P2P

64 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 3 Since a significant portion of a typical attorney's day is spent in the Microsoft environment (e.g., Word, Outlook, Teams, etc.), organizations will look for Gen AI solutions that seamlessly integrate with these applications and elevate their functions. For example, Gen AI-powered conversational search, summarization, and document drafting and analysis pair well with Microsoft Word when creating briefs, motions, contracts, and other legal documents. Similarly, natural language chatbots that can answer basic legal queries, engage in multi-turn, iterative conversations, and automate work intake requests via Microsoft Outlook or Teams can improve legal team productivity. Integrating with existing data sources – including proprietary client or corporate data and third-party sources ––will be critical to maximizing the potential and capabilities of an organization's Gen AI investment and minimizing instances of invented content. Most point solutions cannot access data from competitive third-party providers, which limits their effectiveness. Similarly, large global organizations will benefit from the synergies and efficiencies that deploying one integrated Gen AI platform creates. The ability to seamlessly access proprietary corporate or firm-wide data, translate it into the local language, enhance it with localized information (e.g., court and financial records, news, etc.), and leverage it to draft new documents –– all under the governance of local compliance regulations and data security is something that multiple disparate point solutions cannot quickly provide. Additionally, if attorneys travel frequently between global offices, working comfortably in a consistent Gen AI environment will improve efficiency and productivity. Cost and Other Considerations While implementing individual point solutions might seem to be more cost-effective in the short-term than purchasing a fully-featured, integrated Gen AI solution, many metrics beyond cost should be considered, including user efficiency, productivity, and satisfaction, training requirements for multiple point solutions, long-term technology roadmaps and other IT considerations –– all of which can impact the total overall cost of implementing and adopting Gen AI. For example: • Model Upgrades: As models improve and change or new ones are created, organizations might find individual point solutions unable to keep up with the latest advances. An integrated Gen AI platform framework would allow easy model upgrades or replacements as technologies improve, giving organizations peak performance with little disruption. • Continuous innovation: As fierce competition drives new technological and product innovations, first-generation point solutions implemented today could be leap-frogged by other solutions tomorrow, necessitating a disruptive switch in solutions and/or providers to gain the desired features and performance. As use cases evolve, a comprehensive Gen AI platform will be better able to implement new features without disrupting established workflows or existing applications and data integrations. • M&A: As we've seen with other legal start-ups, innovative Gen AI startups will likely be acquired by more prominent players to maintain competitiveness, gain market share, and develop new tech capabilities and talent. Gen AI's rapid descent into Gartner's Trough of Disillusionment could hasten this process, especially for smaller solution providers that cannot keep up with innovation or are unprepared to F E A T U R E S

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