Extract from Eric Gorman, Jeff Ikejiri, Nathan Giang and Minki Kim’s article “The Right Data Strategy Can Help Your AI Plan Succeed: A Guide for In-House Legal Teams”
Introduction
Generative AI (gen AI) has ushered in a wave of significant transformations across a range of business functions, including corporate legal functions. This innovative technology has the potential to transform legal departments and enhance efficiency across a spectrum of tasks, such as analyzing data, researching legal issues, summarizing documents, and comparing information. Legal organizations are attempting to embrace these new tools. However, they frequently fail to consider a key component needed for success: a robust data strategy.
What Is a ‘Data Strategy’?
Before exploring its role in powering the effective use of gen AI tools, it is critical to understand what a “data strategy” entails in a corporate legal setting. In general, a data strategy is a comprehensive plan that outlines how an organization collects, stores, manages, shares, and uses data. It is a roadmap that aligns the organization’s data initiatives with its strategic business goals. A robust data strategy addresses issues including data governance, data quality, data architecture, and data literacy, helping to ensure that enterprise data are treated as assets that can drive decision-making and innovation. Finally, a foundational component of a data strategy is a blueprint that provides tactical insights into the systems where data resides, the interconnectivity of those systems, and the data stored there, as well as the business questions/considerations that each system (and its associated data) is intended to address. In the context of a corporate legal function, this will typically influence how department resources are capturing and storing information related to legal matters, contracting, and law department knowledge.
