motivations for taking time out of their demanding schedules to write chapters – spreading knowledge to help move the industry forward and impart insights from their work.

The guests reflected on their favorite parts of the experience. Levy enjoyed bringing together the community and seeing different perspectives. Carlisle appreciated being able to consolidate information on contract lifecycle management. Moini was proud to contribute right before having a baby. Lambert highlighted Levy juggling this book and writing his own solo book on legal tech stories from the front lines.

The guests offered advice to law students and lawyers looking to learn about and leverage legal tech. Carlisle emphasized starting with an open mind, intentional research, and reading widely from legal tech thought leaders. Moini recommended thinking big but starting small with iterative implementation. Levy stressed knowing your purpose and motivations to stay focused amidst the vast array of options.

Lambert prompted the guests to identify low-hanging fruit legal technologies those new to practice should focus on. Levy pointed to document automation and AI. Moini noted that intake and forms digitization can be a first step for laggards. Carlisle advised starting small with discrete tasks before tackling advanced tools.

For their forward-looking predictions, Carlisle saw AI hype fading but increasing tech literacy, Levy predicted growing focus on use and analysis of data as AI advances, and Moini forecasted a rise in online legal service delivery. The guests are excited about spreading awareness through the book to help transform the legal industry.

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Transcript:Continue Reading Colin Levy, Dorna Moini, and Ashley Carlisle on Herding Cats and Heralding Change: The Inside Scoop on the “Handbook of Legal Tech”

On this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert delve into how AI can transform legal writing with ClearBrief founder and CEO Jacqueline Schafer. As a former litigator, Schafer experienced firsthand the frustrating scramble to finalize briefs and prepare filings. She founded ClearBrief in 2020 to leverage AI to analyze documents and suggest relevant evidence and citations to streamline drafting.

ClearBrief integrates into Microsoft Word to align with lawyers’ existing workflows. By uploading case documents and discovery materials, the AI can pull facts and quotes directly from the record to support legal arguments in the brief. New features even generate chronologies and timelines from case files automatically. Schafer explains the AI doesn’t hallucinate text from scratch, avoiding ethical pitfalls. Rigorous security and confidentiality controls provide the trust needed to gain adoption at top law firms.

According to Schafer, attorneys now exhibit much greater openness to tailored AI tools that enhance productivity versus disrupting their workflows entirely. Younger associates and paralegals tend to be most enthusiastic about the technology while firm leadership lags. She believes empowering the next generation of legal professionals with AI will modernize law practice to better serve unmet needs.

Looking ahead, Schafer expects to expand ClearBrief’s features to assist paralegals along with corporate attorneys beyond litigation. By leveraging AI to handle tedious tasks like cite-checking, lawyers can focus their time on high-value analysis and strategy. With the aid of trusted AI writing assistants, attorneys can craft compelling briefs and filings more efficiently while still verifying the underlying sources.

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Transcript:Continue Reading Jacqueline Schafer on Writing Briefs at the Speed of AI: How ClearBrief is Transforming Legal Drafting

On this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert interview Thomas Suh, Founder and CEO, and Ken Block, Senior Account Executive of LegalMation. The company provides AI-powered tools to help litigators automate repetitive tasks and work more efficiently. The conversation focuses on LegalMation’s products, overcoming resistance to adopting new legal tech, and predictions for the future evolution of legal service delivery.

Suh provides background on founding LegalMation about seven years ago to help streamline the “scut work” litigation associates spend time on. The flagship product automates drafting responses to lawsuits, discovery requests, demand letters, and more by leveraging a firm’s historical data. LegalMation initially built an automation tool internally at a law firm before deciding to spin it off into a standalone legal tech company. The product found an early champion in the form of a corporate legal department interested in licensing it. Today, LegalMation serves large corporate legal departments, law firms, and insurance companies.

Suh and Block discuss common roadblocks to adopting new legal technology like lack of trust and skepticism. Suh notes the importance of identifying the right use cases where efficiency gains matter most. For high-stakes litigation, efficiency may be less of a concern than for high-volume routine matters. Corporate legal departments are often early adopters because they are focused on efficiency and supplementing personnel. Law firms still incentivized by billable hours may be warier of efficiency gains.

For the YouTube Viewers, Block demonstrates LegalMation’s Response Creator tool for automating drafting of responses to complaints and discovery requests. The AI leverages a firm’s historical data to maintain proper tone and style while speeding up document preparation significantly. Lawyers can still review and edit the AI-generated drafts before finalizing. Suh explains that because the AI relies solely on a firm’s data, it maintains consistency rather than attempting to generate random creative language.

