Legal Ops Leaders Less Afraid of AI, but Many Still Haven't Adopted Tools
Though a lot of the fear factor seems to have decreased around artificial intelligence, that doesn't mean that every legal department is jumping right in.
February 07, 2018 at 03:52 PM
4 minute read
The conversation around artificial intelligence in legal departments is constantly evolving—much like the technology itself.
In 2018, legal ops leaders said in-house discussions about AI are characterized more by excitement than fear. That's a change from not too long ago, when some of the legal community buzzed with anxiety that AI meant job loss.
“It [AI] is not something to be fearful of. It's just another software. It will not replace humans,” said Connie Brenton, chief of staff and senior director of legal operations at NetApp Inc. “It's simply an efficiency tool just like all the other software. It looks [like] magic, but it takes elbow grease to get it running, and exponential investment.”
Brenton said the positive change in perception could stem from more familiarity with the technology in the legal ops field. Through organizations like the Corporate Legal Operations Consortium, which Brenton leads as CEO, she said department leaders have more exposure to new AI technologies and can discuss their views on how the tools work in practice.
“It's not like it was 10 years ago where every department found out [about technologies] on its own,” she said. “We're sharing use cases, [and] sharing best practices on how to implement.”
NetApp's legal department has been evaluating and beta testing new technologies including AI, so Brenton's been able to speak with fellow CLOC members about the training and investment involved. She can also share NetApp's experiences with new technologies' efficiency gains and returns on investment.
That type of sharing is one reason legal departments that aren't necessarily very tech-forward have begun to warm up to the thought of in-house AI use, even if they haven't actually implemented these tools yet, said Anand Rao, a principal with PricewaterhouseCoopers' U.S. advisory practice who has worked extensively with AI in legal departments.
“Mid-tier players are waiting [for] a stage where the big players have tried it, and seeing how those players come through, then [they will] go to them and then customize it to get the job done and reduce their cost,” Rao said.
Ameen Haddad, assistant general counsel at Oracle Corp. and a member of Oracle's legal operations group said that he hasn't seen fear of AI replacing jobs in the legal ops field for a while, but he has seen companies wary of investing in AI too soon.
“We're trying to adopt things we know tested and worked well and we're very interested in seeing how the technology develops, but [we're] still at the beginning stages of some of it,” Haddad said.
That wariness played out in recent data from HBR Consulting's Law Department Artificial Intelligence Survey, in which only 6 percent of legal department respondents said they currently have AI tools or are piloting them.
Haddad and Brenton both noted that smaller legal departments may be drawn to new AI technology at a faster pace, to make up for having a smaller staff and less bandwidth to get work done.
But Frances Pomposo, the operations director of legal, privacy, ethics and compliance for Workday Inc. said that while small and midsized legal departments may be tempted by AI's financial benefits and efficiency, they can face unique barriers to AI installment.
Smaller departments may not have enough data or cases to sufficiently train AI tools. If a company doesn't yet have a set process to standardize nondisclosure agreements and other contracts, AI won't be helpful, she said, as it's best used for tasks that repeat frequently. If there's not much repetition in contracts or elsewhere, AI isn't a good first investment.
“Where I've worked, it [AI] is something we've looked into, but it's not highest priority,” she said. “Because if you're just setting up a department and you have to look at implementing a contract system or implementing AI, the obvious choice is to implement the base-level operations first.”
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