There is a growing movement toward the use of data analytics, machine learning, and artificial intelligence technologies in a wide range of industries. In fact, many cutting edge technical prognosticators have begun proclaiming that artificial intelligence (AI) has reached breakthrough levels. David Brooks, for example, in a recent New York Times Op-Ed entitled “Our Machine Masters,” explains that these AI advances are driven by three underlying trends: “cheap parallel computation technologies, big data collection, and better algorithms.” Regardless of the underlying rationale, he concludes: “The business plans of the next 10,000 start-ups are easy to forecast: Take X and add A.I. This is a big deal, and now it's here.”

In the legal industry, however, it's been unclear whether AI is having a material impact. Certainly, the use of machine learning applied to the e-discovery process, often called technology assisted review (TAR) or predictive coding, has established a beachhead. But, there is scant data about what kind of actual adoption this use case has, never mind other interesting applications within the legal sphere. This includes information governance and other in-house use cases such as risk assessment, contract review, selection of outside counsel, matter management, billing, and budgeting.

In order to develop baseline usage metrics, the Coalition of Technology Resources for Lawyers (CTRL) commissioned the Information Governance Initiative (IGI) to conduct primary research into these advanced analytical use cases. CTRL is an industry education and research group committed to the development of practical guidance for lawyers as they attempt to leverage various technologies in practice. CTRL has just released its first annual survey entitled: “Data Analytics in the Legal Community: 2015-2016 Trends.”