Law firms are building AI around their most valuable asset: experience

For generations, a law firm’s most valuable asset walked out the door every night.

It was the attorney who remembered the clause that saved a deal years ago.

The trial lawyer who knew which arguments worked on a judge and which ones didn’t.

The partner who told an associate, “We’ve seen this before.” Now law firms are racing to turn that expertise into software.

After spending the past two years adopting tools from OpenAI, Harvey, Microsoft, Legora, and others, large law firms are building systems around something more valuable: what only they know.

The bet is that artificial intelligence steeped in their deal histories, trial strategies, and client preferences will be more useful than whatever the firm across the street can buy.

Law firms are spending big to bottle their secret sauce.

Earlier this year, Kirkland & Ellis agreed to pay Palantir $500 million to build technology for one of the firm’s core businesses: advising private equity clients on raising money.

Latham & Watkins bought its own Nvidia servers to start customizing large language models.

At Morgan & Morgan, America’s largest personal injury law firm, lawyers have begun using an in-house artificial intelligence model trained to recognize patterns in their cases.

A younger lawyer might miss that a patient showing signs of a pinched nerve near the spine could later require surgery.

The firm says its software can flag that possibility. “Our best and experienced people will spot it almost immediately,” said Yath Ithayakumar, Morgan & Morgan’s chief transformation officer. “But if you’re a first-year attorney, this is your first job, maybe that’s not as obvious to you.

Technology makes a huge difference.” This story is part of a series called The AI Data Grab, an inside look at how tech giants are increasingly turning to workers, users, and the physical world to get data to train AI.

Read more stories in this series here.

That is the promise behind Morgan & Morgan’s push to build its own technology.

The firm, which has said it will spend $1 billion on the effort over the next decade, isn’t trying to compete with OpenAI.

It wants to capture what its best lawyers already know.

Many law firms already use the same high-tech tools.

Harvey says it has users at 80% of the country’s 100 largest law firms by revenue.

Legora says it covers a majority of the same firms.

When everyone can buy the same systems, the edge has to come from what those systems know, said Mary O’Carroll, chief executive of the LegalEng Consulting Group, a boutique legal consulting firm based in San Francisco.

If a firm has “done every private equity deal for all of time and has a corner on the market,” the prize is being able to use that history so lawyers can say, in effect, “I have the knowledge of 50,000 deals in my back pocket,” she said.

That helps explain why Morgan & Morgan is going so far as to build its own technology.

The firm sits on decades of case files showing how its attorneys have handled injuries, discovery fights, settlements, and trials.

Its history is not just a record of work done.

It is the raw material these systems need to be useful. “We have more data than anybody else,” Ithayakumar said. “We have to be good stewards of it.” Responsible use starts with control.

Morgan & Morgan has to be careful about who gets access to its data, what they’re allowed to do with it, and whether outside vendors can retain or learn from it, Ithayakumar said.

And before the firm can use its data to spot patterns across cases, it has to strip away any details that could identify the people behind them.

That need for control has opened a new lane for tech companies.

Harvey wants to do for law firms what Palantir is doing for Kirkland & Ellis.

This year, Harvey took an open-weight model and trained it further for legal work.

Eventually, it wants to help firms do something similar with their own matters.

LexisNexis and Thomson Reuters, owner of Westlaw, see a similar opening.

Both built massive businesses by collecting cases, statutes, and regulations, then layering them with their own editorial analysis.

Next, they pushed into the software lawyers use to draft, research, and review documents.

Now they are moving closer to the models themselves.

Thomson Reuters is offering customers access to Thomson, a model trained on 150 years of its own content.

LexisNexis says it’s aiming for a similar future: models grounded in both its legal corpus and a firm’s own data.

Law firms asked for it, said Sean Fitzpatrick, chief executive of global legal at LexisNexis. “All of the models can do things in a similar way,” he said.

What sets them apart “is the content and the context that those models have.” For all the money flowing into these custom systems, it’s too soon to tell whether the winners will be the firms with the most data or the software companies that help them use it.

What everyone seems to agree on is the direction of travel.

The next fight in legal technology is not over who has the smartest software.

It’s over who gets to own what the software knows.

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