Deploying AI and analytics to improve legal outcomes

A series of massive jury awards have grabbed headlines lately, including an $8 billion punitive damages verdict against Johnson & Johnson. Large jury awards, especially these types of megaverdicts (defined as $10M and up), are magnifying the potential downside of going to trial, causing many companies to consider how to leverage artificial intelligence (AI) and analytics to monitor and plan litigation activities. Through the use of this technology, law departments can make data-driven decisions including whether to go to trial or settle, or even which counsel can best execute case strategy.

At the General Counsel Conference 2019 in New York, after concluding my panel discussion on “Practical  Uses for AI in Corporate Legal,” I was approached by an engaged group of in-house counsel who wanted to understand realistic and cost-effective ways to improve strategy and case outcomes.  While each conversation described different scenarios, I found a number of my answers had common themes.

Use data for predictive modeling

Predictive analytics can give a company a competitive advantage by helping shape litigation strategy. Data can be used to anticipate and mitigate company risk and to develop effective litigation and settlement strategies. The answers lie in the information that’s already available. Historical case information can be analyzed to understand potential outcomes, the likelihood of litigation and whether a case settles or goes to trial. Law departments are also using AI and analytics to help measure spend, contain costs and make smarter budgetary decisions such as the use of billing information to find patterns in spend and case support. Predictive modeling can also aid in outside counsel and supplier selection, including the application of data-driven analysis of historical performance to inform hiring decisions for specific matters.

Articulate the vision and understand what is doable

Businesses need to clearly articulate their challenges to effectively achieve meaningful benefits from AI. Companies refrain from investing in AI due to their inability to define departmental goals and priorities or identify the right stakeholders to align and collaborate with. Assessing needs through strategy workshops is a logical place to start. These workshops should be conducted by data scientists and AI platform experts with organizational legal stakeholders, IT executives, business analysts and data owners to ensure that business requirements are well defined. These meetings can also help determine how to build a solution that applies machine-learning models and algorithms to predict outcomes and identify patterns that meet the requirements. As a result of these sessions, a roadmap can be defined as well as plans to build a proof of concept or set up a pilot.

The right solution considerations

Building an effective AI solution requires high-powered data science talent, which is often scarce. Assembling the components of such a system can be time consuming and complex. Other key considerations include determining the right deployment options such as off cloud (on-premises), private cloud, public cloud or hybrid and whether the AI solutions sought can scale to accommodate the massive amounts of data. Having additional capabilities in other areas such as text-mining (i.e., concept and entity extraction, categorization, summarization and sentiment analysis) can be used to support litigation and investigation activities.

On the topic of litigation and investigations, machine learning and predictive analytics capabilities can help automate tasks and improve planning activities as well as provide significant early case assessment, eDiscovery, and post-production case benefits.  Using these technologies, organizations can reduce timeframes and resources needed to support the review and production of data for litigation.  Legal professionals and investigators can also use these capabilities to design a workflow and approach to address the unique challenges of a compliance investigation enabling teams to unearth facts and establish a cohesive story that can be told or able to prove, defensibly, that no “story” exists.

Come meet us at Legalweek New York February 4-6, 2020 to learn more about using AI/analytics and other legal solutions we have to support the legal industry. We welcome you to use the time to learn more about the integration of our text analytics powered by Magellan with our Axcelerate eDiscovery product to deliver new sentiment analysis capabilities.

Andy Teichholz

Andy Teichholz is the Sr. Industry Strategist for Compliance and Legal at OpenText. He has over 20 years of experience in the legal and compliance industry as a litigator, in-house counsel, consultant, and technology provider. Andy is focused on helping businesses succeed with digital transformation. In this capacity, he has served as a trusted advisor to customers by leveraging his business acumen, industry experience, and technical knowledge to advise on regulatory compliance, information governance, and data privacy issues as well as support complex litigation and regulatory investigations.

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