ABA Journal

Legal Rebels Profiles

e-Sign on the Dotted Line: When it comes to using generative AI and contracts, the devil is in the details

By Julianne Hill

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Riding the waves of ChatGPT’s explosive entrance in late 2022, a host of vendors have developed generative artificial intelligence-powered tools for use throughout the contract life cycle.

“It is not often in an old-school industry like legal for there to be monumental shifts in how we work and think about work, and we’re undergoing one now,” says Chris Young, general counsel of Ironclad, a platform devoted to contract life cycle management.

Along with drafting and reviewing, generative AI can leverage contract datasets for strategic insights to help mitigate risk and negotiate, manage and assess contracts.

Using generative AI trained on a company’s past models for contract review holds promise, some say.

“That’s where you see a lot of the key efficiency gains,” says Young of Ironclad, which is both a customer and partner of OpenAI. “At Ocrolus, one of our clients, contract volume increased 90-plus percent” in the first nine months it used Ironclad. “But the time it took for them to negotiate contracts decreased 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. With the Ironclad AI Playbooks tool, a contract’s provisions can be compared to the company’s list of acceptable clauses and provisions for that type of transaction.

“You can dynamically negotiate a contract-leveraging AI and have a work product that reflects where your company is from a risk-profile standpoint—what’s acceptable for that legal department,” Young says.

In contract data extraction, the rise of chatbots allows people outside the legal department to easily learn what’s in their contracts, says Gaurav Oberoi, CEO and co-founder of Lexion, a contract life cycle management software company.

“The value of these is to help the business self-serve questions: ‘Hey, do we have an NDA with so-and-so? Is it coming up for renewal soon? And when it comes for renewal, is there a price cap on how much we can increase?’”

Knowing what’s in the company’s contracts is key, Young says. “If you don’t have standardization among your contracts, it’s hard to tell where you stand as an organization.”

Still, some of the implementation details for contract analysis can be tricky, says Noah Waisberg, co-founder and CEO at Zuva, an AI-powered document processing platform.

For instance, looking for a single assignment clause often can be time-consuming. Additionally, while generative AI can draft contracts, the need for accuracy is so high that using a trusted template can be a better starting point.

“If you get GPT to do it, you actually have to read it—and I would argue that takes longer,” says Waisberg, co-author of AI for Lawyers: How Artificial Intelligence Is Adding Value, Amplifying Expertise and Transforming Careers.

Others question AI-powered tools’ time-saving capabilities in the long term. Ken Adams, chief content officer of LegalSifter, warns that training AI on poorly written contracts or ones with bad data could lead to less-than-ideal outcomes.

Legal Rebels Class of 2024

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Head of the Class: Law schools consider post-ChatGPT coursework

e-Sign on the Dotted Line: When it comes to using generative AI and contracts, the devil is in the details

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This story was originally published in the February-March 2024 issue of the ABA Journal.

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