Last month, I attended a session titled “Uniquely LLM: How Generative AI is Transforming eDiscovery”. While the event centered on large language models (LLMs), what stood out most was what the technology means for the future of document review, and more importantly, how we lead and deliver that work in my own job.

At this point I think we can all agree that generative AI (GenAI) has moved beyond being a potential buzzword or a trend, but is actually shaping industries. And eDiscovery is no exception. In our industry, it is shaping how we approach review, analysis and production of electronically stored information (ESI). 

Let’s get one thing straight: paralegals are the glue that holds litigation together. As a paralegal, you know you are typically the first to know when discovery deadlines are looming and the last to leave when a production goes out the door. So let’s talk about eDiscovery in a way that gives you the confidence to own your role in it.

Litigators know eDiscovery can be one of the most unpredictable line items in a case budget. One unexpected dataset, increased custodian counts, complex forensic collections, or intractable opposing counsel, and the numbers start to climb – fast.

This fall I attended both Relativity Fest in Chicago, IL and the Everlaw Summit in San Francisco, CA. Like many of you, at Proteus, we’ve been discussing the topic of Generative AI, so it was no surprise that it was a central theme at these two industry conferences, as well. 

Litigators and eDiscovery practitioners often face a common document review challenge when preparing for litigation – too many documents (and too little time to get through them). Linear review, that is, reviewing every document individually, is the most appropriate option in certain situations, but can often be complemented by predictive coding. This is a defensible way to create massive time and cost savings, preserving budget for merits counsel, not for eDiscovery and document review partners