Peer to Peer Magazine

Summer 2019: Part 1

The quarterly publication of the International Legal Technology Association

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Page 26 of 67

28 We Expect More… AI Promise Meets Reality B Y T J J O H N S O N , B R A D B L I C K S T E I N , A N D B R E N T M E L S O N L egal AI is clickbait for catchy news headlines. It's causing a frantic adoption ener. Harnessing that ener in the right direction is key. In the growing market, focusing on the right Legal AI choice and deploying it successfully are both critical to achieve the promise of AI. We can't just throw money at this challenge and hope it sticks. We need to step back, ensure we understand the business problem being solved while keeping the excitement. Let's start with the notion that there is no such thing as AI software… semantics? Maybe. "AI" as a term is used to cover a pretty wide range of computing capability. Today there ARE software tools enabled and driven by AI. Where core Legal AI capabilities are integrated into software, it "super-powers" the tool, energizing the databases to better efficiencies and driving software to provide better results and outcomes. Some use the phrase "augmented intelligence" as a better descriptor. Planning to Engage One thing is certain, Legal AI is not going away. We feel pressure to incorporate/integrate something that is "Legal AI" into our solutions/ processes/enterprise. We don't want to be left behind and we need to futureproof ourselves. We must plan for the right time to engage. The important question to ask is NOT "How do I bring AI into my legal organization", it's "What business problem can Legal AI software solve?" "What skills are needed to be ready for when Legal AI hits an acceptable maturity level?" The biggest risk for a law firm in adopting Legal AI today is to focus on the advertised features and benefits – the Hype - without understanding how it will impact day- to-day operations or how it can be leveraged for the practice or business of law. Apple, Google and Amazon have all made announcements around big money they are investing in the AI problem to make it better, so we know there will be progress. MIT announced $1 billion in funding to create a new college that combines AI, machine learning, and data science with

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