Welcome to Original Jurisdiction, the latest legal publication by me, David Lat. You can learn more about Original Jurisdiction by reading its About page, and you can email me at davidlat@substack.com. This is a reader-supported publication; you can subscribe by clicking here.
Portions of this article originally appeared on Bloomberg Law, part of Bloomberg Industry Group, Inc. (800-372-1033), and are reproduced here with permission. Both the text and the footnotes contain material that didn’t appear in my Bloomberg Law column—a form of bonus content for Original Jurisdiction subscribers.
The number of AI-native law firms is exploding, many of them founded by associates frustrated with Biglaw’s pace on artificial intelligence. But partners are also leaving, drawn by AI’s potential to be what Cravath partner turned boutique founder Benjamin Gruenstein called a “force multiplier.”1
The latest leading litigator to depart from a storied firm is Chris Kercher. After more than 17 years at Quinn Emanuel, where he represented clients such as Elon Musk and Ken Griffin, Kercher left to launch his own boutique, Kercher Law.
Why did Kercher leave Quinn Emanuel—one of the world’s most prestigious and profitable law firms, with more than $9 million in profits per equity partner—to hang a shingle?
The short version of his answer can be summed up in a word: AI. The long version rests on certain timeless aspects of law and the legal profession—which make Kercher confident that lawyers aren’t going anywhere.
‘The same job Abraham Lincoln had’
Kercher has spent the past three years exploring possible applications of AI in his practice as a commercial litigator, making him an early adopter in Biglaw. He founded the AI and Data Analytics Group at Quinn Emanuel, as a laboratory of sorts to explore how the firm’s lawyers could better leverage AI. He has taught classes about AI at Stanford Law and NYU Law, his alma mater.
These experiences led Kercher to reflect on the direction of his legal career. As he told me in an interview, “I’m around 25 years into my legal career, and I started asking myself: What do I want to do for the next 25 years?”
And his deep understanding of AI caused him to ask fundamental questions about the practice of law and the role of lawyers: “Where does a human fit in? Clients have Claude; clients have ChatGPT. Why are they coming to lawyers?”
“And the answer is, they have a dispute,” he said. “It’s the same job, in many ways, that Abraham Lincoln probably had: Clients come in with a problem, you advise them, you counsel them, you strategize, maybe you negotiate.”
“But at the end of the day, if you have to walk into court and advocate for them, that’s why they build courthouses. And much of that work in the middle, between the client coming in and advocating for the client in court, can be assisted and augmented by AI.”
Returning to first principles
As much as he loved his time at Quinn Emanuel, Kercher felt that starting his own firm would best allow him to explore AI’s full potential.
“To really understand what you can do with this new technology, you have to get closer to the work,” he explained. “I want to understand, as matters come in, what help do I really need? What is the right role for an associate, for a paralegal, for software or AI?”
“When you’re in a system and you’re in a process, that is the system, that is the process, and it’s difficult to reinvent from first principles,” he said. “Launching my own firm presented the rare opportunity to start with a blank slate, with something brand-new and unconstrained.”
Historically speaking, much of what clients paid for was what Kercher called “context assembly.” In a big-ticket litigation or transaction, “you had all these documents, all these facts, all these memos, all this legal research”—and clients paid for a large number of (very expensive) lawyers to put it all together.
Today, AI can handle much of this context assembly, such as document review or due diligence. This shift has profound implications for the architecture of a law firm: how matters are staffed, how work flows, how young lawyers are trained, and how clients are billed. And in Kercher’s view, building a new firm from the bottom up is the best way to integrate AI into every aspect of running a law firm and serving one’s clients.
“If you look at electrification and early industrial work, factory owners would take their factories and add a light bulb here, a motor there,” he said. “But Henry Ford designed the Highland Park plant by asking, ‘What if we build electricity throughout the factory? What if we just assume that electricity exists, so we can get its benefit in everything we do?’ And that’s how I’m looking at building, from day one, the systems to bring this all together.”
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‘Flipping the risk’
One area where AI should bring major transformation is billing, according to Kercher.