Looking ahead, Suh predicts that the litigation process will become more modular, with different firms or providers specializing in discrete phases rather than handling a case end-to-end. Block emphasizes that younger lawyers expect to leverage more technology and are unwilling to slog through repetitive manual tasks, which will force law firms to adapt. Technology stacks and automation will become selling points for recruiting top young talent.

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Transcript

Continue Reading Thomas Suh and Ken Block on How LegalMation is Revolutionizing Litigation Efficiency (TGIR Ep. 222)

In this episode of The Geek in Review, hosts Marlene Gebauer and Greg Lambert have an illuminating discussion with Christina Wojcik, the new Managing Director of Corporate for LexFusion. Christina has over 20 years of experience pioneering innovation in the legal services and technology space.

The conversation covers Christina’s diverse background and journey into legal tech, including formative experiences at companies like Pangea3, IBM, Seal Software, and Citi. She shares key lessons learned about the importance of visionary leadership, solving real client problems, and embracing a fearless, entrepreneurial spirit.

Christina provides insights into top pain points for legal departments today, especially at highly regulated organizations like major banks. She discusses the cautious approach many are taking with emergent technologies like generative AI—treating it like a “monster behind the door” to be carefully studied before fully unleashing.

Christina advocates for “failing fast” when testing innovations, allowing for rapid iteration in a safe sandbox environment. She explains her rationale for joining LexFusion and how she hopes to leverage her well-rounded expertise to drive value for legal tech providers and clients alike.

The conversation concludes with Christina’s predictions for the legal industry’s evolution in areas like AI adoption, CLM consolidation, and new service delivery models. She provides a fascinating insider perspective on the future of legal innovation.

https://open.spotify.com/episode/3B4A7EFJBE1WzqUteJXXRr?si=mOC-OyQ4Qhe1glFffLysdg

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Transcript

Continue Reading Unleashing the Legal Monster Behind the Door – LexFusion’s Christina Wojcik (TGIR Ep. 221)

This week we are joined by Brandon Wiebe, General Counsel and Head of Privacy at Transcend. Brandon discusses the company’s mission to develop privacy and AI solutions. He outlines the evolution from manual governance to technical solutions integrated into data systems. Transcend saw a need for more technical privacy and AI governance as data processing advanced across organizations.

Wiebe provides examples of AI governance challenges, such as engineering teams using GitHub Copilot and sales/marketing teams using tools like Jasper. He created a lightweight AI Code of Conduct at Transcend to give guidance on responsible AI adoption. He believes technical enforcement like cataloging AI systems will also be key.

On ESG governance changes, Wiebe sees parallels to privacy regulation evolving from voluntary principles to specific technical requirements. He expects AI governance will follow a similar path but much faster, requiring legal teams to become technical experts. Engaging early and lightweight in development is key.

Transcend’s new Pathfinder tool provides observability into AI systems to enable governance. It acts as an intermediary layer between internal tools and foundation models like OpenAI. Pathfinder aims to provide oversight and auditability into these AI systems.

Looking ahead, Wiebe believes GCs must develop deep expertise in AI technology, either themselves or by building internal teams. Understanding the technology will allow counsels to provide practical and discrete advice as adoption accelerates. Technical literacy will be critical.

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Transcript

Continue Reading Observing the Black Box: Transcend’s Brandon Wiebe’s Insights into Governing Emerging AI Systems (TGIR Ep. 218)

This is part 3 in a 3 part series.  Part 1 questions Goldman’s Sachs data showing that 44% of of legal tasks could be replaced by Generative AI.  In Part 2, we find some better data and estimate an upper limit of 23.5% of revenue that could be reduced by Generative AI. All of our assertions and assumptions will be discussed in further detail in a free LVN Webinar on August 15th.

The Big Idea:  We apply reductions in hours due to Generative AI to a few matters to determine Generative AI’s potential effect on profitability.
Key Points:
  • We establish a baseline sample matter and compare changes to that sample matter when Generative AI is applied
  • We explore how leverage is affected by Generative AI and how those changes may affect profitability in unexpected ways

Determining Generative AI’s effect on law firm profitability requires a bit more than a “back of the napkin” calculation with rough percentages based on keywords in time entries, as we did when roughly calculating the effect on revenue.

As Toby pointed out at the end of the last post, Generative AI is unlikely to hit all timekeepers equally.

We begin with this assertion.

