Riding the wave of ChatGPT’s explosive rise in late 2022, a host of vendors have developed generative, AI-based tools for use throughout the contract lifecycle.
“It’s not often in an industry as old-fashioned as legal that there are huge shifts in the way we work and think about work, and we’re experiencing them now,” said Chris Young, general counsel of Ironclad, a platform dedicated to contract lifecycle management.
In addition to drafting and reviewing, generative AI can use contract datasets for strategic insights to mitigate risk and negotiate, manage, and review contracts.
Using generative AI trained on a company’s previous models for contract review holds promise, some say.
“That’s where you see a lot of the key efficiency gains,” says Ironclad’s Young, who is both a customer and partner of OpenAI. “At Ocrolus, one of our customers, contract volume increased by more than 90 percent” in the first nine months of using Ironclad. “But the time it took them to negotiate contracts fell by 50%.” He said in August that 60% of Ironclad customers had adopted its AI programs in the past six months.
Contract redlining also benefits from a trained generative AI platform. The Ironclad AI Playbooks tool allows the terms of a contract to be compared against the company’s list of acceptable clauses and provisions for that type of transaction.
“You can dynamically negotiate an AI that supports contracts and have a work product that reflects where your company is from a risk profile perspective – what is acceptable to that legal department,” says Young.
In contract data extraction, the rise of chatbots makes it easy for people outside the legal department to find out what’s in their contracts, says Gaurav Oberoi, CEO and co-founder of Lexion, a contract lifecycle management software company.
“The value of this is to help the company’s self-service questions: ‘Hey, do we have an NDA with so-and-so? Will there be innovation soon? And when it comes to innovation, is there a price ceiling on how much we can increase?’”
Knowing what’s in the company’s contracts is critical, Young says. “If you don’t have standardization in your contracts, it is difficult to say where you stand as an organization.”
Still, some implementation details for contract analytics can be tricky, says Noah Waisberg, co-founder and CEO of Zuva, an AI-powered document processing platform.
For example, searching for a single assignment clause can often be time-consuming. Furthermore, while generative AI can draft contracts, the need for accuracy is so great that using a trusted template may be a better starting point.
“If you get GPT to do it, you actually have to read it – and I would say that takes longer,” says Waisberg, co-author of AI for Lawyers: How Artificial Intelligence Is Adding Value, Amplifying Expertise and Transforming Careers.
Others question the long-term time-saving capabilities of AI-powered tools. Ken Adams, chief content officer of LegalSifter, warns that training AI on poorly written contracts or contracts with bad data can lead to less than ideal results.
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This story was originally published in the February-March 2024 issue of the ABA Magazine.