How Artificial Intelligence Saves Money on eDiscovery

We’ve written recently about eDiscovery applications of natural language processing, a specific type of artificial intelligence (AI) and about how AI can streamline eDiscovery and make your work easier. Since time is, as always, money, it should come as no surprise that AI is also a powerful cost-saving tool.

While the technology behind AI is complex, the gist of it is easy to understand: AI is simply the capability of computers to simulate human thought and reasoning. This is frequently accomplished through a type of AI known as machine learning, where the system learns from its own experience. That learning may be accomplished through feedback from a human training partner or through internal sensors that allow the system to detect and learn from its own mistakes. AI simulations have taught themselves multi-step tasks such as how to walk and how to complete the “surprisingly complex” task of getting dressed.

When it comes to eDiscovery, AI is the answer to the problem of exploding data volumes and unprecedented quantities of electronically stored information (ESI).

The Business Pressures Facing Modern Legal Practices

For years, corporate legal departments and law firms have been asked to do more than ever before—while at the same time, corporate legal budgets have been slashed and clients have increasingly tightened their purse strings. It’s true that the old model, wherein the cost of legal services was unpredictable, uncontrollable, and essentially fixed, is outdated. (Arguably, the pricey billable hour was never a good idea, as it encouraged clients to view lawyers a last-ditch call and an expense to be avoided rather than a long-term strategic partner.) But something has to give in the battle to save money on legal services in general and eDiscovery in particular.

Don’t let that something be your sanity. AI applications offer myriad ways to save money at every stage of eDiscovery.

Money-Saving AI Applications in eDiscovery

Advanced processing techniques. Before the 2015 amendments to the Federal Rules of Civil Procedure, the standard approach to eDiscovery was to just save everything and send everything to review. Thankfully, the amendments’ renewed emphasis on proportionality has established that a more measured, reasonable approach is appropriate.

And technology has stepped up to assist that effort, with AI-based processing tools allowing eDiscovery professionals to dramatically cull their data sets early in the process. This, obviously, saves money on every downstream step in the process. It’s common to see 95 percent reductions in data volume through applying the natural language processing-based techniques of email threading, concept clustering, and near-deduplication. That means you could be looking at saving 95 percent on collection, in-house initial review, and the black hole of eDiscovery spending—outsourced document review. You’ll also pay less on an ongoing basis for data hosting and have less to produce, lowering your costs all around.

Technology-assisted review (TAR). Review is still the most expensive stage of eDiscovery, because its nuances require the most hands-on attention from trained—and pricey—attorneys. While AI can’t “do” review all by itself, TAR uses AI to prioritize the most relevant documents for human review. Whether you’re using the older approach of starting from a seed set of pre-coded documents or using a continuous active learning system that learns by observing a human review team, TAR can streamline review tremendously, getting faster results at a lower cost.

Analytics and iterative process improvement. With real-time dashboards displaying data volumes, custodian statistics, hosting costs, and vendor fees, you can improve your eDiscovery workflow with every case. Analyzing your processes with the assistance of smart technology can reveal inefficiencies, bottlenecks, and opportunities to streamline workflows.

In this age of increasing pressure to control spend and stay within ever-shrinking legal budgets, AI’s abilities—to reduce downstream data through efficient processing, save on review using predictive coding, and leverage information gained from real-time analytics to improve workflows—offer huge cost savings for eDiscovery practitioners.

Are you ready to incorporate more intelligent technology into your eDiscovery workflows? We’ve been pioneering best-in-class eDiscovery tools for years, helping attorneys save time and money. Please contact us to learn more.

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