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8 | LEXPERT • June 2018 | www.lexpert.ca/usguide contract review to pinpoint provisions that the UK secession may impact." In discussing the development of their company NexLP, which uses AI to analyze data and identify trends, co-founder Jay Leib described the questions he and partner Dan Roth started to consider in the late 1990s: "What is the future of the industry?" he asked. "ere were whistleblowers in their companies who knew what was going on, and the unstructured data contained the stories. Companies could detect potential problems early on, provide alternatives to counsel and the C-suite, and under- stand their exposure. It would prevent unnecessary legal spend and mitigate risk, thus protecting the company's brand and shareholder value. "Nearly 80 per cent of a company's data is unstructured," Leib said. "While unstructured data represents the lion's share of a company's data, for years lawyers have been stuck with antiquated tools that focus primarily or solely on Boolean search. Better tools are needed to truly understand data, infer meaning, classify the various types of ideas present, and help you get to the result fast — even if that result didn't involve the keywords you used." Document reviewers have always tried to detect what a target company might be concealing, but now vendors of AI tools are developing "technology that can turn information into stories. Story Engine is a program that can read through unstructured data and summarize conver- sations, including the ideas discussed, the frequency of the communications and the mood of the speakers." is is not to say that computers can feel the mood of speakers as humans can, but computers can ingest more unstructured data than we can and, within that, recognize patterns. en enter the humans: corporate leaders will ultimately still make the decision to pursue deals or not. And they will continue to be greatly assisted by internal and external counsel when it comes to strategy. It takes wisdom to discern, "What does it all mean?" So is this what humans do better? Discern meaning in a deal, using "Every decision is a kind of pre- diction … and every prediction, crucially, involves thinking about two distinct things: what you know and what you don't. … A good theory, of course, will do both. But the fact that every prediction must in effect pull double duty creates a certain unavoidable tension." Brian Christian and Tom Griffiths, In Algorithms to Live By Business Issues stories about Friday aernoon partner staffing calls, trying to avoid picking up the phone, still getting caught, and having a ruined weekend. "Misses — pretty much every Big Law midlevel M&A associate through junior partner has a time when they realized their juniors systematically missed finding things they were supposed to. "New Categories — the team finishes a multi-week diligence project, then the deal structure changes. It turns out the original review missed a now-critical category." Abramowitz asks, "Aside from lazy, inexperienced or depressed first years, what are the structural or hierarchical problems with how firms are doing due diligence?" Waisberg replies: "e junior lawyers who do most of the review don't actually know what they're looking for. As smart and well-educated as they may be, and even though their firms may have fancy training programs, it takes practice to spot change of control clauses/exclusivity/ non-compete/MFN. is is the system- atic component of how mistakes get made in due diligence. e random component of errors is that diligence is oen done by tired, distracted, rushed lawyers." Alston Ghafourifar wrote in a VentureBeat article, "By automating labor-intensive, low-value tasks, artificial intelligence systems free up lawyers and other legal professionals to concentrate on complex, high-value projects. But when between 13 and 23 per cent of the average lawyer's time could be automated, the financial impact on the industry is an open question." AI is useful in M&A due diligence for that which is routine, voluminous, needs customization or is nearly invisible and possibly fraudulent. As Waisberg said, "Since lawyers were looking for the same provisions so frequently (e.g., change of control, assign- ment, exclusivity), I thought it might be possible to build soware to help find this info." e "quick win" of AI can simply take in more volume on routine functions than a human can. At the next level, AI is highly suscepti- ble to customization. Brexit, for example: "Brexit Contract Review Solution is a new collaboration between NextLaw Labs (Dentons law firm's legal tech investment vehicle) and R AVN Systems. e solution leverages R AVN's AI technology and a bespoke algorithm co-developed with Dentons' subject matter experts to enable high-volume