Generative AI is revolutionizing the legal industry by driving critical efficiencies in long-established processes. Doing more with less has historically been a challenge for in-house counsel, and teams are eager for new solutions, particularly in e-discovery. As documented in a new IDC Research Study commissioned by Relativity, Generative AI in Legal 2024, 50% of respondents have reported that their AI use has increased over the past two years and respondents reported that 48% of their day-to-day AI use involves generative AI. Knowing where to start with generative AI can feel overwhelming, especially with so many potential applications. To help narrow the options and derive the greatest value, in-house teams need to prioritize solutions that will have the most impact on how they work. For teams ready to apply generative AI directly to e-discovery, first-pass review has proven a great area to start. Why First-Pass Review During a recent industry event, in-house e-discovery leaders highlighted three key reasons for why first-pass review is an ideal starting place: Optimize review workflows: Teams can determine their generative AI workflow and keep human reviewers in the loop. Generative AI-powered technology can be used for first-pass review, followed by a second pass by human reviewers to confirm documents are responsive. Save time and money: Generative AI can analyze thousands of documents per hour, quickly identifying the most relevant content. Standardize document evaluation: Generative AI provides a consistent determination every time, unlike human reviewers who might code the same document differently. It doesn’t get exhausted through long documents and performs a full assessment every time. In the end, experimentation is key to learning quickly and getting the most out of generative AI- powered solutions. From automating routine tasks to taking on parts of the EDRM, continuous testing and refinement finding will help you find the most effective use case for your organization. Trust But Verify As with any new technology or process change, corporate legal teams should approach generative AI with the same caution, identifying inherent risks and verifying outputs. When evaluating the results of generative AI, teams can depend on the same best practice metrics used in e-discovery for the last 20 years: recall, precision, elusion rate and more. By adhering to these metrics for accuracy, teams can easily gauge the performance of their prompt input and compare results to current workflows. Generative AI does introduce new types of risks, but these risks can be mitigated with appropriate technology parameters. For example, Relativity addresses the risk of hallucinations through a chain-of-thought approach, requiring that generative AI validate its citations in the source document it is analyzing. When it comes to security and privacy with generative AI, organizations need to deploy strategies to prevent employee misuse. Public models like ChatGPT are constantly learning, and employees can easily input proprietary data into prompts that become part of the training data set for future outputs. Relativity At Relativity, generative AI solutions are built with privacy and security at their core using a secure integration with Microsoft Azure’s OpenAI services. All data input into Relativity aiR for Review stays within the confines of RelativityOne, and no data is stored or retained by Azure OpenAI. Additionally, all AI innovation rests upon Relativity’s AI Principles, which guide our everyday decision-making to ensure we’re creating technology that’s clear, fair, and gives our customers the utmost control. Starting your Journey Like any journey, the beginning is the hardest part. Here are some tips to get started: Identify effective use cases: Determine where you are spending the most resources and your appetite for generative AI to help address challenges. For ideas, check out the AI Advantage Webinar Series to hear from your peers. Recognize the opportunity: Generative AI offers a unique chance to differentiate yourself as a leader and set your company apart from the competition. Those that started early are already logging many successes and savings. Experiment and learn fast: The more you use your models and train them on your data, the more powerful and accurate they will become to you. Likewise, the faster you start prompting, the faster you can determine what prompts deliver the best results. Most importantly, technology companies are innovating on these products faster than ever and the earlier you sign on, the more you can define changes to products. Collaborate for success: Partner with internal and external teams to identify avenues for enhanced productivity. For example, external teams can use generative AI to save you money on billable hours. Or, complete jobs in a fraction of the time. The next step to implementing generative AI into your e-discovery workflows is simple: set up time with the Relativity team to find the right solution or partner for your business. Topics Artificial Intelligence (AI), ATL Artificial Intelligence Tools, ATL Legal Tech Center, Automation, Generative AI, In-house, Relativity, Sponsored Content, Technology
