Supreme Court Lawyer's AI Prep Claims Draw Criticism From Peers
Neal Katyal, a Milbank partner and former acting solicitor general, won a tariff case before the Supreme Court in November and credited an AI tool for helping him prepare. In a TED Talk released Thursday, he said a custom AI system trained on 25 years of Supreme Court records predicted not just the justices' questions but their eventual opinions.
The court ruled 6-3 in favor of the business coalition challenging President Donald Trump's global tariffs. Katyal argued the case after winning a coin flip with another advocate.
His public credit for the victory prompted swift pushback from legal scholars and court watchers. Multiple critics said his framing suggested he single-handedly won a case that involved dozens of amicus briefs and multiple elite law firms.
What Katyal Said
In the talk, filmed in Vancouver last month, Katyal described bringing four coaches to prepare for oral argument: a mindfulness coach who worked with tennis player Andre Agassi, an improv coach, a meditation coach, and Harvey, an AI model built by Harvey AI, a San Francisco legal tech company.
Katyal displayed Harvey's predicted questions next to the actual oral argument transcript, saying some matched "almost verbatim." He credited the tool with identifying what he called an "escape route" to persuade Chief Justice John Roberts.
"Harvey glimpsed that narrow door, I held the door open, the Chief Justice walked through it," Katyal said.
He acknowledged how his presentation might sound. "I know how this sounds," he said. "Lawyer wins a big case, gets a fancy TED Talk invitation, talks for 14 minutes about how great he is."
The Pushback
Daniel Epps, a professor at Washington University School of Law, said the comments came across as "arrogant" and could damage Katyal's standing with the justices. Epps, who clerked for Justice Anthony Kennedy, said Katyal sounded as though he could manipulate the justices and change their votes.
"I think he's really damaged his credibility with them," Epps said.
Xiao Wang, who directs the University of Virginia's Supreme Court Litigation Clinic and has argued twice before the justices, said high court advocates are only one part of winning cases. "I thought it was a little strange for the quarterback here to say there is in fact an 'I' in team," Wang said.
Critics posted on social media and published columns on the National Review website and The Volokh Conspiracy, a legal blog hosted by Reason magazine.
The Broader Picture
Katyal later credited his legal team in a social media post promoting the talk, naming fellow Milbank partner Colleen Roh Sinzdak and the Liberty Justice Center, which organized the business plaintiffs.
Harvey AI said in an email it has no arrangement with Katyal to promote its services and he holds no investment stake in the company. Katyal did not respond to requests for comment.
The case underscores how legal professionals increasingly use AI tools for case preparation. Wang said Supreme Court advocates will likely adopt the technology for digital moot courts if many haven't already.
Harvey's client list includes Walmart, Comcast, and O'Melveny & Myers. The company said its tools have been used to prep for at least one other Supreme Court case this term.
What Experts See in AI Prediction
Mitu Gulati, a University of Virginia law professor who studies the Supreme Court, said the value of AI prediction tools lies in identifying patterns in how justices question and reason through cases. Advocates prize consistency from the bench, and knowing the justices follow logical patterns is reassuring, he said.
"It's not that they're outcome-driven, regardless of argument," Gulati said.
Even if Katyal overstated the AI model's role, Gulati said the talk highlighted the preparation and performance skills that make Katyal valuable for high-stakes Supreme Court work.
"Everybody reads everything and it's hard to imagine oral argument changed anybody's vote," Gulati said. "That said, if you can change a vote, that's why you pay the guy."
For legal professionals interested in how AI tools apply to case preparation and legal research, resources on AI for Legal work and AI learning for paralegals offer practical guidance on current applications in law practice.
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