When context assembly had to be done by associates, billing by the hour made sense for law firms because it insulated them against downside risk. If a matter turned out to be more complex or difficult than originally expected—making it more expensive to service, by requiring more associates—the firm was protected, since it was getting paid for the additional billable hours. The client bore most of the risk.
But now, in Kercher’s words, context assembly “has been largely de-risked,” since it can be done primarily—and far more cheaply—by AI.
“So one simple change I’m making is just ‘flipping the risk,’” Kercher said. “I’m leaning hard into ‘fixed fee by phase’ billing, so clients can always understand the cost to get to the next level—while also knowing that they can always step off the treadmill at any time.”
Fixed-fee billing—whether by phase or by matter, which Kercher said he’s also open to discussing—limits the client’s risk (which is why clients like it), while exposing the firm to more risk. But if a case “blows up,” the impact to the firm is now limited thanks to AI, since much of the extra work “can be handled by compute, rather than associates.”2
By capping the client’s risk, fixed-fee billing provides the client with more certainty and comfort. This could make clients more willing to litigate, based on the greater predictability about what it might cost—in turn generating more work for firms.3
So as some work goes away thanks to AI, new work will emerge—which is one of the reasons that Kercher isn’t worried about the long-term future of lawyers and the legal profession.
“If you think about legal as a percentage of GDP, I really don’t think it goes down,” he predicted. “What the transition to the future looks like, including the shape of the work, is an open question. But at the end of the day, the system will work it all out. Our goals—advocating for our clients, helping them achieve their objectives—haven’t changed.”
‘It’s just going to be called litigation’
Kercher has spoken publicly about using specific, cutting-edge tools to litigate cases, such as Claude to strategize and Syllo AI to review documents.4 But at the end of the day, he has an old-fashioned view of litigation.
“‘AI-native’ is a term you see thrown around a lot, especially on the transactional side,” he said. “On the litigation side, I think it’s much more interesting—and it’s just going to be called ‘litigation.’ It’s not ‘AI-native litigation,’ but litigation with an understanding of how we can use AI and technology more generally to get more out of our work and to really extend ourselves.”
“The robots are not coming—at least not for lawyers who can stand up in court and persuade a judge, persuade a jury, and win the case,” he said. “The most protected part in law is that endpoint: the person who’s doing the advocacy, conducting the negotiation, presenting to the board.”
In the end, Kercher described himself as “incredibly bullish” on how AI will affect lawyers and the legal profession. Noting that the practice of law is one of civilization’s most enduring professions, he predicted that “it’s never going away, because it’s how we mediate conflict.”
AI might eliminate certain tasks—or, to be more precise, the ability of lawyers to make money from performing those tasks. But Kercher is confident it won’t eliminate clients’ underlying needs.
As Kercher put it, “What’s left? What’s left is human disputes. Human disputes are not going anywhere.”
For more about Ben Gruenstein and his decision to leave Cravath, Swaine & Moore to launch Gruenstein Law, check out our podcast conversation, which I posted yesterday.
Of course, as Kercher mentioned, even a fixed-fee arrangement might include provisions allowing the firm to bill more than originally anticipated in truly exceptional or extreme situations. But he also acknowledged that there might be cases where a firm takes a financial hit because of a fixed-fee arrangement—where a firm might “get punched in the face,” as he put it (paraphrasing Mike Tyson)—and smart firms will learn from those experiences, using that data to improve their pricing for future cases.
As Gary Wingens, chair of Lowenstein Sandler, put it in a piece for Bloomberg Law, “As work becomes faster and cheaper, clients will buy more of it, not less. In practice, that means matters that clients once deferred, narrowed, or abandoned can suddenly become economically viable and move from a client’s ‘nice to have’ bucket to the active docket.”
I saw a demo of Syllo AI back in 2024, and I was blown away—and I can’t imagine how powerful it must be today. So I wasn’t surprised by last month’s news of the partnership between Syllo and Kirkland & Ellis, which plans to invest $500 million in AI over the next three to four years. For more about Syllo and AI-powered document review more generally, check out this white paper, Agentic AI Document Review Is Transformative for Complex Litigation (to which Chris Kercher contributed as a practitioner).
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