Extract from Nick Inglis’s article “Evaluating the Current and Future State of eDiscovery and its Processes”
In my book Advancing from eDiscovery to Prediscovery, I provide a deep dive into the current state, process evaluation, and future state of Information Governance and eDiscovery, as well as how these disciplines can be aligned.
In this second in a three-part blog series about the book, I will summarize the second section, focusing specifically on the current and future state and process of eDiscovery.
The basis for the eDiscovery profession is, as has been said, best reflected in the EDRM, a linear step-based process released by George Socha, and Tom Gelbmann in 2005. It begins with identifying data related to a case, then moving along a straight line path to collecting, preserving, analyzing, processing, and finally presenting it.
While eDiscovery processes have remained chiefly static since this model was developed, new technologies like Artificial Intelligence (AI) and Machine Learning are gradually being adopted by more companies and firms and presenting an array of intriguing results that are shaking it up.
The professionals who are leading in the adoption of new technologies tend to view eDiscovery as more of a dynamic profession than the linear EDRM presents. Meanwhile, countless lawyers remain on the sidelines with these advancements and continue to perform their role with little changes to the process.
