In the gold rush of generative AI, it seems that every legal tech vendor wants to be a one-stop shop for legal technology. But after 15 years of developing legal tech, Nik Reed, CEO of Knowable, a legal technology company devoted to helping enterprises bring order and organization to their executed agreements, believes that lawyers should be wary of the hype. Often, the most successful AI solutions are those that focus on solving specific problems exceptionally well rather than attempting to be all things to all lawyers. 

On today’s LawNext, Reed joins host Bob Ambrogi for a conversation that explores what makes legal AI actually work well in practice. It is a topic he has been thinking about, in one form or another, since he was still a student at Stanford Law School, where he co-founded the legal research startup Ravel with classmate Daniel Lewis in 2012. After LexisNexis acquired Ravel in 2017, Reed moved into strategic product management there, and then joined Knowable in 2019 to lead its product research and development. He became the company’s CEO last November, just as the company launched Ask Knowable, its generative AI suite. 

In a conversation that explores what makes legal AI actually work in practice, Reed emphasizes the critical importance of pristine data environments, high-quality metadata, and clearly defined use cases. “It's still hard to build really good products, especially for lawyers, and it takes a lot of hard work,” Reed says. “ And anyone that's telling you that that's not the truth is probably already a product that you shouldn't be using.”

But ultimately, he believes, AI has the potential to restore balance to legal practice by handling the rote work lawyers never wanted to do, allowing them to return to what they went to law school for – critical reasoning and solving complex problems.

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