Generative AI will disproportionately impact non-partner hours.

We are comfortable making this assertion for two reasons:

  1. Generative AI, in its current state, is most likely to replace or shorten the time to complete lower complexity and lesser specialized tasks that should be performed at the associate or paralegal level.
  2. Any time legal work hours are reduced, Partners tend to protect their own hours.

With that in mind, Toby began a profitability analysis, beginning with a baseline sample matter that does not factor in any use of Generative AI. We will use this baseline to compare against our AI adjusted matters.


Baseline M&A Sample Matter Data

Our baseline sample matter is loosely modeled on an M&A transaction and includes 5 timekeepers:

  • an Equity Partner
  • a 17th year service partner
  • 10th, 7th and 3rd year associates
TK Hours Rate Realization Revenue Expense Profit
EP 80 $1,000 88% $70,400 $15,200 $55,200
SP17 100 $895 88% $78,760 $48,500 $30,260
10yr 125 $735 88% $80,850 $48,750 $32,100
7yr 90 $660 88% $52,272 $32,400 $19,872
3yr 55 $595 88% $28,798 $18,150 $10,648

Estimated Annual Profit Per Equity Partner (PPEP) – $1,851 X 1400 hrs = $2,591,400

Leverage – 60% Non-Partner Hours


There are, of course, a number of assumptions in this baseline data that could greatly change from firm to firm, including the billable rates, the realization rate, and the expense for each timekeeper. However, we will keep this baseline data consistent across all of our examples in order to make a fair comparison. With different rates, realization, and expenses you will get different results. We strongly encourage every firm to perform a similar calculation for themselves.

Baseline Matter Analysis

The total hours billed are 450. The total revenue is $311k and the total profit in dollars is $163k.

Our model then translates the profit on this one matter into an estimated PPEP number for the firm. This is so we can determine profit margin impact separate from profit dollars.

In this baseline model, the PPEP number is ~$2.6m; meaning that if all work at this firm were staffed and billed like this one matter, the firm average PPEP would be about $2.6m.

Leverage

There’s an old adage in economic circles: “Workers Work. Owners Benefit.”
Continue Reading AI-Pocalypse: The Shocking Impact on Law Firm Profitability

by 3 Geeks (Ryan McClead, Greg Lambert, and Toby Brown)

This is part 2 in a 3 part series. The first part is here. Part 3 is here.

The Big Idea: We found a much better dataset, though still small, from which to extrapolate actual effects of Generative AI on the legal industry.

Key takeaways:

  • We got anonymized and summarized data for 10 corporate legal departments from LexisNexis CounselLink
  • The data showed that almost 40% of time entries, representing 47% of billings, could potentially use Generative AI.
  • We estimate that a realistic initial upper limit for Generative AI would be to reduce that work by half, or 20% of time entries and 23.5% of revenue

In the previous post, Ryan got tired of hearing the Goldman Sachs “44% of Legal is going away” stat being quoted uncritically and decided to actually look into the underlying data used in their report. Ryan’s exploration of the data is an interesting story in and of itself, but the bottom line is that the data is fuzzy at best, the sample size is laughable, and the breathlessly unquestioning reporting on Goldman’s study has been remarkably sloppy.

After writing up his findings, Ryan shared that post with Greg and Toby, and the question quickly arose, “can we find some actual, useful data to better understand the effect that Generative AI might actually have on law firms?” Gregreached out to Kris Satkunas from LexisNexis CounselLink, a recent interviewee on the Geek in Review, to see if CounselLink could share some anonymized benchmark data for us to analyze.

LexisNexis CounselLink Data

As a reminder the Goldman data was using survey questions about how important certain “work tasks” were for their jobs. Those tasks included things like “Getting Information”, “Identifying Objects, Actions, and Events”, and “Scheduling Work and Activities”. These are quite vague and wide open to interpretation.

