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36 P E E R T O P E E R : I L T A ' S Q U A R T E R L Y M A G A Z I N E | W I N T E R 2 0 2 4 engineering to work in legal contexts. Once adapted to your needs, users must add steps to their workflow to import data into the Gen AI tool, conduct their analysis, and then move outputs to usable platforms. The second approach utilizes Gen AI features embedded within case management and preparation solutions. This enables your team to use Gen AI designed explicitly for litigation to help manage case data while keeping work centralized. For many law firms still in the early stages of Gen AI implementation, this shows value quickly and encourages strong user adoption. For example, if your firm already has a case management tool, find out if it offers Gen AI to analyze case documents. Instead of manually building a case chronology, using timekeepers to seek relevant events from thousands of case documents, integrated Gen AI can quickly identify key events and the connections between the characters and issues in your case. Then, increased data. Of course, ediscovery and litigation support teams are already well-acquainted with using technology to improve efficiency. Ediscovery platforms (and technology-assisted review) have streamlined processing and review for the last decade. Modern case management solutions that integrate with popular ediscovery software further streamline processes, feeding responsive documents directly into a cloud-based collaborative workspace that allows the litigation team to build their case during data production. These case management solutions enable the creation of chronologies, events, and facts and manage transcripts and designations on the same platform, eliminating the need to hop from tool to tool. And now, the next wave of efficiency-boosting technology is generative AI (Gen AI). There are two main approaches to implementing Gen AI. The first approach involves adopting a broad, standalone Gen AI tool that may require customization or prompt

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