A recent podcast discussed a case where AI was used in an accelerated litigation as an excellent example of how to win at trial using AI.

The episode of the podcast Law disrupted, hosted by John B. Quinn, Founder and chairman, Quinn Emanuel Urquhart & Sullivan was titled Winning at Trial with AI, and his guests were Quinn Emanuel Partner Christopher Kercher and Jeffrey Chivers, Co-Founder of Syllo AI. The 35-minute discussion is available here.

In the podcast, Kercher and Chivers discuss the use of AI in a recent “bet-the-company fight” over a $183 million merger. The case presented a significant challenge due to the extremely short timeline from engagement to trial (six weeks) and a looming drop-dead date for the merger. This compressed schedule demanded rapid and efficient handling of massive discovery obligations, including reviewing tens of thousands of documents.

Syllo’s work with Quinn Emanuel was documented in their recent whitepaper Agentic AI Document Review Is Transformative for Complex Litigation (which we covered here), which provides ten real world examples of the use of Syllo AI in actual cases.

The practical applications of AI in the case included:

Document Review and Organization: Reviewing massive quantities of documents using Syllo AI, tagging them, organizing them, and creating chronologies. Notably, Syllo AI facilitated categorizing the documents into 35 different categories, which allowed the team to find critical documents expeditiously, streamlining deposition and trial preparation.

Targeted Document Identification: Using natural language prompts to find documents relevant to specific ideas or themes, going beyond traditional keyword searches. As Quinn noted, summarizing Kercher’s point: “I want to make the case X, I want to argue X. Give me all the documents that supports it.”

Analyzing Adversary’s Production and Privilege Logs: Using AI to identify deficiencies in the opposing side’s document production and scrutinize the validity of privilege log entries. As Chivers noted: “There was a point in the case where the Quinn team wanted to do an analysis of the deficiencies in the other side’s production. And so we, in a period of about 48 hours, made changes to our automated review tool to have it perform more of a deficiency analysis function.”

Brainstorming and Strategy Development: Using Claude AI as a “daily thought partner” to brainstorm legal arguments, identify potential weaknesses, and explore different strategic approaches.

Drafting and Editing Legal Documents: Utilizing Claude AI to improve clarity, conciseness, and tone in legal writing, including briefs.

Deposition Preparation: Using AI to analyze documents and suggest effective ways to deploy them during cross-examination.

What did the use of AI mean for the case? Here are a couple of other considerations discussed in the podcast:

AI as a Force Multiplier and Essential Tool: Both Kercher and Chivers emphasize that AI, specifically platforms like Syllo and Claude, acted as a “force multiplier” for the legal team. It enabled a small group of lawyers to handle a workload that would traditionally require a much larger team within the given timeframe. As Kercher noted: “in the right hands of very skilled litigators, it’s a tool that is a force multiplier for your brain.”

The “Mental Models” and Domain Specificity of Syllo AI: Chivers explained that Syllo AI is specifically designed for litigation by attempting to replicate the “mental models” or ways of thinking that lawyers use when analyzing legal problems and documents. This domain-specific approach, combined with the ability to utilize and combine multiple underlying AI models, leads to more accurate and relevant output for litigators compared to general-purpose LLMs.

Could not using AI be considered malpractice? As Quinn stated: “I can foresee a time when it’s going to be malpractice not to use this capability.” Kercher concurred, stating: “I think so, too”

One thing AI is already doing is helping lawyers focus more on strategic work. As Chivers noted: “What I’m seeing is that lawyers really are spending more time on the strategic parts of the litigation… It’s like speed to insight, speed to pivot. You’re going to end up spending the same amount of time, but where you land is a much better compelling case.”

People keep asking when we’re going to see compelling examples of how AI can really benefit lawyers in actual cases. This case provides a clear example of how to win at trial using AI and doing so when the stakes are high!

Again, a link to the episode of the podcast is here, and Syllo’s white paper with several real world examples (including more details about this one) where AI has been leveraged to help lawyers in case is here.

So, what do you think? Is this a compelling example of how to win at trial using AI? Please share any comments you might have or if you’d like to know more about a particular topic.

Image created using Microsoft Designer, using the term “robot judge reading a verdict at the end of a high stakes trial”.

Disclosure: Syllo is an Educational Partner and sponsor of eDiscovery Today.

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