This article was published online in CIO Applications. It is reprinted here with permission.
In recent years, tools leveraging artificial intelligence (AI) have become increasingly pervasive in the e-discovery world, with terms such as continuous active learning and natural language processing entering the vernacular of lawyers, IT professionals, and clients seeking ways to reduce costs and improve quality. But while technology-assisted review (aka predictive coding) may be the most well-publicized application of AI in the legal community, machine learning and related branches of AI can be harnessed in a variety of other contexts to the benefit of our clients. In this article, we will consider how law firms can extract the most value from AI to help resolve the tension between delivering the high quality legal advice clients demand, while simultaneously keeping fees within clients' tightening legal budgets.
The material in this publication was created as of the date set forth above and is based on laws, court decisions, administrative rulings and congressional materials that existed at that time, and should not be construed as legal advice or legal opinions on specific facts. The information in this publication is not intended to create, and the transmission and receipt of it does not constitute, a lawyer-client relationship.