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Robot lawyers are thriving during the pandemic



This is the web version of Eye on A.I., Fortune’s weekly newsletter covering artificial intelligence and business. To get it delivered weekly to your in-box, sign up here.

A lot of A.I. companies are having a good year—and that includes those who sell A.I.-enabled tech to lawyers.

Last week, I spoke with Jason Brennan, the chief executive officer of U.K.-based legal A.I. company Luminance. He told me the company, which now has more than 250 customers across the globe, including a fifth of the world’s largest 100 law firms, has had a 30% increase in customers since the start of 2020.

Luminance has an interesting history: It was founded in 2015 by a group that included Mike Lynch, the former founder and CEO of one-time star U.K. technology company Autonomy. (Lynch is fighting extradition to the U.S. on fraud charges and is awaiting a verdict in a civil fraud suit in the U.K.) Lynch’s Invoke Capital has been one of Luminance’s biggest funders, but the company is also backed by venture capital firm Talis Capital and the big U.K.-based law firm Slaughter & May (which was also one of Luminance’s first customers and, what’s more, has represented Lynch in the past).

Luminance’s machine learning platform uses some elements of natural language processing, the kind of machine learning that can understand language, and some elements of clustering, a machine learning discipline focused on, as the name suggests, grouping data based on similarities and differences.

Clustering is one of the unsupervised learning techniques (ones that don’t rely on a pre-labeled training data set) that are increasingly gaining ground in business applications. In the case of Luminance, its system uses both unsupervised learning and supervised methods—while its software knows that a certain set of documents are similar, it doesn’t know what they are until a human lawyer training the system applies a label to them. Once the document set is labelled, the system can learn to predict the right label for akin documents it encounters in the future.

The result is a system that can tell lawyers which documents—and importantly, which clauses within documents—are most similar and which are outliers.

This is important because it turns out that a lot of the “grunt work” of Big Law involves doing exactly what Luminance does: combing through vast troves of documents, trying to find those clauses that might be problematic. Maybe they need to be updated due to a regulatory change. Or maybe they are part of the contracts held by a company that is being acquired and would open up a big liability issue for the buyer. Either way, law firms once deployed small armies of paralegals and junior associates to find them. It used to be that law firms could simply charge for all this labor and pass the cost on to the client. But that hasn’t been true for at least a decade. These days, clients are more likely to demand law firms accept a flat fee for this sort of work, or pay based on some pre-agreed outcome, not on man hours. So firms have had to become much more efficient. Corporate in-house legal departments are also having to do more with less.

That’s good for Luminance. And Brennan tells me that during the pandemic, the company has seen its customers use its A.I. in novel ways. Take the Italian law firm Portolano Cavallo and the U.K. arm of the global firm Dentons. Both firms found their clients needed to quickly determine if any contracts had force majeure clauses and exactly how they could be triggered. “It’s the idea of needing to pivot very quickly to something new and unforeseen,” Brennan says. “Force majeure clauses have been out there forever, but the relevance of it couldn’t be predicted.” Using Luminance, both Dentons and Portolano were able to complete this task in record time—in fact, Portolano says in a client newsletter that it was able to complete a document review that might have taken many days in just 45 minutes.

Brennan says he’s seen other interesting uses such as companies gaming out which creditors might be on the hook in potential bankruptcies, investigating M&A transactions as many industries brace for consolidation, and even preparing for possible class action lawsuits against the cruise line industry.

Like many A.I. company CEOs, Brennan says his customers are not simply using his product to cut costs. He says A.I. is also enabling them to find new revenue streams. For instance, in the past, in big M&A transactions, the likes of the Fortune 500 would engage a big global law firm to conduct a due diligence review of contracts above a certain pre-agreed dollar value. It was simply too onerous and too expensive to look at everything. And, once a merger actually came together, the work of integrating the combined firms’ contracts was often farmed out to smaller law firms, since it was too pricey to get a large one to do it, Brennan says. But now A.I. systems such as Luminance are allowing the big firms to offer comprehensive document reviews and actually retain the post-merger integration work. At the same time, they’re also allowing some smaller firms to compete for work that they wouldn’t have had the manpower to handle before, he says.

So, how long will it be until we have fully robotic lawyers? Well, Brennan thinks the day when software like Luminance will actually perform legal analysis—assessing which clauses are most likely to trigger a legal issue, for instance—is still a long way off. “We want lawyers to be lawyers,” he says. “Right now we are focused on highlighting information to lawyers and letting them do what they do best.”

And with that, here’s the rest of this week’s A.I. news.

Jeremy Kahn

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