Generative Legal @ Cornell Tech

I will be opening this gathering (confirmed speakers are listed here as well). It will cover the following topics:

01

Kick-off

State of the Tech

What’s actually possible with legal AI today, and what’s still on the horizon? This opening presentation offers a grounded overview of the current state of generative AI for legal applications — how foundation models are evolving, which breakthroughs matter most for legal work, and where the technology still falls short. Attendees leave with a clear-eyed understanding of AI’s capabilities and its limits.

02

Keynote

Fireside conversations

Two fireside-style keynote Q&As punctuate the day — candid, on-stage conversations with leaders shaping the intersection of law and AI. Speakers will be announced closer to the event.

03

Panel discussion

The Client Perspective

What do in-house leaders actually want from AI-enabled law firms? Hear directly from the people buying legal services about their expectations for outside counsel. Are they demanding AI-driven efficiencies? Do they trust AI-assisted work product? How are they weighing a firm’s AI capabilities in pitches and panels? This session surfaces the client voice and helps firms understand where the market is heading.

04

Panel discussion

The Legal Team in 2029

The legal team of 2029 may prove a meaningful departure from today’s. As AI absorbs the junior work that once filled the ranks and sustained the billable hour, teams are adding engineers and other AI specialists in their place. Alongside this, what that team can actually do turns increasingly on access to frontier models, compute, and data. This session convenes leaders rethinking who sits on the legal team, how their work should be priced, and whether frontier technology will continue to be available to lawyers across markets.

05

Debate

“This house would build, not buy.”

Before a tribunal of three judges, the proposition will argue that legal teams should own the application layer: tailored legal AI, built either from the ground up or on an open-source foundation. The opposition will argue that the better course for a primary tool is a commercial legal AI platform, however customized.

AI and Legal Education

Eflon CC BY 2.0

I was interviewed in the Forum (Cornell Law School’s Alumni Magazine) about AI and Legal Education. It reads, in part:

When she first began her legal studies at Cornell, [Jessica Rosberger ’26] says many students didn’t want to disclose they were using AI (“it felt like academic dishonesty”) but now it is “explicitly discussed” and used as a tool in studies and research. “I feel confident now going into practice to understand how the technology is evolving. I don’t know where it’s going, but I want to keep up with it,” says Rosberger, who joins the Manhattan District Attorney’s office after graduation. “In my view, Cornell is maintaining its integrity as a top law school by integrating AI into coursework and clinics. We have a professional responsibility to keep up with the technology and the platforms available to us.”

This sense of responsibility is especially evident at Cornell Tech, which offers courses and programs—including a Master of Laws (LL.M.) in Law, Technology, and Entrepreneurship degree—bringing together experts in engineering, computer science, design, business, and law “to build the foundations for new digital technologies—especially AI.”

“Our faculty are thought leaders in artificial intelligence and machine learning,” says David Reiss, clinical professor of law and research director of the Blassberg-Rice Center for Entrepreneurship Law. “The Law School has always been committed to ensuring that our graduates are practice ready. The integration of AI into the curriculum provides them with better tools. It will make them better lawyers and give them a leg up in practice.”

Reiss co-authored an article in Bloomberg Law explaining why law schools should teach how to integrate AI into practice. “Different AI products lead to wildly different results. Just demonstrating this to law students is very valuable, as it dispels the notion that AI responses can replace their independent judgment,” writes Reiss. Simulations were designed in which students were asked to complete the same transactional tasks, like drafting a contract or creating a client email, using different AI tools. The results were different because each platform drew from different sources or used different algorithms to interpret language—some provided a helpful first draft, while others did not, or even hallucinated.

“Our goal is student learning. It was for this reason that we like to deploy the AI tools at the end of our exercises: You do the work and then interrogate it with the AI tools of your choice,” explains Reiss. Just recognizing the capacity for different platforms to produce different results is critical. “AI is not a replacement for lawyers. We want our students to understand how it can be an enhancement for lawyers. It can increase efficiency and help meet tighter deadlines. The lawyers who adapt to AI will succeed and those who put their heads in the sand will fall behind.”

    *     *     *

Some law students are already trying to improve AI for practical usage. When Biying Cheng ’25 was at Cornell Tech’s Entrepreneurship Clinic, she assisted a client who designed an AI chatbot to help tenants deal with landlord issues and housing court. “We devised questions to test what level of detail the chatbot could and should provide, considering legal liability and jurisdictional issues,” says Cheng, who was already comfortable with AI. “I’m not a native speaker, and ChatGPT helped me draft emails, outline memos, and find resources. I called it Professor G and asked it to explains words I was unfamiliar with.”

Cheng’s pursuit of a J.D. came after receiving a master’s in international finance from Columbia University and a B.A. from The Chinese University of Hong Kong. Her work with the AI chatbot was a full-circle moment for someone who had witnessed Chinese students in Hong Kong participating in protests because of a serious housing problem. She saw how the law and AI could help New York City tenants facing housing issues. Cheng also co-authored an article with Professor Reiss on the real world impact of crypto and blockchain on tenants and real estate investors.

“The legal industry tends to be pretty conservative,” says Cheng, who now clerks for the U.S. District Court, Eastern District [of New York]. “But lawyers should want to become fluent in AI as a way to understand how it can impact lives in better ways.”

“We’re going to look to our younger colleagues to move us forward,” says Reiss. He believes that AI can help “refine legal judgment” with the right kind of prompting and critical review. AI can help lawyers “stress test” their own reasoning , identify blind spots, and learn about novel issues.