Industry-Sponsored Research Week

AI tools can help address greater contract volumes and finite resources

By David Schwartz
Published: January 12th, 2021

A detailed article on the use of AI in managing sponsored research contracts appears in the December issue of University-Industry Engagement Advisor. For subscription information, click here. 

As with most areas involved in university operations these days, industry contract management staff are facing the timeless challenge of “doing more with less.” Artificial intelligence tools could offer help.

“Contract volumes continuously increase,” said Melissa L. Matsil, director of sponsored research agreements at Rutgers University, during a recent UIDP webinar entitled, ‘How AI & Expertise are Making Contracts Easier.’ “We don’t have enough resources to put toward thoughtful and skilled and studied review of those contracts — all with the expectation and hope that we are mitigating risk for our institution. We’re also asked to be doing better with less, and to help really foster better relationships with our sponsors and find ways in which to meet our sponsors halfway through the creation of fair and reasonable contracts.”

“We currently have over 1,300 active sponsors; we do not have contract personnel who have expertise in 1,300 different sponsors,” added panelist John Hanold, associate vice president for research and director of sponsored programs at Penn State University. “The diversity and complexity of that portfolio just continues to grow.”

Hanold added that with funding from agencies like NIH and NSF now accounting for fewer total research dollars received by universities, negotiations with other sources, such as foreign entities and multiple industry sponsors, are “fraught with challenges.” Industry sponsors, he added, all have their own priorities, and “every single line of the contract could be a potential conversation or argument.”

In the face of that challenge, he continued, “we do not have a rigid sieve through which all these agreements go. We’re expected to come up with creative, flexible solutions. That’s one reason we’re out looking for tools to help make that just a little easier for [our staff].”

Which is where artificial intelligence (AI) comes in. “The challenge universities have is organizing the data within the contracts within a technology and keeping all their obligations straight on an ongoing basis,” said moderator Kevin Miller, CEO of LegalSifter, whose AI software reads a contract and offers advice on key terms and potential problem areas. Those problem areas may involve creating contracts, managing them, negotiating, executing, or some combination of all four.

“When you make a contract it usually takes more than two humans; trying to get them to agree on a whole bunch of language that usually not one of them wrote at first draft, and usually over multiple pages, is really tricky,” Miller summarized. If AI tools can do some of that work, any contracts team would welcome the productivity boost.

Hanold offered a real-world example of the potential of AI, sharing how he had piloted a tool used for a limited number of agreement types “just to see what I thought we could get out of it.”

He explained that speed was not necessarily his only concern. “It also has to do with the confidence of the participants — since these questions are being asked in the margins of a document things might be missed during review. That confidence can lead to some speed in processing, and to more consistency,” he noted. Hanold pointed out that with a hypothetical billion-dollar a year research portfolio, “if a very experienced contract negotiator gets a 2% increase in efficiency and a less experienced one gets 8%, that’s hugely significant.”

The other benefit, he added, was that the tool helped the negotiators focus their efforts. “I’ve seen a lot of different universities have contracting playbooks … and there are disadvantages to the ones that are very detailed,” he observed. “It’s extremely difficult for any negotiator to keep in mind all of the millions of things a university looks at in an agreement for so many sponsors and sponsor types. Working with our implementation team on this, we’ve been taking some guidance documents, some of which are 20 years old, some of which are two months old, and feeding that [data] into a single framework.”

“I came to the table being a complete skeptic, thinking AI was a tool to replace humans rather than to help us do things in a more efficient and scalable way,” added Matsil. “Now I’m a complete convert. We’re starting slow, but I have every intention to expand and bring the good word about how AI can enhance the work we already do in a very meaningful, thoughtful way. Tools can help with scalability, consistency and accuracy. If you use AI, you will have a more consistent approach to contract management across the board.”

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Posted under: University-Industry Engagement Week

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