The Point
Artificial intelligence-powered contract review systems allow automated analysis of thousands of contracts at a time, rendering unnecessary their manual review by attorneys.
Use of this technology yields major cost savings in attorneys’ fees, while producing more accurate results.
This Matters
Prior to purchasing a corporation or real estate, the purchaser and its bankers conduct “due diligence” of contracts to which the acquired corporation is a party, or of agreements connected with the real estate. They’re looking for terms that might pose risk, or terms that might be a source of value.
Traditionally, this has meant hiring lawyers to read each contract in search of those terms. Many lawyers. Many hours of reading. Many hours to pay for.
Most purchases still involve this kind of expensive, manual, in-person review by attorneys.
Because …
1. AI-powered systems that automate this analysis have been available for the past three or four years.
On June 1 Thompson Reuters announced the latest of these: HighQ Contract Analysis.
Like others in this field, HighQ Contract Analysis brings together three elements:
1) Data from the marketplace to train and validate the system’s machine learning models — for instance, in a real estate deal, lease terms for properties comparable to the one being acquired;
2) Legal expertise — for instance, in a real estate deal, attorneys expert in building leases make contract review templates that are specific to real estate lease terms, to automate analysis of those terms via AI; and
3) Technology — artificial intelligence-powered functionality to identify and report on terms with which the purchase is concerned (such as, “What are the landlord’s maintenance obligations?”, or “Is there a mutual right to break?”).
Similar, current offerings include LexisNexis’ Survey of Commercial Lease Terms, Blackboiler, and Avvoka.
2. Example of a Use Case.
“A typical use case would be for a buyer assessing a purchase of an office block, based in part on a review of all the contracts associated with the properties being purchased …. The buyer needs to identify key risks, such as how much income is generated by these properties, what properties are likely to be vacant and who is liable for things such as insurance and repair.”
3. The AI-powered systems provide reporting more accurate than attorneys can provide (and, of course, a lot faster).
One of the most famous tests of AI tech-vs-attorneys dates back to 2018. It involved an AI-powered contract analysis system from an Israeli company called “LawGeex“:
“Twenty US-trained lawyers, with decades of experience ranging from law firms to corporations, were asked to issue-spot legal issues in five standard NDAs. They competed against a LawGeex AI system that has been developed for three years and trained on tens of thousands of contracts.
” … the LawGeex Artificial Intelligence achieved an average 94% accuracy rate, ahead of lawyers who achieved an average rate of 85%.”
4. For corporate Legal conducting such due diligence, this kind of AI-powered system presents a chance to cut expensive attorney services, and get greater accuracy, paying cheaper tech charges.
Stephen Embry, former litigation partner in a large law firm who reports on legal technology, puts it this way:
“It’s no secret that contract review is critical and time-consuming, and a source of real pain for legal departments. So tools like HighQ Contract Analysis can make in-house departments much more efficient and cost effective ….
” … All of these products are good news for business, maybe not so good news for lawyers.”
As long as M&A and commercial real estate deals are done, contracts will have to be reviewed as part of due diligence. But, with these AI-powered systems, lawyers won’t be needed for the lion’s share of these reviews. CFOs and other business executives should insist that the corporate law function adopts this technology, captures the savings it makes possible, and get greater accuracy than a tired attorney working the umpteenth hour of his / her billing quota is likely to deliver.