REFinBlog

Editor: David Reiss
Cornell Law School

September 30, 2026

Generative Legal @ Cornell Tech

By David Reiss

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.

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