In an attempt to find more useful data for our purposes, we asked Kris for the percentages of all time entries that included the keywords “Draft” or “Review” in the description. Our assumption is that those two terms will capture a large percentage of actual time entries in which lawyers are likely to use Generative AI. We fully recognize that this simple heuristic will not produce a clean data set from which to extrapolate definitive results, but as a first pass at some real data, we believe this gives us a nice estimate of tasks that could potentially be ripe for automation with Generative AI.
Continue Reading Generative AI Could Reduce Law Firm Revenue by 23.5%

This is the first in a 3-part blog post, it first appeared on The Sente Playbook.  The other 2 posts are co-authored by Toby Brown and Greg Lambert and will follow later this week. Apologies for the length of this post, but I was channeling my inner Casey Flaherty.
The Big Idea:  The data that Goldman used is insufficient to make the claims about Generative AI’s effect on legal that their report did.
Key Take-Aways:
  • Reporting about this report is sloppy
  • Reporting within this report is sloppy
  • The underlying data doesn’t tell us much meaningful
  • 3 Geeks attempts to find meaningful data
On March 26th, 2023 Goldman Sachs sent shockwaves through the legal industry by publishing a report claiming that 44% of “something” in the Legal Industry was going to be replaced by Generative AI.  I didn’t question that stat at the time, because it sounded about right to me.  I suspect that was true for most people who know the legal industry.  As I’ve heard this stat repeated by multiple AI purveyors actively scaring lawyers into buying their products or services, I eventually started to question its validity.
I started by looking into the press coverage of that 44% number and was immediately confused.  (All emphasis below added by me.)

Law.com  – March 29, 2023
Generative AI Could Automate Almost Half of All Legal Tasks, Goldman Sachs Estimates
“Goldman Sachs estimated that generative AI could automate 44% of legal tasks in the U.S. “

Observer – March 30, 2023
Two-Thirds of Jobs Are at Risk: Goldman Sachs A.I. Study
“The investment bank’s economists estimate that 46% of administrative positions, 44% of legal positions, and 37% of engineering jobs could be replaced by artificial intelligence.

NY Times – April 10, 2023
A.I. Is Coming for Lawyers, Again
“Another research report, by economists at Goldman Sachs, estimated that 44 percent of legal work could be automated.”

Okay, so which is it?  Generative AI is going to replace 44% of legal tasks, positions, or work?
Because those are 3 very different things; each of which would have extremely different impacts on the industry if they came to pass.  Lest you think I cherry-picked three outlying articles, go ahead and Google “AI Replace 44% Legal Goldman Sachs” and see what you get.  Those 3 articles are in my top 5 results.
My top result as of this writing is a news article from IBL News, writing last Tuesday that Goldman says,  “AI could automate 46% of tasks in administrative jobs, 44% of legal jobs, and 37% of architecture and engineering professions.”
We should probably just go back to what the Goldman Sachs report actually said and then we can chalk this up to lazy tech journalism.  Well, not so fast.  Because while the Goldman researchers clearly say “current work tasks” (see below) even that begins to fall apart once you dig into the underlying data.

What Goldman Sachs actually said in the report

Continue Reading 44% of Investment Bankers Think They Can Make Lots of Money Off of Attorney Insecurity (AI)

Tony Thai and Ashley Carlisle of HyperDraft, return to The Geek in Review podcast to provide an update on the state of generative AI in the legal industry. It has been 6 months since their last appearance, when the AI Hype Cycle was on the rise. We wanted to get them back on the show to see where we are on that hype cycle at the moment.

While hype around tools like ChatGPT has started to level off, Tony and Ashley note there is still a lot of misinformation and unrealistic expectations about what this technology can currently achieve. Over the past few months, HyperDraft has received an influx of requests from law firms and legal departments for education and consulting on how to practically apply AI like large language models. Many organizations feel pressure from management to “do something” with AI, but lack a clear understanding of the concrete problems they aim to solve. This results in a solution in search of a problem situation.

Tony and Ashley provide several key lessons learned regarding limitations of generative AI. It is not a magic bullet or panacea – you still have to put in the work to standardize processes before automating them. The technology excels at research, data extraction and summarization, but struggles to create final, high-quality legal work product. If the issue being addressed is about standardizing processes or topics, then having the ability to create 50 different ways to answer the issue doesn’t create standards, it creates chaos.

Current useful applications center on legal research, brainstorming, administrative tasks – not mission-critical legal analysis. The hype around generative AI could dampen innovation in process automation using robotic process automation and expert systems. Casetext’s acquisition by Thomson Reuters illustrates the present-day limitations of large language models trained primarily on case law.

Looking to the near future, Tony and Ashley predict the AI hype cycle will continue to fizzle out as focus shifts to education and literacy around all forms of AI. More legal tech products will likely combine specialized AI tools with large language models. And law firms may finally move towards flat rate billing models in order to meet client expectations around efficiency gains from AI.

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⁠⁠TranscriptContinue Reading You Still Need to Put in the Work: Hyperdraft’s Ashley Carlisle and Tony Thai on the AI Hype Cycle (TGIR Ep. 213)