Prolific reporting on artificial intelligence (AI) applications in business can be intimidating. Especially for those of us who lack hands-on expertise in the use of machines to perform cognitive functions.
For business leaders trying to control corporate legal costs I find that a concrete example can help to by-pass the technical stuff to make the P&L impact clear.
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Take the real estate sector.
Specifically, consider the management of condominiums*.
We begin with a business problem that confronts all condo managers and their boards. In considering any action — or inaction — they must ascertain: What constraints are imposed by this particular condo’s governing documents?
From GlobeSt.com — a publication for real estate lawyers:
“CHICAGO–A typical client for Nicholas Bartzen, an associate with Levenfeld Pearlstein’s [a law firm] Community Association Group [a group of lawyers within the law firm that focuses on serving a specific kind of business client — condo managements and their boards], would be a condominium representative whose building has anywhere from four to 500 units and whose board has a question that needs to be responded to quickly.
“The answer can most likely be found within the condo’s governing documents but as Bartzen tells GlobeSt.com:
“‘ The way these documents have been written is anything but uniform.'”
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The problem:
- This law firm’s condo lawyers are frequently called upon to interpret a particular condo’s governing documents: Can we do this? Do we have to do that?
- Governing documents for condos vary in their terms — a lot.
- It’s too expensive to pay for a lawyer like attorney Bartzen to read — manually and line-by-line — these governing documents in these circumstances.
- But … attorney Bartzen needs to get his answers right. “Close enough” won’t do.
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What’s an AI solution to this problem?
“To find the clauses that he needs within these documents, Bartzen turns to an application called Diligen, which uses machine learning — a type of artificial intelligence that self-corrects and learns as it receives more information — to scan the governing document. To be sure there are other applications on the market that offer similar AI-driven scanning services ….”
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Why is this particular solution effective? According to Mr. Bartzen, it’s the specificity of the match between the technology and his problem:
” … Bartzen likes Diligen because he says it is aimed at his niche practice of law. Other applications that he vetted, he says, ‘didn’t have the algorithms that I need for my clients.'”
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The business significance?
First, economy: This lawyer won’t be reading these governing documents line-by-line every time he has a question about them.
Second, accuracy: There’s evidence that the machine can be more reliable than the human eye and brain when it comes to AI-assisted review of legal documents.
Though it’s early days (in the accumulation of empirical tests and their results) — in the test by a prominent Israel-based legal tech firm called LawGeex that I wrote about in March, AI beat humans 94% to 85% for accuracy.
Third, speed: In the Israel-based legal tech firm’s test the humans took an average of 92 minutes to do their work — versus 26 seconds for the AI platform. (And I read the bio’s of those attorneys — and they were impressive).
* A form of real estate ownership where several units are each separately owned, and so-called “common areas” outside those individual units are jointly owned and managed on behalf of the individual unit owners by a community association.